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Version 2.2 User Manual - Universidad de Zaragoza

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1. period for example if you have selected 3 hourly periods P1 P2 and P3 the net mettering will be applied for each period independently These additional cases PERIODS cannot be selected if there are batteries and the aging model is Schiffer Selling surplus H in tank F Sell surplus HZ in tank difference That is selling H2 stored in the H tank resulting between the HZ in the tank at the end of the year and at the from the difference between the start and the end of beginning the year Price fkg 9 Annual Inflation E 13 3 Purchase and sale prices as well as inflation rates must be introduced for all cases described above Data to Compare with AC grid supply only On the left bottom of the tap there is a Data to compare with electrical supply only from 40 conventional grid panel to Compare with AC grid supply only for comparison with the hypothetical Total cost installation of AC and connection 3900 O amp M annual cost of grid connection 130 t R Dufo L pez HOGA User Manual 58 case in which there was no autonomous system but all the energy is bought to AC grid Give the hypothetical total initial cost of installing AC grid connection and the annual maintenance cost It should be noted that these costs have no relation with the autonomous system itself they only serve to compare with a case where not acquired a standalone system but all 1t did was connect to the network and co
2. Add from Database Zero e ll Mame Power kw Aca cost 0 0 0 1 9360 20 2 17550 20 3 23400 20 La Elec Consumo kVV y Eficiencia PCS O Lifetime and O amp M costs data Electricity DC cn 7 pears and 4pr 7 Hours and h Ha Pa tn a t E 2 E i LO D w Eficiencia de PCS a w 0 0 005 0 01 0 015 0 02 0 025 0 03 0 035 0 04 0 045 0 05 0 055 0 06 HZ OUTPUT MASS FLOW kg h HHY of HZ is 39 4 kih kg Nominal H2 mass flow 0 06 koh Itis needed at least 0 6 kim to generate H2 FUEL CELL ELECTROLYAER HZ TANK Annual Inflation Rate for Fuel Cells Electrolyzers and y y Max Variation of Fuel Cells Electrolyzers and H2 Tanks Cost e g for an H2 Tank Cost s expected 390 reduction on current cost introduce IN 30 Es Limit is reached in 21 9 pears R Dufo L pez HOGA User Manual 123 3 15 3 H2 Tank When an electrolyzer is present an estimation must be made of several parameters 1HOGA will use these for all combinations once the full year simulation is concluded in order to determine the size required for the Hz tank where H generated by the electrolyzer is stored The stored Hz provides the consumption values and the H required by the fuel cell The tank cost must also be estimated in kg of capacity and a maximum tank size must be determined by 1HOGA Account must be taken of the fact that the H2TANK setpoint variable must be obtained a
3. then the next time you open the xlsx file Excel will not ask you any question The Excel shows the results for each of the N series cases prob numbers 0 to N 1 in the example cases O to 499 and for each of the cases 5 7 o Probability variables Combinations of average average Std Dev average 3Std Dev average Std Dev average 3Std Dev of different variables taken into account in the probability anaylsis cases numbers N to Nas number of probability variables 7 in the example cases 500 to 524 It also shows the minimum R Dufo L pez HOGA User Manual 162 maximum average and standard deviation of each result variable Al G E Project 1 hoga Solution 0 y 4 BoOJpe y Do E f 6 4 12 1 K Mmm nn oo Project 1 hcpa Solution 0 _2 COMPONENTS PV generator 3240 Wp slope 602 Wind turbines group DC 546 W AC Generator 1900 VA Batteries bank 9360 Wh Inverter 500 VA Rectifier AC DC 496 W 3 ESTRATEGY LOAD FOLLOWING Pigen INF W Pmin_gen 570 W SOC stp_gen 20 SOC min 20 l el _5 RESULTS FOR THE DIFFERENT COMBINATIONS OF THE PROBABILITY ANALYSIS _6 First 500 rows are the results corresponding to random data series Next 25 rows correspond to characteristical cases Next row correspond to the case shown in simulation Finally MINIMUM MAXIMU 7 _8 Results corresponding to random data series _9 Case prob Rad kWh m2 day Wind m s W_flow
4. 165 150 135 120 105 90 75 60 45 30 15 0 15 30 45 60 75 530 105 120 135 150 165 180 Azimuth For reference solar trajectories are shown for winter and summer solstices for latitude 41 66 ee Solar tracking The user must select the method applied for sun tracking The default value 15 No Sun Tracking Tracking System No Tracking Mo Tracking Horizontal Ass Vertical Axis Two Axis R Dufo L pez HOGA User Manual 65 Optimal slope button The optimal slope is shown after clicking the button Optimal slope After some seconds the following screen is shown 3 Optimal slope for PV panels da gt _ m i Rad Slope Opt kwh da 2 37 Rad 15 kwh day Rad 30 kWh day Rad 45 Kw h day Rad 60 kwh day Rad 75 KW h day 2 9 2 28 2 65 2 89 2 97 Rad 30 kwh day Slope Opt 60 2 67 316 3 56 3 77 3 78 3 58 3 21 53 3 8 4 64 5 01 5 1 4 92 4 47 3 78 43 5 1 5 74 5 84 5 62 5 11 4 33 3 37 27 5 84 6 33 6 19 5 69 43 3 92 2 81 12 6 4 712 6 72 6 02 5 3 04 2 57 6 7 19 7 27 6 94 6 28 5 27 4 03 2 75 3 7 31 6 68 6 7 6 34 5 61 4 61 3 41 23 6 74 5 88 6 31 6 36 6 04 5 37 4 39 40 6 39 4 45 5 12 5 5 5 55 5 27 4 68 55 5 57 2 3 3 46 3 82 3 96 3 88 3 57 62 3 97 1 97 2 32 2 54 2 63 2 58 2 39 62 2 63 4 88 5 07 5 4 65 4 07 3 3 33 5 08 Month of lowest irradiation over horizontal surface is DECEMBER Optimal slope to maximize the irradiatio
5. E total E Unmet E bought Cord HP Minihidro 0 27 AC Grid 0 11 Etotal eH yrl Total Load in the year EU niet EM he yr Unmet Load not covered by the standalone system Ebought4Corid kM heyr Energy bought to 4C grid 5 000 10 000 15 000 20 000 Total load per person and year kWh person yr Eperson max Unmet load 0 265 kiyhpersondyr gt IDH maximum 0 51379 On the left HDI you should enter the number of people in the community to use electricity of the installation as well as the constants for the HDI On the right you enter data for the creation of employment for each technology number of jobs per GWh of energy generated Default data were obtained from the doctoral thesis of Juan Carlos Rojas Zerpa 37 R Dufo L pez HOGA User Manual 126 3 17 Sensitivity Analysis Only in PRO version Pressing the button on the main screen Sensitivity Analysis the following screen appears if you have not entered all the data and resource consumption a message appears saying that you first have to enter the data JE SENSITIVITY ANALYSIS Lo ade Wind Solar Load Interest and inflation AC Gen Fuel Inflation Components costs SENSITIVITY ANALYSIS OF LOAD Load1 Case base Average Daily Total Load 3 63 kWh Add Remove last one Ez Draw OK The screen has six tabs where you enter data for HOGA perform sensitivity analysis 1f desired Sensitivity of w
6. IMPORT HOURLY DATA FILE R Dufo L pez HOGA User Manual 47 Monthly Average Data source le Monthly Average Loadprofle Import Hourly data file data im 4 and kg Hz The default option is Monthly Average This is adequate in case the expected load corresponds to monthly average hourly values Data on load must be introduced on the load tables in watts and kg H2 Three load tables are available for AC DC and Hp click on the tabs to display these Load profiles are shown for the month under the cursor bottom left AC loads are displayed in blue with DC loads in green and H loads in red the latter are shown as energy with an HHV value of 39 400 Wh kg for H2 Also water consumption from water tank previously pumped can be defined AC LOAD W tab In this table you must enter the AC load W values for each hour of the day for each month AC LOAD tw DC LOAD w I H2 LOAD kg WATER m3 day FROM WATER TANK PREVIOUSLY PUMPED PURCHASE SELL ENERGY GY Monn Oih 12h 23h 34h 45h 56h 67h 78h em 9410h 1011h 1142h 12 13h 1344h 1415h 15 164 JANUARY 22 110 176 132 110 110 308 308 220 176 15 FEBRUARY 22 E 7 E ET 7 110 176 132 110 110 308 308 220 176 15 MARCH 22 22 22 22 22 22 110 176 132 110 110 308 308 220 176 15 E APRIL 22 22 22 22 22 22 110 176 132 110 110 308 308 220 176 15 HAT 22 22 22 22 22 22 110 176 132 110 110 308 308 220 176 15
7. Tesis Doctoral Departamento de Ingenier a El ctrica Universidad de Zaragoza Abril 2007 10 Dufo L pez R Bernal A gust n JL 2011 Generaci n de energ a el ctrica con fuentes renovables Optimizaci n de sistemas h bridos renovables con almacenamiento energ tico mediante algoritmos gen ticos Editorial Acad mica Espa ola LAP LAMBERT Academic Publishing GMBH amp Co KG Saarbriicken Alemania ISBN 978 3 8443 4336 6 11 Dufo L pez R Bernal Agustin JL Yusta Loyo JM Dominguez Navarro JA Ramirez Rosado IJ Lujano J Aso I Multi objective optimization minimizing cost and life cycle emissions of stand alone PV wind diesel systems with batteries storage Applied Energy Volume 88 Issue 11 November 2011 Pages 4033 4041 12 Hybrid Optimization Model for Electric Renewables HOMER http www nrel gov homer 13 Back T Fogel DB Michalewicz Z Evolutionary Computation 1 Basic Algorithms and Operators Bristol and Philadelphia Institute of Physics Publishing R Dufo L pez HOGA User Manual 189 2000 14 Michalewicz Z Fogel DB How to solve it modern heuristics 2nd ed Berlin Springer 2004 15 Coello CA Veldhuizen DAV Lamont GB Evolutionary Algorithms for Solving Multi Objective Problems New York Kluwer Academic Plenum Publishers 2002 16 Zitzler E Thiele L Multiobjective evolutionary algorithms a comparative case study and the strength Pareto approach
8. button Clicking on the button SHADOWS a window is opened where we define the obstacles elevation versus azimuth and the reduction factor of the direct radiation if the obstacle covers the sun default 100 In the example we have added two obstacles one of elevation 50 in azimuth 15 to O southeast and a 30 elevation in azimuth 15 to 30 southwest As reference curves solar trajectories in solstices are shown all solar trajectories are between both For each range of azimuth indicate elevation of obstacles and the percentage of reduction in direct wradiation From 2 160 NM 165 150 135 120 105 30 rD B0 45 30 15 To 1565 150 135 120 105 30 T5 B 45 30 15 0 5 Obstacles elevation 2 0 0 0 0 0 O 0 0 O 0 50 Reduction in direct irradiation 100 100 100 100 100 100 100 100 100 100 100 100 Azimat From O S 15 30 45 60 fo 30 105 120 135 150 7165 lo E la 0 45 BU fo 30 105 120 135 150 165 BOTH Obstacles elevation B 30 0 0 0 O 0 0 0 O 0 0 Reduction in direct irradiation 100 100 100 100 100 100 100 100 100 100 100 100 Azimut OBSTACLES ELEVATION vs AZIMUTH a a gt gt __ _ gt gt _ _ gt gt gt gt gt gt _ gt gt _ _____ gt gt _ ___ gt gt __ gt gt __ gt gt _ _ _ __ gt _ __ __ gt gt ___ gt ____ gt __ gt _ gt gt ____ _ _ Elevation BE 8 amp
9. 2007 27 Batteries Model Ah Schuhmacher 1994 EB aM Marnwell eMchowan 1993 Copeth 1994 Schiffer 2007 Copetti or Schiffer Models Only in PRO version If we choose the models Schiffer or Copetti the button Control Data appears Batteries Model Battenes Model Ah Schuhmacher 1993 Ah Schuhmacher 1993 Eibar M anwell HcGowan 1993 Ruibal ManwellMclowan 1333 9 Copetti1994 ContolData Copetti1994 ContolData o Schiffer 2007 Schiffer bat Data R Dufo L pez HOGA User Manual 99 By checking button Control Data 1t shows the screen for the auxiliary components for battery charging the Battery Charge Regulator and the rectifier or battery charger which will exist if there 1s an AC generator H AUXILIARY COMPONENTS FOR BATTERIES CHARGE BATTERIES CHARGE REGULATOR 24 Y Acquisition cost fey El 4 Treg max A Lifetime 10 years RECTIFIER AC DC CONVERTER 230 Vac f 24 Vdc Acquisition cost 100 200 Pnom kit Lifetime 10 years Efficiency 90 BATTERIES CHARGE DISCHARGE REGULATION TO BE APPLIED ONLY IN COPETTY OR SCHIFFER MODELS REFERED TO 2 CELLS o CONTROL PH CONTROL ON OFF OWER CHARGE PROTECTION PW H Float Charging voltage 2 3 y Boost Charging voltage 2 4 O YER DISCHARGE PROTECTION Boost duration 2 Low Voltage Disconnect LD 1 85 Boost activated if SOC lt FO Low voltage Reconnect LVR 2 Low SOC Disconnect 30 Low SOC Re
10. E JUNE 22 22 22 22 22 22 110 176 132 110 110 308 308 220 176 15 E JULY 22 22 22 22 22 22 110 176 132 110 110 308 308 220 176 15 E AUGUST 22 22 22 22 22 22 110 176 132 110 110 308 308 220 176 15 SEPTEMBER 22 22 22 22 22 22 110 176 132 110 110 308 308 220 176 15 OCTOBER 22 22 22 22 22 22 110 176 132 110 110 308 308 220 176 15 E NOVEMBER 22 22 22 22 22 22 110 176 132 110 110 308 308 220 176 15 E DECEMBER 22 22 22 22 22 22 110 176 132 110 110 308 308 220 176 15 E 4 b Scale factor for Monday Friday 1 Scale factor forthe weekend 1 In the tables AC DC and H table data can be written quickly if all the months have the same value for an hour For example if the load for every month at the first hour of the day 0 1h is the same for example 500 W you must enter this value of load in the cell JANUARY 0 1h and then you click your mouse in the cell JANUARY 1 2h then all the cells of the column 0 1h will take the same value 500 W Also scale factor must be entered one for weekdays and another one for weekend A pair of scale factors must be entered for each kind of load Scale factor for Monday Friday i Scale factor for the weekend 1 Scale factor can also be used to enter data in kW indicating scale factors of 1000 R Dufo L pez HOGA User Manual 48 DC LOAD W tab In this table you must enter the DC load W values for each hour of the day for each month Scale factor must be entered one for weekdays and a
11. HDI and JOBS Sensitibity Analysis The main screen shows menus and buttons All of them provide access to additional screens Probability Analysis 43 CALCULATE E REPORT where the different system elements may be selected Text fields and check boxes are also available for further input of system details On the main screen there are 5 tabs where data needed must be entered in the 5th tab you see the results of the optimization as a graph R GENERAL DATA OPTIMIZATION CONTROL STRATEGIES FINANCIAL DATA RESULTS CHART Dufo L pez HOGA User Manual 3 1 1 GENERAL DATA tab In this tab we must enter the most important Which components can have the system Maximum and minimum allowed for some components Constraints that must be met 30 Maximum execution time and who we want to allow selected optimization parameters HOGA or user Also indicated The date and time of the beginning of the simulation The comparison with the worst month method of photovoltaic battery systems GENERAL DATA COMPONENTS PY panels Wind turbines Hydro turbine Wf Batteries 4 AL Generator Inverter H2 F C Elpz COMPONENTS OPTIMIZATION CONTROLSTRATEGIES FIMANCIAL DATA RESULTS CHART MIN AND M x No COMPONENTS IN PARALLEL Batteries in parallel Min 1 Max 1 PY panels in parallel Min O Max 12 1 1 CONSTRAINTS Ml
12. HOMER The current 1HOGA version allows the user to select this or an alternative more complex and accurate method the Cycle Count or Rainflow method according to Downing s Algorithm Downing and Socie 1982 28 This method is utilized by applications that provide more accurate simulations such as HYBRID2 29 In the current version it has been added the method proposed by Schiffer et al 27 much more accurate model which includes aging corrosion in 38 we showed that Schiffer model predicts correctly batteries lifetime while other models can predict 2 or 3 times the real lifetime Once the system has been calculated for all the hours in one year HOGA calculates the different parameters which will determine the system s NPC throughout its useful lifecycle fuel consumption energy cycled by the batteries hours of operation of the system components generation of CO etc With this data costs may be ascertained for fuel operation maintenance and acquisition as well as replacement periods for the different components Finally the NPC value may be calculated for the system thereby ensuring an adequate combination of control variables and elements R Dufo L pez HOGA R Dufo L pez User Manual 17 HOGA User Manual 18 2 INSTALLING AND RUNNING THE APPLICATION 2 1 Installing HOGA runs in Windows XP Vista or Seven A minimum value of 1152x864 pixels is recommended for screen resolution Any lowe
13. Hourly simulation Hourly values separately Monthly and annual Average Power Monthly values Annual values Hydrogen detailed AC Generator detailed Water load MONTHLY WATER CONSUMPTION WATER PUMPED mo AND WATER STORED IN TANK AT THE END OF EACH MONTH m ay M Water in tank m3 a Month E Water Load MI Water pumped Water in tank at the end of the month MONTHLY ENERGY OF WATER LOAD WATER PUMPED kWh AND WATER STORED IN TANK AT THE END OF EACH MONTH E T Ne A E PR qa nee T A S E eae AS IS eee Rom ar E Oe eens Pees E A O hale aad atari zjstgig lg delat la Rs dd ad 3 8 D E oe Ea z Ea SER ea 36 amp B 50 3 4 wo y o 1 2 3 4 5 6 9 10 11 12 ul Tate 0 1 000 2 000 3 000 4 000 5 000 6 000 7 000 3 000 0 1 000 2 000 3 000 4 000 5 000 6 000 7 000 8 000 0 1 000 2 000 3 000 4 000 5 000 6 000 7 000 8 000 Hourly Energy of Water Load kWh Hourly Energy of Water Pumped kWh Hourly Energy of Water Stored in Tank kWh 1 0 1 000 2 000 3 000 4 000 5 000 6 000 7 000 8 000 0 1 000 2 000 3 000 4 000 5 000 6 000 7 000 3 000 0 1 000 2 000 3 000 4 000 5 000 6 000 7 000 3 000 Save Data Only in PRO PRO and EDU versions Represented hourly data can be exported to a file by clicking the Save Simulation Data button Data is stored in hourly rows and in columns there are the different values You can choose to save as an Excel file xls or as a text file txt For sav
14. This factor is an indicator of the randomness of wind speeds High values of this parameter show that wind speeds for a given time of the day are largely dependent upon wind speeds for the preceeding time interval Lower values indicate a more random variation of wind speeds with a lesser autocorrelation between time of the day and speed readings This parameter is directly influenced by local land topography Autocorrelation factors are usually lower for complex local topographic conditions and higher for more uniform ground These two parameters are generic 1 e applicable to a full year whereas the parameters described below change every month Night Speed m s This indicates the average wind speed at night for a given month Wind speeds are higher during daytime for most locations in our planet since temperature differences between landmasses and oceans are higher during that period Besides more turbulences and changes R Dufo L pez HOGA User Manual 75 in the direction of the wind are present during daytime The chart below shows average wind speeds measured at 1 hour intervals in January for an inland region in China jam mm fa ma o I I I I I I a a a I I ie ae iege 1 1 l 1 as i i i E REDE Biar JE senescence a DOR sees a Des Pes De eee AE ls KEK oo il edb CG DR KEEN BOP HOUR The curve may be modelled according to the time at which maximum speed is recorded so that
15. 2 E az naco J 0 86 o Monthly Average Speed Metheorological data NASA web gt Night speed Amplitude F Factor and Hour max speed Input Data Month Av wind m s a JANUARY Av wind ms FEBRUARY f Jan 3 8 MAR CH Feb 3 8 Mar 3 7 Apr 3 6 May 3 Jun 2 8 Jul 3 1 Aug 2 9 Sep 2 8 Her E Nov 3 5 Dic 3 7 Anemometer Height 10 m AUGUST SEPTEMBER OCTOBER _ NOVEMBER gt DECEMBER Form Factor b 2 Autocorrelation factor 0 82 10 12 14 16 18 20 22 24 26 28 30 Force 0 consecutive days with wind lt 3 m sinmonth January Y Av sp year m s Wind speed m s A Bow Info time of calm wind Calm is considered Scale by 1 Scaled Average Speed m s Scaled Average Speed m s OK 3 32 Form factor of the wind speed serial 2 1 lt 3 m s It may be difficult to know or estimate wind related data for the site where the system will be installed Two options are available for Data Sources Monthly Averages or Import Hourly Data File The best choice will always be a file with hourly values This is sometimes difficult to obtain in this case an estimation will be necessary for average monthly values Data source f Monthly Average C Import Hourly Data File data in m s Anemomenter height The user must always state the height used for all wind related readings This data will be normalized for the height of the wind turbine s hub Anemometer Height 10
16. Cost NPCJ emission 500200 kglO2 yr Mamet foto kh yr meta D Prange bi et Ren Cost E E kwh Simulate Report L Elyzer 0 44 SIMULATE REPORT 0 44 SIMULATE REPORT 0 44 SIMULATE REPORT 0 44 SIMULATE REPORT 0 44 SIMULATE REPORT 0 44 SIMULATE REPORT 0 44 SIMULATE REPORT 0 44 SIMULATE REPORT 0 44 SIMULATE REPORT Y OTHERS AUX 3 DC Voltage 24 Y SS 10 ACVoltage 230 Y 11 12 PRE SIZING 13 Energy Storage 4 days range 14 Max bat parallel gt Cn min Max PY pan parallel gt P min Jm L Max wind t parallel gt P min Sensitivity analysis 3 Hybrid system Best solution E E COMPONENTS 2s x 9p PY panels of 135 W slope 60 12s x 1p batteries of 390 A h 4 AC Generator 4 kVA 2 Inv 500 VA 2 Unmet load 0 77 NPC sensitivity Analysis 14520 0 44 kWh a CALCULATE STRATEGY LOAD FOLLOWING Plgen INF Pmin_gen 1200 Peritical_gen 0 SOC setpoint_gen 20 SOC min 20 Sensitivity Analysis Summary Save Table as Excel oo coo oa oo eo S 0 0 0 0 0 0 0 R Dufo L pez HOGA User Manual 180 4 7 Summary of the sensitivity analysis Once the sensitivity analysis is done once all optimizations have been performed one for each combination of sensitivity analysis cases by clicking on the Sensitivity Analysis Summary button on the main screen bottom it is shown for each sensitivity a
17. EEE Transactions on Evolutionary Computation 1999 3 4 257 71 17 Graham V A and Hollands K G T 1990 A method to generate synthetic hourly solar radiation globally Solar Energy Vol 44 6 pp 333 341 18 Liu B H Jordan R C 1960 The interrelationships and characteristic distributions of direct diffuse and total solar radiation Solar Energy 4 1 19 19 Hay J E Davies J A 1978 Calculation of the Solar Radiation Incident on an Inclined Surface Proceedings First Canadian Solar Radiation Data Workshop J E Hay and T K Won eds Toronto Ontario Canada 20 Rietveld M A new method for estimating the regression coefficients in the formula relating solar radiation to sunshine Agricultural Meteorology 1978 19 243 52 21 Collares Pereira M Rabl A 1979 The average distribution of solar radiation correlations between diffuse and hemispherical and between daily and hourly insolation values SolarEnergy 22 pp 155 164 22 Erbs D G Klein S A Duffie J A 1982 Estimation of the Diffuse Radiation Fraction for Hourly Daily and Monthly average Global Radiation Solar Energy 28 4 pp 293 302 23 Schuhmacher J 1993 INSEL Interactive Simulation of Renewable Electrical Energy Supply Systems Reference Manual University of Oldenburg Renewable Energy Group Dept of Physics PO Box 2503 D 26111 Oldenburg 24 Manwell JF McGowan JG A Lead
18. Loss factor During simulation 1HOGA calculates the current generated by PV panels as a function of irradiation and shortcut current However a loss factor must be introduced to account for dirt possible errors on the panel orientation Loss Factor selected 1 2 R Dufo L pez HOGA User Manual 85 Maximum Power Point Tracking The user must select whether a MPPT Maximum Power Point Tracking is available for maximum power PY battery charge regulator includes Masinum Power Point Tracking MPPT If the checkbox MPPT is unchecked If not checked MPPT the output voltage of the PV generator is considered fixed by battery voltage DC bus voltage so that the voltage on PV array will be the nominal voltage of the system Vpuspc 1 e the nominal voltage of the PV panel multiplied by the number of panels in serial Vouspc Vn panel Npanels serial In this case the power supplied by the photovoltaic generator is calculated as follows P Isc G Vn_panel Npanels_serial Npanels_parallel LF Where G is the irradiance on the surface of the panels in kW m2 and LF is the loss factor selected In this case the output power practically do not depends on ambient temperature except for extreme temperature values Selecting the MPPT box In this case the battery charge regulator provides the maximum power point so that at each moment the panels generate the maximum possible power depending on the irradiance The power is calcul
19. Mean 3 332 Std Dev 0 198 m s Maximum 3 95 Min 2 63 m s Probability Average Wind speed m s Hourly variability in the series O In the simulation show the case obtained with the following data Load Irradiation Wind Speed Average v Average Average In the case of the simulation include hourly variability In the probability analysis report in the last two charts show the probability distribution of Hours running AC Generator h yr v Annual cost of fuel of AC Generator currency yr When clicking at any cell of the results table do not update results OK R Dufo L pez Standard Deviation 0 2 kWh m2 day d ha Mean 4 658 Std Dev 0 211 kiwh m2 day Maximum 4 53 Min 2 74 kWh day Maximum 5 19 Min 4 07 kWh m2 day Average Irrad kWh m2 day HOGA User Manual 131 With this analysis for each combination of components and control strategy to study there will be N different combinations of hourly series of the variables which variability we want to analyze load irradiation wind speed and or water flow Each hourly series of load and resources is derived from the original series but its average value will be obtained according to a Gaussian probability distribution with mean the original average value defined in their screens and standard deviation set in this screen N the number of series to be calculated for each combination of components and control strategy mus
20. Month MUA Energy produced by Fuel Cell EH Energy consumed by Electrolyzer AC generator detailed tab R Dufo L pez HOGA User Manual 156 Showing details on consumption and AC generator power The example figure of this simulation corresponds to a system different from the simulation seen before Hourly simulation Hourly values separately Monthly and annual Average Power Monthly values Annual values Hydrogen detailed AC Generator detailed Fuel consumption mn O anu Energy kWh TAE o MN n A A la a el AA NA o b m Fuel consumption o N o o e o O O 1 000 2000 3 000 4 000 5 000 6 000 7 000 8 000 Hour of the year Water load tab so Sec deco a a Se chases PASA A EVER A DESA SE Water load Month MONTHLY ELECTRICITY GENERATED BY AC GENERATOR kWh a ASE a e A AGE A A AA 0 i i 0 1 000 2 000 3 000 4 000 5 000 6 000 7 000 8 000 Hour of the year In the case that there is water consumption which has previously been pumped to water tank from river or from waterhole 1t shows the values of consumed and pumped water for each month in m3 and kWh of energy as well as water accumulated in the tank at the end of each month Also shown are the hourly values throughout the year separated The example figure of this simulation corresponds to a system different from the simulation seen before R Dufo L pez HOGA User Manual 157
21. REPO DCYoltage 24 Y ACYoltage 230 Y PRE SIZING Energy Storage 4 days range Max bat parallel gt Cn min Max PY pan parallel gt P min Max wind t parallel gt P min eo ooo ooo e j HDI and JOBS Hybrid system Best solution Sensitibity Analysis COMPONENTS 2s x 9p PY panels of 135 W slope 609 12s x 1p batteries of 390 A h 4 AC Generator of 1 9 kVA 2 Inv 500 VA 4 Rect 493W 2 Unmet load 0 4 NPC 20824 0 63 kwh Probability Analysis STRATEGY LOAD FOLLOWING P1gen INF Pmin_gen 570 W Poritical gem 0 SOC setpoint gen 20 SOC min 20 43 CALCULATE Save Table as Excel Save Excel Table At the end of the simulation it 1s enabled in the lower right corner the Save Table as Excel If you click it an Excel file with the values of the result table will be generated After you save the Excel file if you open the file with Microsoft Excel 1t reports a message asking about opening the file then you click on Yes as answer and the file is correctly opened by Microsoft Excel R Dufo L pez HOGA User Manual 140 Es Inicio Insertar Dise o de p gina F rmulas Datos Revisar Vista Acrobat O s x E a Calibri ju ET Ajustar texto General 5 E x em Ex Ei ae Ar A r7 iaie ieee rs ca At N E Portapapeles fa Fuente Ta Alineaci n Ta N mero Ta Celdas Modificar Aro v fe Project 1 HO
22. Sell Eto AC grid Purchase E from AC grid Incomes selling E Cost purchasing E 8810 TOTAL 0 650 65 o o o o RR11 Then the cash flows of costs and incomes are shown Below 1s displayed the number of cycles for each case depth of discharge DOD conducted by the batteries using the method Rainflow to count EFi B 6 D E F G H I J K L M N o P a R im 3814 3815 CASH FLOW THROUGHOUT SYSTEM LIFETIME 3816 CASH FLOW OF COSTS AND INCOMES 3817 Initial cost of investment 15883 5 S included installation and initial variable costs of 693 8 Loan of 80 3818 All values in currency Costs Incomes For each component cahs flow includes initial acquisition cost year 0 replacement costs years when the component must be replaced and incomes of selling the component at 3819 YEAR Costs PV Gen O amp M PV Gen Costs Wind T O amp M Wind T Costs Hydro T O amp M Hydro T Costs AC Gen O amp M AC Gen Costs Inv 3820 cash year NPC cash year NPC cash year NPC cash year NPC cash year NPC cash year NPC cash year NPC cash year NPC cash yea 3821 0 8642 4 8642 4 o o 1241 5 1241 5 o o o o 0 o 1040 1040 o o 5 3822 pi o o 141 2 135 8 o o 66 3 63 8 o 0 0 0 o o 13 7 13 2 3823 2 0 o 144 133 2 o o 67 6 62 5 o o o o o o 14 13 3824 3 o o 146 9 130 6 o o 69 61 3 o o o o o o 143 12 7 3825 4 o o 1498 128 1 o o 70 4 60 1 o 0 o o o o 146 12 5 3826 5 o o 152 8 125 6 o o 71 8 59 o o o o o o 149 EZ 3827 6 0 o 155 9 1
23. Tipo HOGA project hoga Cancelar R Dufo L pez HOGA 3 1 Main Screen Project Data Calculate DataBase Report Help User Manual Y LOAD AC GRID RESOURCES Y SOLAR WIND HYDRO COMPONENTS Y PY PANELS WIND TURB HYDRO TURB BATTERIES Y INVERTERS Y AC GENERATOR H2 F C Elyzer GENERAL DATA OPTIMIZATION CONTROL STRATEGIES FINANCIAL DATA RESULTS CHART COMPONENTS V PY panels Hydro turbine V Batteries AC Generator J Inverter 1 H2 F C Elyz MIN AND MAX No COMPONENTS IN PARALLEL Batteries in parallel Min 1 Max 1 PY panels in parallel Min 0 Max 12 Wind T m parallel Min 1 Max 1 CONSTRAINTS Maximum Unmet Load allowed 1 annual Unmet load can be covered by AC grid if it exists and it is allowed in LOAD AC GRID window OPTIMIZATION PARAMETERS SELECTED BY USER o HOGA Maximum execution time 0 h 15 min Display Parameters Z Minimum time for the genetic algorithms Simulation start hour O day 1 month 1 Compare with Worth Month Method Pv bat Days of battery auton 4 7 CHARGE BAT DC Voltage 48 Y AC Voltage 230 Y PRE SIZING Energy Storage 4 days auton Max bat parallel gt Cn min Max wind t parallel gt P min Max PY pan parallel gt P min
24. You must copy these 8760 values to a txt file e Files obtained by Windfreedom software files txt These files have been obtained using Windfreedom software downloadable from the website of Joaquin Mur http www windygrid org software fpage pagel with this software you can obtain hourly wind data from many meteorological stations in the R Dufo L pez HOGA User Manual 71 world To obtain these files you must have installed the software Wolfram Mathematica otherwise you will not be able to download the data 1 full year data should be downloaded using Windfreedom beginning at O h 1 January and ending at 24 pm on December 31 This txt file can be directly open by 1HOGA e Files with extension vnt They include data on the height at which readings were taken as well as hourly wind speed values e Files with extension wnd These files are generated by the HOMER application e Files with extension dat SCRAM files These may be downloaded from the EPA web site in the U S When importing wind data the probability of the wind speed is plotted and also the form factor of the Weibull distribution that fits best is written Monthly Average data Data source Monthly Average Import hour data file 6760 values in m s If we do not have the hourly wind data we can synthetically generate this from monthly average data Monthly values can be Monthly Average Speed Values Monthly Average Nigtht speed
25. all of these related to a horizontal surface and to the plane of the PV array Draw button Clicking on Draw will show the chart for the calculated data Hourly irradiation values will be displayed in red for a horizontal surface and in green for the plane of the PV array as calculated by HOGA R Dufo L pez HOGA User Manual 68 Graph ago t a a a ver Plane of PV array 60 Horiz surface BACK Export buttons Click on Export slope to export data referred to hourly irradiation values on the plane of the PV array tilted surface of the PV panels Click on Export horiz to export data referred to hourly irradiation values on a horizontal surface Select Ghoriz in case the irradiation data for the current project must be used for additional projects Scale factor A scale factor for the hourly irradiation can be defined default 1 The hourly irradiation over tilted surface will be multiplied by the scale factor when we click the OK button Scale factor Click on OK to return to the main screen R Dufo L pez HOGA User Manual 69 3 4 Wind Resources The Wind Resources screen may be accessed by clicking on Wind Resources area or selecting Wind in the Data menu JE WIND Data source 2 Monthly Average gt Import hourly data file 8760 values in m s Latitude 9 N S 41 66 Monthly Average Data Longitude
26. losses 13m Losses in Penstock 4 pA Total Efficiency Turbine Generator dO Flow Data ls gi Monthly Average FLOW l s Hourly January February March April hay June FLOW ls July August September October Max flow le Average flow 7 ls November Max generator output power 0 642 ky EDETI December Fi The following data must be introduced Total Head H the difference in elevation between the head water level and the tailwater level expressed in m Pressure losses in the power canal and draft tube in m HOGA uses the data described above to calculate the Available Head H which indicates the difference between the two The value of losses is needed for the penstock water mains penstock and for the turbine in order to obtain the Net Head H Data must be introduced separately for losses in the penstock and on turbine generator performance The latter is used by the application to R Dufo L pez HOGA User Manual 79 provide an estimate for the maximum power available for any given waterfall based on head and flow Data on turbine generator performance will not be used for hourly calculations of energy produced by the turbine since more accurate performance data will be utilized when turbine data is available in another screen Data Sources for the flow expressed in m s may be Monthly Averages or an Imported Hourly Data File In the first case Monthl
27. there are several likely reasons for this The system includes H load but no electrolyzer is accounted for Include this component in the system Either the size or the maximum number of components PV panels batteries and wind turbines allowed is too small In this case the system cannot deliver enough energy to meet the energy demand Increase the power or the maximum number of system components R Dufo L pez HOGA User Manual 186 allowed The search space may be too small for some of the algorithms small population and or few generations so no system can be found that meets the criterion for Maximum Allowed Unmet Energy Allowed Increase pouplation size and number of generations 11 I have a system that includes an electrolyzer and the simulation screen I see that in some hours there is excess energy but this energy is not used in the electrolyzer why The electrolyzer has a minimum operating power defined in its characteristics but its income electrical power must be higher than the minimum energy required to start generating hydrogen B Pn If the excess energy is not sufficient to start generating the hydrogen electrolyzer is not used 1e it does not operate See section 3 15 2 If the hydrogen tank is full in the simulation it has reached the limit set on its size see section 3 15 3 the electrolyzer will not work hydrogen will not be generated as it cannot be stored 12 I have a system including f
28. 28 19 0 o 201 7 95 7 o o 947 449 o o o o o o 23 9 11 3 ESA 20 o o 205 7 93 9 669 9 305 7 96 6 441 o o o o o o 243 12 7 30 21 o o 209 8 92 1 o o 98 5 43 2 o o o o o o 248 10 9 31 22 0 0 214 90 3 o o 100 5 42 4 o o o o o o 25 3 10 7 32 23 o o 218 3 88 6 o o 102 5 41 6 o o o o 0 o 25 8 10 5 33 24 o 0 222 6 86 9 o o 104 5 40 8 o o o o o o 26 3 10 3 34 25 o o 227 1 85 2 318 5 119 5 106 6 40 o o 0 o o o 26 9 10 1 4 _35 TOTAL Costs PV Gen O amp M PV Gen Costs Wind T O amp M Wind T Costs Hydro T O amp M Hydro T Costs AC Gen O amp M AC Gen Costs _36 NPC 8642 4 2715 1928 1 12749 o o 1040 321 3 37 38 TOTAL COST NPC 29441 5 _39 LEVELIZED COST OF ENERGY 0 46 S kwh 40 ALI 42 43 AA Al O Project 1 hoga Solution 0 A AK AL AM AN AO AP AQ AR AS AT AU AV AW AX AY AZ 2 3 4 5 6 7 hk O amp M H2 Tank Costes Fuel of AC Gen Costs ext Fuel for F C Costs Purchasing Eto AC Incomes Selling E to AC gi Incomes Selling H2 Financia Costs TOTAL Costs Incomes 8 NPC cashyear NPC cash year NPC cash year NPC cash year NPC cash year NPC cash year NPC cash year NPC cash year NPC 9 o o o o 0 o o o o o o o o 3176 9 3176 9 3176 9 3176 9 10 o o 0 49 6 477 o o o o o o o o 1809 2 1739 7 2177 7 2093 9 E o o o 546 50 4 o o o o o o o o 1809 2 1672 8 2189 2023 9 12 o o o 60 53 3 o o o o o 0 o o 1809 2 1608 4 2201 1956 6 13 o o 0 66 56 4 o o o o o o o o 1809 2 1546 6 2213 6 1892 2 14 o o 0 72 6 59 7 o o o o o o o o 1809 2 1487 1 2227 183
29. 3100 3100 3100 3100 3100 2500 2500 2500 2500 2500 2500 2500 2500 2500 2050 2050 2050 2050 2050 2050 2050 2050 2050 SOC at the begining of simulation 100 Z of SOCmax Depth Of Discharge Lifetime calculation using model Rainflow cycle counting Equivalent cycles Modified Number of full equivalent cycles 1254 3 1800 1800 1800 1800 1800 1800 1800 1800 1800 _KiBaM Model Cycles to D Failure vs Depth of Discharge a 00 c20 CIO Charge 1 500 1 500 520 452 390 1600 1500 730 635 550 1600 1500 1095 945 816 1600 1500 1780 1550 1340 1600 1500 2588 2250 1940 1600 1500 2995 2595 2240 1600 1500 3730 3230 2800 1600 1500 4125 3580 3090 1600 1500 4490 3895 3360 kg CO2 equiv kWh capacity OPZS Hawker TZS 24 of 3360 Ah Discharge Current A c 0 391 k 0 391 Cmax 4668372 Annual Inflation Rate expected 2 for Batteries Costs Max Variation of Wind Batteries expected e g for an expected 60 reduction on current Batteries cost introduce 60 The limit is reached in 45 4 years 101 The last table column which is also new C charge in A Ah indicates the Maximum Battery Charge Rate or Maximum Battery Charge Coefficient This 1s an additional constraint on the maximum charge current imposed by the KiBaM Model When the Data option is selected for the Kinetic Model the additional graph is no longer displayed The
30. 38 2 0 06 16 Av wind m s FEBRUARY 38 2 0 06 16 Jan 4 44 MARCH 37 2 0 06 16 Feb 4 44 APRIL 36 2 0 06 16 Mar 4 34 May 3 2 0 06 16 Apr 4 24 JUNE 28 2 0 06 16 May 3 64 w 31 2 0 06 16 fu dun 3 44 AUGUST 29 2 0 06 16 Juk 3 74 SEPTEMBER 28 2 0 06 16 Aug 3 54 _ OCTOBER 32 2 0 06 ig El Sep 3 44 _ NOVEMBER 35 2 0 06 16 Oct 3 84 p DECEMBER 37 2 0 06 16 Nov 4 14 Dic 4 34 la Form Factor b 2 Autocorrelation factor 0 82 os E ae 0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 Force O consecutive days with wind lt 3 m sin month January Y Av sp year m s Wind speed m s 3 96 Catcuite_ Ed Visualize montlhy wind speed night speed ampltude Calm it considered Scale by 1 Scaled Average Speed m s OK E o i 3 96 ooo orm factor of the wind speed serial 2 1 lt m s If Visualize monthly wind speed night speed amplitude bottom right is selected the chart to the right shows the wind profile m s versus the time of the day under the cursor Data source 9 Monthly Average Import hourly data file 8760 values in m s Import Latitude 2 N S 41 66 Anemometer Height 10 M Longitude 2 w E 0 86 HE Average Data Monthly Average Speed 9 Night speed Amplitude F Factor and Hour max speed Input Data Month Night speed m s Ampltude m s F Factor Hour max sp JANUARY JANUARY Ay wind m s FEBRUARY J
31. 50 100 150 200 HOGA User Manual 172 K Print Preview ci NE CO cms DEB e ely S S l Chse OTHER RESULTS Hours running AC Generator mean 89 h Std Dev 56 17 Annual cost of fuel of AC Generator mean 44 5 Syr Std Dev 28 A Hydro Turbine Energy mean 0 kWh yr Std Dev O Discharge Energy Battery Bank mean 656 kWh yr Std Dev 22 9 Hours of Batteries charge media 1925 h yr Std Dev 60 6 Hours of Batteries discharge mean 4792 h yr Std Dev 34 1 Max current of Batteries Charge Regulator mean 129 A Std Dev 0 Rectifier max pow er mean 499 4 W Std Dev 5 5 Energy purchased to AC grid mean 0 kWh yr Std Dev 0 Energy sold to AC grid mean 0 kWh yr Std Dev 0 Cost of purchasing Eto AC grid mean 0 yr Std Dev 0 Incomes of selling Eto AC grid mean 0 yr Std Dev 0 H2 tank size mean 0 kg Std Dev 0 Energy of Fuel Cel mean 0 kWh yr Std Dev O Hours running Fuel Cell mean 0 h yr Std Dev O Energy of Hectrolyzer mean 0 kWh yr Std Dev 0 Hours running Bectrolyzer mean O h yr Std Dev O Hydrogen sold for external use mean 0 kg yr Std Dev O Incomes of selling H2 mean 0 yr Std Dev O External fuel purchased to be used at Fuel Cell mean 0 kg yr Std Dev 0 Cost of external fuel purchased to be used at Fuel Cel mean 0 yr Std Dev 0 VARIABLE COST NPC purchase E sell E variable replacement of components O amp M variable fuels regulator rectif H2 t
32. 7 AUGUST SEPTEMBER OCTOBER NOVEMBER gt DECEMBER Form Factor b 2 Autocorrelation factor 0 82 8 10 12 14 16 18 20 22 24 26 28 30 Force O consecutive days with wind lt 3 m sin month January Y Av sp pear m s Wind speed m s 3 32 _ Bow Into time of calm wind Calm is considered Scale by 1 Scaled Average Speed m s Scaled Average Speed m s OK i oh Form factor of the wind speed serial 2 lt 3 m s Night speed Amplitude F Factor and Hour max speed data When the Night Speed Amplitude 31 32 option 1s selected for Data Sources the following information 1s required for the table Night Speed monthly values m s Amplitude m s F Factor and the Hour of Maximum Speed together with the value of the Form Factor b and of the Autocorrelation Factor When pressing Calculate button the software calculates the hourly wind speed for the whole year 8760 values using the methodology shown in 30 it takes some seconds R Dufo L pez HOGA User Manual 73 MK WIND Data source O Monthly Average Import hourly data file 8760 values in m s Import Latitude 9 N S 41 65 I Anemometer Height 10 m Longitude w E 0 86 AERA Metheorological data NASA web 9 Night speed Amplitude F Factor and Hour max speed Input Data Mon Night speed imefana F Factor Howmaxs a LI JANUARY
33. Amplitude F Factor and Hour Max Speed Monthly Average Data Monthly Average Speed f Night Speed Amplitude F Factor and Hour Max Speed Force some consecutive days with calm winds In both cases a number of consecutive days with low wind in a specified month or randomly can be forced default O days Force O consecutive days with wind less than 2 m z in month January R Dufo L pez HOGA User Manual 72 Monthly Average Speed data When Monthly Average Speed option is selected form factor Weibull s probability and autocorrelation factor are required When pressing Calculate button the software calculates the hourly wind speed for the whole year 3760 values using the methodology shown in 30 1t takes some seconds The right chart represents in red the probability of each 0 5 m s range the green curve 1s the Weibull ideal distribution for the form factor that 1s most similar to the distribution generated value shown below F WIND Data source o Monthly Average Import hourly data file 8760 values in m s Latitude 9 N 5 41 66 Anemometer Height 10 Longitude W E 0 86 A ER Metheorological data NASA web gt Night speed Amplitude F Factor and Hour max speed Input Data Month Av wind m s E JANUARY E Ay wind m s FEBRUARY Jan 3 8 MARCH Feb 3 8 Mar 3 7 Apr 3 6 May 3 Jun 2 8 Jul 3 1 Aug 2 9 Sep 2 8 Here Nov 3 5 Dic 3
34. BO 1 546 1300 BL SIMULATE REPORT COSTS 0 5130 0 0487 d 135 E0 1 450 1300 aL SIMULATE REPORT COSTS 0 5138 0 0608 10 135 BO 1 468 1300 al La Ll Columns in red correspond to Costs For optimization applied to components and control strategies two specific columns are shown Total System Cost Total Cost NPC in the currency of the project as well as C sec The latter provides an indication of variable costs R Dufo L pez HOGA User Manual 147 which are dependent on the control strategy operation and maintenance costs fuel costs replacement costs for batteries and generators etc For optimization of the strategy only just one specific column 1s displayed called Var Costs NPC in This includes all system costs except for all initial acquisition expenses for the different system components At the top right of the table additional columns are displayed for annual fuel costs and total costs related to each of the system elements referred to the time of the initial investement NPC as well as data on income from sales of excess electric energy and H these are both negative costs For sales income higher than total costs a negative NPC may result The more negative this value the more profitable the facility Not all the excess energy generated is always available for sale to the AC grid Part of the energy may be on the DC bus and the inverter may not have enough capacity to
35. Irradiaction over the surface of the PY panels 4 64 kwh m2 Rad 2 iad in Ay Daily Irradiation 9 29 kwh From file hourly values in kw h m2 By clicking on the button on the bottom right Draw the different series are plotted R Dufo L pez HOGA User Manual 128 Sensitivity of Load Load x In the 3rd tab we accede to cases of load sensitivity analysis As for the other variables we can add up to 3 cases Each time we add a new case we are reminded that if we chose on the screen of inverters the option in which the inverter is selected to cover the maximum power load it is possible that in some cases the peak consumption is higher than the peak base case and the system could not meet the demand because the inverter is set too small In that case deselect this option on the display of Investors In the case of import from file this should be 8760 4 35040 rows The first 8760 hourly values should be AC load in Wh 8760 following DC load values in Wh the following 8760 data are the hydrogen load in kg and 8760 last data is the volume of water consumption in m3 s for each hour the height of pumping losses pump data etc are the same as in the base case By clicking on the button on the bottom right Draw the different series are plotted Sensitivity of interest rate I and inflation rate 9 x In the 4th tab we accede to cases of sensitivity analysis of the economic parameters to calculate the NPV int
36. OBJECTIVE Display Mon dom only o Cost CO Emis Cost Unmet load 4 avobe min cost 300 Triple Mas no Non Dom 50 Another Storage Pareto every 5 gen Export Paretos If on the main screen Optimization tab you click on the option called Display Non dom only the results table and results chart will be the Pareto representation of non dominated solutions For example if the multi objective optimization 1s Cost CO2 Emissions these are solutions with the lowest cost and lowest emission levels When this check box is not selected all solutions evaluated by the principal algorithm will be displayed The user must choose between Multi Objective Total Cost NPC versus CO Emissions or Total Cost NPC versus Unmet Energy or triple cost emissions unmet or another see section 3 1 4 Additional data must be introduced on the maximum number of non dominated solutions as well as on the maximim percentage of NPC to be transferred amongst them with respect to the minimum NPC for all of them Click on Storage Pareto every to input the number of generations between successive archiving of Pareto charts to disk Once calculations are completed click on Export Paretos to save Paretos stored in memory to an ASCII file In this case the calculation time set in main screen General data tab see section 3 1 3 is not enough to evaluate all combinations of the components so the genetic algorithms will be used
37. ONES usaba 198 R Dufo L pez HOGA User Manual 8 1 INTRODUCTION AND OVERVIEW HOGA improved Hybrid Optimization by Genetic Algorithms 1 11 is a software developed in C for the simulation and optimization of Hybrid Renewable Systems for generation of electrical energy DC and or AC and or Hydrogen The software can simulate and optimize systems of any size from systems with consumption of the order of few Wh daily until many MWh consumption and even GWh daily You can also simulate and optimize grid connected systems with or without load and different cases of Net Mettering can be defined Optimization 1s achieved by minimizing total system costs throughout the whole of its useful lifespan when those costs are referred to or updated for the initial investment Net Present Cost NPC Optimization is therefore financial mono objective However the programme allows for multi objective optimization where additional variables may also be minimized equivalent CO emissions or unmet load energy not served as selected by the user Since all of these variables cost emissions or unmet load are mutually counterproductive in many cases more than one solution is offered by the programme when multi objective optimization is sought Some of these solutions show better performances when applied to emissions or unmet load whereas other solutions are best suited for costs In version 2 0 PRO we can also optimize multiobje
38. Renew Frac 97 6 Excess E 550 kWh yr Batteries lifetime 18 67 yr AC gen fuel 33 04 litre yr DATA Irradiation 4 65 kWh m2 day Load 7 94 kWh day RESULTS Total Cost NPC 35764 Lev cost of E 0 49 kWh Unmet load 0 0 Page 2 of 3 When you close the probability report a screen appears asking 1f you want to save the results of the analysis of probability as Microsoft Excel file same Excel file as the one which is saved when clicking the button Save Prob Data in the simulation window shown in 4 6 2 4 4 6 System Costs Clicking on the COSTS cell of the result table corresponding to the row of the solution you want to study a report shows the cash flows of the different components of the system throughout the years of the life of the system Costs are considered positive values and incomes are considered as negative values You can see how some components have a negative cash flow at the end of the lifetime of the system income is obtained by the sale of the component at the end of the lifetime of the system with value proportional to the remaining life of the component This report can be printed in a printer or in PDF format in the same way as explained in the previous section R Dufo L pez HOGA User Manual 173 0858 gt SG H6 do ELO a Project 1 hoga Solution 0 Distribution of nulo NPC RED acquis ition costs replacement cats and incomes for final sale BLU
39. SIMULATE REPORT DC Voltage 24 Y AC Voltage 230 Y Energy Storage 4 days range Max bat parallel gt Cn min Max PY pan parallel gt P min Max wind t parallel gt P min Upon completion all the sensitivity analysis it is shown in the table of results the results of the R Dufo L pez HOGA User Manual 178 analysis No 1 the basis of all cases next figure HE Project EAL hoga Project Data Calculate DataBase Report Help wf LOAD Mono Obejctive optimization Sensitivity analysis 1 Total No of cases evaluated 1356 Time 40 RESOURCES i i Y SOLAR WIND HYDRO COMPONENTS Y PV PANELS WIND TURB HYDRO TURB Y BATTERIES GENERATIONS Y INVERTERS Analysis 1 Sketch V Chart Windl 3 32m s y Rad 1 4 65kwh m2 Loadi 3 63kWh dia v I 9 1 4 2 Inf F 1 Base y Prt xl xixixi 7 AC GENERATOR _ H2 F C Elyzen al TR m l TE TE 0 5 SIMULATE REPORT TOTAL COST NPC E OTHERS AUX 7 16693 173 INF 104 976 0 5 SIMULATE REPORT 2 8 16483 179 0 0 INF EA 96 8 0 5 SIMULATE REPORT g 16483 179 0 0 INF EA 96 8 0 5 SIMULATE REPORT DC Voltage 24 Y AC Vek y 10 16483 179 0 0 INF EA 96 8 0 5 SIMULATE REPORT co 90 11 16483 179 0 0 INF 71 968 0 5 SIMULATE REPORT 12 16483 179 0 0 INF 7 1 96 8 0 5 SIMULATE REPORT a PRE SIZING 13 16483 179 0 0 I
40. account in the probability anaylsis where number of probability variables is the number of variables included in the probability analysis this is a number between 1 and 4 the variables can be load solar irradiation wind speed and water flow For example if the number of series for the probability analysis is set in N 500 and the variables to analyze are load and irradiation 2 variables 5 25 additional series the total number of series analyzed when clicking SIMULATE button are 500 25 Probability series 136 of 500 25 Cancel You can cancel by clicking Cancel button If 1t is not cancelled the results of the row are updated with the average of the 500 series In the simulation screen the case corresponding to the options chosen in the probability analysis screen is shown For example if we have chosen for the Load the Average Std Dev data and for the Irradiation the Average Std Dev data R Dufo L pez HOGA User Manual 161 next figure the simulation screen 1s shown below In the simulation show the case obtained with the following data Load Iradiation Average Std Dev Average Std Dev Ye sanos A VETT MEA Hourly simulation Hourly values separately Monthly and annual Average Power Monthly values Annual values Hydrogen detailed AC Generator detailed Water load Prob Irrad Av SD Load Av SD Simulation of 1 year All the years are the same
41. an error message will be displayed since Paradox tables cannot handle paths longer than the value mentioned above The main application window is now shown with an additional choice for the selection of default or non default values as shown by the image below Default Input data The default values correspond to irradiation levels for Zaragoza Spain a pre determined level of energy consumption and a system including PV panels batteries and an AC diesel generator These values may be changed if the user clicks on No above Anyway if you click Yes this values can be changed later R Dufo L pez HOGA User Manual 28 Open a Project If the option Open an Existing Project is selected a screen opens to choose a path for the project file to be opened with extension hoga A folder with the same name as the file must be present in the same directory This folder contains the tables to be used by the programme when a new project is stored HOGA creates both the file and the folder The figure below shows an existing project called PV diesel where both a file and a folder under the name PV diesel are clearly visible Open Buscar en Proyectos ve e E EF Ev Estrat Multiob oo E GeneracionH2 Documentos Pueblo recientes Ej pv diesel E Estrat Multiob 4 GeneracionHe Escritorio Mis documentos 8 a Mi PC Mis sitios dered Nombre pv diesel ed
42. and the DC voltage of the system is 24 V there will be 2 PV panels in serial but the maximum number of PV panels in parallel should not be much higher than 3200 135 2 11 8 So the maximum number of PV panels in parallel to be selected in the main screen should be 12 ora little more for example 13 IHOGA knows the load and the wind speed so it calculates approximately the peak power of R Dufo L pez HOGA User Manual 107 the Wind Turbines group which can meet the whole load by themselves This peak power power in the example 1 9 kW should be the maximum power of the wind turbines group For example we could select in the Wind Turbines screen a wind turbine of about 0 5 kW another one of about 1 kW and another one of about 2 kW and maybe another one of about 2 5 kW but not much higher The maximum number in parallel should be 1 or perhaps 2 The maximum recommended power for the AC Generator is the power needed to meet the whole load by the AC generator taking into account 90 efficiency for the rectifier The maximum recommended power for the Inverter is the power needed to meet the whole AC load by the inverter The maximum recommended power for the Electrolyzer is the maximum of the following data Photovoltaic generator maximum recommended power Wind turbines group maximum recommended power and the power needed by the Electrolyzer to produce the maximum H2 load expected The maximum recommended power
43. asimum Unmet Load allowed 1 annual Unmet load can be covered by AC grid if it exists and itis allowed in LOAD AC GRID window More Constraints OPTIMIZATION PARAMETERS SELECTED Br o IHOGA USER Maximum execution time O h 15 min Display Parameters Minimum time for the genetic algorithms Simulation start Hour O day 1 month 1 Compare with Worth Month Method P bat 4 The default hybrid system 1s PV Diesel with batteries To add or remove components select them on COMPONENTS R Dufo L pez COMPONENTS J PY panels Wind turbines Hydro turbine Y Batteries AC Generator Inverter FE H2 F C Elyz SS HOGA User Manual 31 After adding or removing a component the layout shown at the bottom will be updated and the buttons on the leftmost area of the screen will be enabled or disabled MINIMUM AND MAXIMUM NUMBER OF COMPONENTS IN PARALLEL Minimum and maximum number allowed for batteries PV panels and wind turbines in parallel must be provided MIN AND M s No COMPONENTS IN PARALLEL Batteries in parallel Min 7 Max 1 PY panels in parallel Mir O Max 12 Note The parallel connection of more than two batteries is often problematic so the maximum number allowed in parallel battery should be I or exceptionally 2 unless you have multiple controllers for different battery banks CONSTRAINTS In CONSTRAINTS user must determine maximum Percent
44. cycling cost for an energy accumulator batteries or electrolyzers is the total cost of storing energy within the component for later supply to the system as needed This cost includes operation and maintenance proportional tear and wear and replacement costs Cycling costs are approximately proportional to the power in the case of batteries and approximately constant for electrolyzers as shown in the figure below The point of intersection of both straight lines Prim charge Will be then used as a reference to determine surplus energy in the system at any given time If the surplus energy is below this point it R Dufo L pez HOGA User Manual 199 will be cheaper to use this to charge the batteries whereas if the surplus energy is above it it will be more convenient to use it for generation of Ho in the electrolyzer Cost of cycling energy electrolyzer fuel cell Piti P kW Cost of cycling energy The Charge Strategy will thus be e For Penarge lt Plim_charge the batteries will be charged to their maximum and any surplus energy will be used to generate H in the electrolyzer e For Peharge gt Pim charge as much hydrogen as possible will be generated in the electrolyzer and any surplus energy will be used to charge the batteries In case the renewable sources alone do not have the capacity to generate all of the energy required for consumption the rest of the required energy which we will
45. displ Cdeg limit 0 842 Batteries lifespam 87552 hours 9 31 years R Dufo L pez HOGA User Manual 166 It is shown the maximum capacity in brown with the end of lifespan when it reaches 80 the loss of capacity for degradation green curve and the loss of capacity due to corrosion blue curve It is noted that in this case the capacity loss due to corrosion is far greater than by degradation This 1s only taken into account by the Schiffer model and not by another model of batteries making 1t much more accurate than the other models I battery current A in each individual battery is displayed in the figure 10 days displayed dl oo o Current in each individual battery first hour discharge after full charge La cassado 1 2 3 4 5 6 7 8 g 10 January year 1 Current in each individual battery first hour discharge after full charge BACK Daye displ It is shown the current for each individual battery green curve and the discharge current for the first hour after full charge blue curve very important parameter for calculating the current factor and quantify the effect of sulfation and its degradation effect R Dufo L pez HOGA User Manual 167 Factors factors used in the Schiffer model in figure display 100 days FSOC FI Facid Fplus Fminus tn DDE a SD So Factors of SOC of current and acid BACK Days displ Cycles full cycles performed by the batteries in
46. e each combination of cases of the sensitivity analysis For example if we set wind 3 cases 2 irradiation cases 3 load cases 2 cases of interest and inflation 2 cases of inflation of the fuel of the AC generator and 3 cases of prices of components the number of sensitivity analysis ie the number of optimizations to perform 1HOGA 1s 3x2x3x2x2x3 216 analysis For another example where the number of sensitivity analysis is 6 the figure below shows a screenshot during the course of the calculation At that moment goes sensitivity analysis number 2 corresponding to Wind 1 Rad 1 Load 2 1 g 1 Inf F 1 Pr 1 in this analysis at this time is the generation 5 of the genetic algorithm It is shown the time elapsed and the number of sensitivity analysis Project Data Calculate DataBase Report Help gt Mono Obejctive optimization Sensitivity analysis 2 Total No of cases evaluated 302 Time 13 RESOURCES COMPONENTS N N Q o o CO2 EMISSIONS kg year TOTAL COST NPC 3 GENERATIONS Sensitity Analysis 2 E Sketch 4 Chart Windi 3 32m s Rad 1 4 65kWh m2 Load2 2 18kwh day I g l 42 22 Inf F 1 Base Pr 1 x1 x1 x1 x1 Gen Total Cost NPCJ E Emission kaCO2 91 Unmet kwh yr Unmet D range Cn ahvicci Ren z Cost EfE kwh Simulate Report 87 0 0 100 0 65 SIMULATE REPORT 87 100 0 65 SIMULATE REPORT 87 100 0 65 SIMULATE REPORT 98 5 0 63 SIMULATE REPORT 385 TEJ
47. for the Fuel Cell is the maximum power needed to meet the whole load by the fuel cell taking into account 80 efficiency for the inverter In these calculations we used the following input data efficiency of the rectifier 90 inverter efficiency 80 electrolyzer efficiency 70 of H2 HHV electrolyzer efficiency 40 of H2 LHV battery minimum SOC 40 In the calculations of the recommended maximum power for the PV array and wind turbine group it is considered an oversize factor of 1 2 taking into account the storage losses note that this factor is too low if the energy storage is in hydrogen Also it is shown the capacity of the batteries bank and the size of the H2 tank for the number of days of energy storage fixed under the button PRES SIZING by default 4 days taking into account the maximum daily load of the year 1HOGA calculates the maximum number of batteries in parallel for the type of battery of HIGHEST capacity of the batteries fixed on the screen of the batteries so that with this number of batteries in parallel the number of days range is covered it calculates the nearest higher integer number It should be noted that the battery with higher capacity may cover the days of autonomy if the parallel number is the maximum However the rest of batteries may not cover the days range If you ticked Max Bat Parallel gt Cn min the maximum number of batteries in parallel is calculated based on the type of battery
48. lt 100 SOCmin since batteries will not operate for higher Depth R Dufo L pez HOGA User Manual 97 values Eo ycled_ kWh Cn Ah Vn V Depth 9 100 Cycles 1000 This value is displayed in green The number of equivalent cycles is calculated as Nag cseles X Ecyctea_i kWh 1000 Cn Ah Vn V This value is displayed under the chart An estimation must be carried out of fixed Operation and Maintenance Costs yr for the battery set to be used by the hybrid system the exact type and number of batteries is not known before the project is started These costs must include the operator and the fixed material regardless of the final number of batteries in operation We must indicate also the average temperature of the batteries during each month of the year as this will be taken into account in Copetti and in Schiffer models and in any model to calculate the floating lifetime taking into account Arrhenius law Temp J 18 F18 M20 420 M22 J 22 Bat PCI J22 422 520 020 N18 ois 4 Mean FL Except Schiffer model consider T mean gt T flotat lite By default the checkbox Except Schiffer model consider Tmean gt Tfloat life is checked This means that except for the Schiffer aging model in any other model if the mean of the batteries temperature is lower than the temperature at which the manufacturer indicates the floating lifetime then IHOGA will consider that the mean of the te
49. of wind the basis Wind 1 Wind 2 and Wind 3 1HOGA considers three different system 3 sensitivity analysis If there are more variables considered for the sensitivity analysis other tabs then the number of optimizations that will make HOGA considers all possible combinations For example if we have 3 cases of wind for the sensitivity analysis and 2 cases of irradiation introduced in the 2nd tab the number of optimizations that will run 1HOGA are 3x2 6 optimizations Adding more variables in the analysis of sensitivity the number of optimizations will be multiplied by the number of cases of each variable Sensitivity of irradiation over the surface of the PV panels Rad x In the 2nd tab we accede to cases of sensitivity analysis of irradiation As in the case of wind using the Add button you can add up to 5 cases and you can delete the last entered using the button Remove last one Each case is called Rad x Rad 1 being the base case case 2 is Rad 2 etc Each case can be defined by a scale factor multiplying the base case or importing in 8760 kWh m2 hourly values from file Irradiation imported must be on the tilted surface of the PV panels not on a horizontal surface If a sensitivity analysis of irradiation is done the optimization of the PV panels during the optimization of the system is not possible SENSITIVITY ANALYSIS OF THE SOLAR IRRADIATION OVER THE SURFACE OF THE PV PANELS Rad 1 Case base Average Daily
50. only ask for the change of the default currency the first time we create a project f you do not change the currency at this time Euro will remain as default currency To change the default currency later I Go to the installation directory and delete the file moneda hog 2 Copy the original tables that after installing the software we will have copied and saved in another directory called Original tables see end page 17 in the folder Tablas in the installation directory deleting previous files 3 Create a new project and change currency If we want to keep as the default currency Euro we must click the Cancel button If we want to use as default currency a currency different from Euro press OK By clicking OK the next screen appears where you can set the new currency You can choose from Euro U S Dollar and another currency which must be defined R Dufo L pez HOGA User Manual 26 E CHANGE DEFAULT CURRENCY TES EI xX DEFAULT CURRENCY TO BE USED BY HOGA US Dollar Equivalence between currencies 1 amp 1 3 Cancel If we choose another currency a text box appears right where we must write 1ts short name Below we must indicate the equivalence between the Euro and the new currency DEFAULT CURRENCY TO BE USED E Another define BsF US Dollar a encles 1 If we clikc the Cancel button 1HOGA will keep the Euro currency and def
51. p LH T E e a Po T 1 LH The output power of the wind turbine at the height above sea level H would be the output power at sea level given by the power curve multiplied by the ratio p po Effect of Ambient temperature If we want to consider the effect of ambient temperature on air density the ckeckbox Consider the effect of temperature must be checked A new box appears where we must enter temperature data We can choose Data monthly average temperature Tamb or better if you have a file with 8760 hourly data on ambient temperature import These data are not the same as used in the screen of the photovoltaic panels as in the wind turbines we must provide the temperature at hub height while for the photovoltaic panels we should indicate the temperature at the height that are placed normally much lower Ambient Temperature at hub height FC Monthly average F5 MI All MIR SA J 4 42 519 014 N3 35 J 4 File with 6760 hourly values E Draw Taking into account ambient temperature 0 0 1s calculated as follows P LR gt lo Po I ie As explained in the screen of the PV panels in the bottom of the screen we must enter the expected inflation rate of the wind turbines and the limit to take them into account if the useful life of installation or study period exceeds the wind turbines lifespan Cases of very high load R Dufo L pez HOGA User Manual 93 As mentioned above
52. replacing Poritical gen With Peritica FC ANd SOCs gen With SOC stp rc However HTANK st would not be applicable if the R Dufo L pez HOGA User Manual 202 fuel cell uses up H2 from the H tank previously produced by the electrolyzer When the power required by the loads from the AC generator is less than P oritical gen the operating power for the AC generator will equal the minimum power to supply the power still not delivered to the loads plus the power required to bring the batteries up to SOC ip sen and the power needed by the electrolyzer to produce H gt until HxTANKgp is reached with no energy lost In some cases the minimum power from the AC generator will be over Pcritical gen so energy will be lost The same is true for the fuel cell R Dufo Lopez
53. the chart to include a fuel cell and or an electrolyzer and an H2 tank When a fuel cell is included and H is produced in the electrolyzer it will obviously be necessary to include an electrolyzer and an H tank so the check box will be disabled for R Dufo L pez HOGA User Manual 119 these Tags will disappear for any elements excluded Data for the calculation of life cycle emissions must be set equivalent CO2 emissions in the manufacturing of the fuel cell and the electroyzer kg CO2 per kW of rated power Equivalent CO emissions manufacturing fuel cells and electrolyzers 330 kg CO equiv 4 rated power The fuel cell and the electrolyzer can be connected to AC bus in this case you must select the checkbox Fuel Cell and Electrolyzer are connected to AC bus by means of their inverter and rectiher respectively Inverter and rectifier data Then you must define the efficiency of the rectifier of the electrolyzer and the efficiency of the inverter of the fuel cell by clicking the button Inverter and rectifier data ELECTROLY ER Efficiency of the rectifier of the electrolyzer 30 p FUEL CELL Efficiency of the inwerter of the Fuel Cell 2 ve Output power 2 of rated Das on a da a 10 ele 30 OR 3 15 1 Fuel Cell Graph shows the efficiency of the fuel cell which is selected in the table Below the graph it is shown the nominal fuel cell power kW and the minimum required amount of
54. the figure displayed 10 years It is shown the cycles without weight factors curve green and the weight cycles blue curve Number of cycles January year 1 December year 10 Cycles without weight factors Cycles with weight factors b 3643 BACK Days displ R Dufo L pez HOGA User Manual 168 Bad ch Number of bad recharges not achieved 99 of SOC in the figure displayed 10 years Number of bad recharges not achieved 99 36 34 32 30 28 26 24 Za 20 January year 1 December year 10 3649 Days displ Resist Resistances charge discharge and and corrosion layer in the figure 10 years of viewing Resistence of charge discharge and corrosion layer January year 1 December year 10 Resistence of charge ro_C Resistence of discharge ro_D Resistence of corrosion layer TO co j 3649 Days displ Corrosion resistence 2 567 ohm 4h R Dufo L pez HOGA User Manual 169 The simulation results shown in the other tabs of the simulation window Separate hour values etc refer to last year of the simulation 4 4 4 Modifying Values in the Results Table Some values of control variables in the results table may be changed by the user as mentioned above This modifies the results but may be useful to determine the influence of different parameters on the hourly system simulation and on the different results obtained for energy and financial co
55. to Remove cells a a p a ca To edit cells use the button shown below or doubleclick on the cell When the user edits a cell the components shown 1n the image below are enabled ZE Clicking on the first symbol validates all changes to the cell whereas clicking on the second one cancels all changes When nothing is selected any changes to the cell will be automatically validated R Dufo L pez HOGA User Manual 84 Add PV panels from database Panels can be added from the database individually or whole family of panels Add FY panel Zero Add PY panels family SiM12 Atersa The added components from the databases can not be modified To modify them it must be done in the database However if you add a component of the database and you rename it then you may change the rest of its features Fixed Operation and Maintenance cost O amp M Additional data must be introduced for fixed operating and maintenance costs yr These costs are independent of the number and the type of the PV panels used for the photovoltaic generator Fixed operator overheads and costs for maintenance material are included regardless of the size of the generator Fixed Operation 8 Maintenance Cost 40 fear The total cost for operation and maintenance will then equal the aggregation of the fixed costs plus the individual cost of PV panels multiplied by the number of panels in the photovoltaic generator
56. transfer all of this energy to the AC bus For optimization of both components and strategy several columns are displayed in black with data on the number and the features of all physical system components For optimization of strategy only data is displayed on the components selected as a function of the strategy H2 tank battery charge regulator and rectifier A number of columns appear in bold with data on the control variables These values may be changed manually so that IHOGA may recalculate the combination of system components and control strategy for the table row where the values are changed thus modifying final results Peri gen W F 3135 LOAD FOLLOWINE IHF 309 IHF IHF 570 O O O 2492 LOAD FOLLOWINE INF 309 INF INF 50 0 O o 4508 LOAD FOLLOWINE INF 309 INF INF 570 O O a 7 3000 LOAD FOLLOWINE INF 309 INF INF 570 O O O 1794 LOAD FOLLOWINE INF 309 INF INF 5 0 O O 1960 LOAD FOLLOWINE INF 309 INF INF 5 0 0 O O 2878 LOAD FOLLOWINE INF 309 INF INF 570 O O O 4315 LOAD FOLLOWINE INF 309 INF INF 5 0 0 O O 2380 LOAD FOLLOWINE INF 309 INF INF 570 O O Annual Energy columns are displayed in blue kWh yr and broken out into Overall Load Total Energy Consumption Energy Generated by Renewable Resources Energy Generated by Solar Panels Energy Generated by Wind Turbines Energy Generated by the Hydraulic R Dufo L pez HOGA User Manual 148 Turbine Excess Energy not used Energy Sold To and Purchased F
57. wind speeds may be higher at night or in the morning Amplitude m s This is the difference between the night speed and the maximum hourly speed Hour of Maximum Speed The time of the day when the maximum speed is recorded F Factor This is inversely proportional to the number of sun hours and directly proportional to the average speed This parameter provides an indication of the dependency of wind speeds upon the time of the day at which speeds are measured Higher F values correspond to narrower variations centered around the time at which maximum speed occurs thus with a larger degree of dependency on the time of the day Once the monthly values are introduced on the table and the Anemometer Height has been specified the user may click on Calculate so that system calculation may be applied for hourly wind speeds throughout the year A wind related text file viento txt is automatically generated by 1HOGA when calculating hourly wind speed values Click on Export to save calculated data to that file or select an alternative file name R Dufo L pez HOGA User Manual 76 0 91 234567839 1011 12 143 14 15 16 17 18 19 20 21 22 3 Sinthetic calculation of wind speed hourly data We have developed a new method which obtains wind speed series similar to the real ones 30 Export button Click on Export button to export hourly wind speed Draw button Click
58. with LOWEST capacity Thus all the batteries would R Dufo L pez HOGA User Manual 108 be capable of covering the days range if the number was the maximum in parallel It also calculates the maximum number of panels and wind turbines The number of panels in parallel is obtained as the higher integer of the division between photovoltaic maximum power recommended by the DC voltage of the system and by power of the type of panel of HIGHEST power If you ticked Max PV pan Parallel gt P min the maximum number of PV panels in parallel is calculated based on the type of LOWEST power panel Similar calculation is made for the maximum number of wind turbines in parallel By clicking OK iHOGA reports the maximum number of allowed components are updated on the main screen IHOGA S Max numbers of components in parallel allowed hawe been updated Max no of batteries of type of HIGHEST capacity in parallel 1 Max no of PV panels of type of HIGHEST power in parallel 12 Max no of Wind Turbines of type of HIGHEST power in parallel 1 The updated values are shown in red MIN AND M s No COMPONENTS IN PARALLEL Bathenes in parallel Min Max 1 PY panels in parallel Mir O Max 12 Wind T im parallel Min 1 Max 1 R Dufo L pez HOGA User Manual 109 3 12 Auxiliary Equipment for Charging the Batteries The Auxiliary Equipment for Charging the Batteries screen may be accessed by clicking on CHARGE B
59. 0 AC Generator 1900 VA Batteries bank of 11232 Wh Batt charge reg 54 A Inverter 500 VA Rectif 501 W SENSIT ANALY SIS 3 Rad 2 5 58kWh m2 Load1 3 63kWh dia I g 1 4 2 Inf F 1 Base Pr 1 x1 x1 x1 x1 NPC 14521 CO2 Emissions 105 kg yr Unmet load 0 kWh yr 0 Days range INF Renew able fraction 100 of demand Levelized cost of energy 0 44 kWh Cormmanante Ds annnratar 2420 Min ANY AC Cannaratar ANNN MA Ratsrine hank of ARN Ah Rat charanran ARA Invartar FON VA Dart N 0 Pagel of 1 Clicking on the button Save Excel on the screen of the summary of the sensitivity analysis a detailed table w the results of the sensitivity analysis the summary best combination found for each sensitivity analysis can be you saved in format xls or format txt If we keep it as Xls when opening the file with Microsoft Excel it shows a message then you must answer Yes and it opens perfectly In Microsoft Excel you should save the Excel file as xlsx format in Excel use Save As and choose file format xlsx then the next time you open the xlsx file Excel will not ask you any question R Dufo L pez HOGA User Manual 182 5 REQUENTLY ASKED QUESTIONS 1 Can 1HOGA only be used to simulate and optimize small low consumption systems No you can simulate and optimize systems of any size from systems with consumption of a few Wh per day until systems of consumption of MWh or GWh daily In pr
60. 0 4 pi o o o 79 9 63 1 o o o o o o o o 1809 2 1429 9 2241 1 1771 2 16 o o o 87 9 66 8 o o o o o o o o 1809 2 13749 2256 2 17145 17 o o o 96 6 70 6 o o o o o o o o 1809 2 1322 2272 1 1660 2 18 o o 0 106 3 74 7 o o o o o o o o 1809 2 1271 2 2289 1 1608 3 19 o o 0 116 9 79 o o o o o o o o 1809 2 1222 3 4863 9 3285 9 20 o o o 128 6 83 6 o o o o o o o o o o 517 3 336 2E o o o 141 5 88 4 0 o o o o o o o o o 537 9 336 22 o o 0 155 6 93 5 o o o o o 0 o o o o 560 336 3 23 o o 0 171 2 98 9 0 o o o o o o o o o 583 6 337 24 o o o 188 3 1046 o o o o o o o o o o 609 338 2 25 o o 0 207 2 110 6 0 o o o o o o o o o 636 3 339 7 26 o o 0 227 9 117 o o o o o 0 o o o o 665 6 341 7 27 o o 0 250 7 123 7 o o o o o o o o o o 697 1 3441 28 o o o 275 7 130 9 o o o o o o o o o o 2622 7 12449 o o o 303 3 138 4 0 o o o o o o o o o 3651 3 1666 4 30 o o 0 333 6 146 4 o o o o o o o o o o 807 4 354 3 31 o o 0 367 154 9 0 o o o o o o o o o 850 2 358 8 32 o o o 403 7 163 8 o o o o o o o o o o 896 6 363 8 33 o o o 4441 173 2 o o o o o o o o o o 946 8 369 4 34 o o 0 488 5 183 2 o o o o o o o o o o 1703 5 639 35 1k O amp M H2 Tank Costes Fuel of AC Gen Costs ext Fuel for F C Costs Purchasing Eto AC Incomes Selling E to AC gi Incomes Selling H2 Financial Costs TOTAL Costs Incomes 36 o o 2532 9 o o o o 17851 5 294415 37 38 39 40 41 42 43 Mh 4 I IZI E 79 In Microsoft Excel you should save the Excel file as xlsx format in Excel us
61. 1 149 o 10 8 5 6 9 5 o o o 8775 2 168 8 101 6 o o o 67 1 208 9 143 o o o o o o o 8776 3 186 9 1125 0 o o 743 301 1 12 5 o 0 o 0 o o o 8777 180 8 108 9 o o o 719 302 7 14 0 0 o o o o o 8778 5 224 112 5 o o o ELLS 299 7 6 9 o o o o o o o 8779 e 252 8 108 9 o o o 1439 296 5 45 0 o o o o o 0 8780 7 298 4 1125 0 o o 185 8 322 6 6 o o o 0 o o 0 8781 8 298 4 1125 o o o 185 8 343 8 5 9 o o o 0 o o o 8782 9 216 8 108 9 o o o 107 9 358 6 o 0 o o o o 0 8783 10 186 9 1125 0 o o 743 340 8 9 o 0 o o o o 0 8784 11 180 8 108 9 0 o o 719 234 8 9 6 o 0 o o o o 0 8785 12 186 9 1125 0 o o 743 161 2 15 5 o 31 3 16 2 27 4 o o o 8786 YEAR Load AC_load DC_load H2_load H2 load kg Water Pv Wind Hydro Gener Fuel Gen Cost Fuel FC Fuel FC Fuel ext FC C Fuel e 8787 TOTAL 2568 3 1324 9 o o o 1243 4 35515 119 o 42 2 21 8 36 9 o o 0 8788 8789 8790 8791 Mettering energy purchased and sold to AC grid No Net Mettering 8792 8793 RESULTS FOR HOURLY PERIODS OF PURCHASING AND SELLING ENERGY TO THE AC GRID 8794 8795 HOURLY PERIOD P1 8796 MONTH Unmet Load Excess E Sell Eto AC grid Purchase E from AC grid Incomes selling E Cost purchasing E 8797 1 o 1 26 o o o o 8798 2 o 24 84 o o o o 8799 3 o 100 5 o o o o 8800 4 0 112 05 o o o o 8801 5 o 58 39 o o o o 8802 5 o 24 69 o o o o 8803 7 o 5 55 o o o o 8804 8 o 26 24 o o o o 8805 9 o 122 33 o o o o 8806 10 0 136 85 o o o o 8807 11 o 37 97 o o 0 o 8808 12 o o o o o o 8809 YEAR Unmet Load Excess E
62. 23 2 o o 73 2 57 9 o 0 0 o o o 152 12 3828 7 o o 159 120 8 o o 74 7 56 7 o o o o o o 155 11 8 3829 8 o o 162 2 118 5 o 0 76 2 55 6 o o 0 o o o 15 8 11 5 3830 9 0 o 165 4 116 2 o o 77 7 546 o o o o o o 16 1 11 3 3831 10 0 o 168 7 114 740 7 500 4 79 2 53 5 o o o o o o 16 4 LLI 63 3832 11 o o 172 1 111 8 o o 80 8 52 5 o o o o o o 16 7 10 9 3833 12 o o 175 6 109 7 o o 82 4 SLs o 0 o o o o 17 1 10 7 3834 13 o o 179 1 107 5 o 0 84 1 50 5 o o 0 o o o 17 4 10 5 3835 14 0 o 182 6 105 5 o o 85 8 49 5 o o 0 0 o o 17 8 10 3 3836 15 0 o 186 3 103 4 o o 87 5 48 6 o o o 0 o o 18 1 10 1 3837 16 0 o 190 101 5 o o 89 2 47 6 o o 0 o o o 18 5 9 9 3838 17 o o 193 8 99 5 o o 91 46 7 o o 0 0 o o 18 9 9 7 3839 18 o o 197 7 97 6 o o 92 8 45 8 o o o 0 o o 19 2 9 5 3840 19 0 0 201 7 95 7 o o 947 449 o o 0 o o o 19 6 9 3 3841 20 o o 205 7 93 9 669 9 305 7 96 6 441 o o o o o o 20 9 1 77 3842 21 o o 209 8 92 1 o o 98 5 43 2 o o o o o o 20 4 9 3843 22 0 o 214 90 3 o o 100 5 42 4 o o o 0 o o 20 8 8 8 3844 23 o o 218 3 88 6 o o 102 5 41 6 o o o 0 o o 21 2 8 6 3845 24 0 o 222 6 86 9 o 0 104 5 40 8 o o 0 o o o 217 8 5 3846 25 0 o 2271 85 2 318 5 119 5 106 6 40 o o o o o o 22 1 8 3 42 3847 TOTAL Costs PV Gen O amp M PV Gen Costs Wind T O amp M Wind T Costs Hydro T O amp M Hydro T Costs AC Gen O amp M AC Gen Costs In 3848 NPC 8642 4 2715 1928 1 12749 o o 1040 264 2 3849 3850 TOTAL COST NPC 28915 1 3851 3852 3853 CYCLES OF CHARGE DISCHARGE OF BATT
63. 27 01 ene 17 00 223 96 176 0 0 o 47 96 56 87 0 66 0 0 0 0 0 28 01 ene 18 00 289 96 242 0 0 0 47 96 0 0 0 0 0 0 0 PA 01 ene 19 00 383 9 264 0 0 0 119 9 0 18 37 0 0 0 0 0 30 01 ene 20 00 453 86 286 0 0 0 167 86 0 11 67 0 0 0 0 0 31 01 ene 21 00 431 86 264 0 0 0 167 86 0 14 22 0 0 0 0 0 32 01 ene 22 00 337 92 242 0 0 0 95 92 0 135 0 0 0 0 0 33 01 ene 23 00 135 96 88 0 0 0 47 96 0 2 96 0 0 0 0 0 34 02 ene 0 00 69 96 22 0 0 0 47 96 0 0 93 0 0 0 0 0 35 02 ene 1 00 69 96 22 0 0 0 47 96 0 0 0 0 0 0 0 36 02 ene 2 00 69 96 22 0 0 0 47 96 0 0 9 0 0 0 0 0 37 02 ene 3 00 69 96 22 0 0 0 47 96 0 0 0 0 0 0 0 38 02 ene 4 00 69 96 22 0 0 0 47 96 0 0 0 0 0 0 0 Mot bol 2 ART Te After the 8760 rows one for each hour it displays the monthly and annual total values of different energies and the total values of purchase and sale energy to the AC grid energy costs and incomes Total values also appear for different time periods of the sale to AC R Dufo L pez HOGA User Manual 159 WIND os ec o eo dt e AM dd a o xk ojo omo ono o re je jon 8772 TOTAL MONTHLY VALUES AND TOTAL ANUAL All energy values are in kWh Fuel consumption of AC Gen is expressed in litre H2 load H2 used by fuel cell external or from H2 tank and H2 generation by electrolyzer are in kg 8773 MONTH Load AC_load DC_load H2_load H2_load_kg Water_l PV Wind Hydro Gener Fuel Gen Cost Fuel F C Fuel FC Fuel ext_FC C Fuel e 8774 1 186 9 112 5 o o o 743 182
64. 3 SOFTWARE VERSIONS PRO version professional full PRO version can be used without any limitation in any can be used without any limitation in any field PRO version inlcudes all the features of the software EDU version educational EDU version can only be used in training or educational fields No use is permitted in projects engineering work installation work and in general in any case in which there is derived economic transactions EDU version 1s not permitted in research fields EDU version is limited to total average daily load of 10 kWh EDU version inlcudes all the features features of the software except for Sensitivity analysis Probability analysis Batteries models Copetti and Schiffer Net mettering All versions need internet connection to verify that the license is active If no internet connection is available HOGA will not run The internet connection is required only to get the current date from the internet and check the validity of the license R Dufo L pez HOGA User Manual 4 License terms to use iHOGA for all versions All rights reserved You may not modify reverse engineer decompile or disassemble the object code portions of this software You may not sell rent lease or otherwise charge for the distribution installation copying or storage of the Software This Software is owned by Rodolfo Dufo L pez and is protected by copyright law and internati
65. 4 Schiffer 2007 Cycles to failure Temp J 18 F18 M20 20 M22 J 22 Mean C at fC J2 A422 520 020 N18 D18 20 10 20 30 40 50 60 70 80 90 V Except Schiffer model consider Tmean gt T flotat life Depth Of Discharge lh calculation usg madet Number of full equivalent cycles 1254 3 O Rainflow cycle counting 7 Modified gt Full equivalent cycles Annual Inflation Rate expected 2 2 Max Variation of Wind Batteries expected e g for an expected for Batteries Costs 60 reduction on current Batteries cost introduce 60 The limit is reached in 45 4 years As usual data for each component type is displayed in rows 3 10 1 General data General data for batteries includes Name Nominal Capacity Cn in A h Nominal Voltage Vn Acquisition Cost Operation and Maintenance Costs yr for each unit Minimum State of Charge SOCmin as a percentage of maximum SOC Self Discharge Coefficient monthly Maximum Acceptable Intensity Imax for each battery in A Global roundtrip Efficiency and Floating Life in PRO we must indicate the temperature at which floating time is defined usually 20 C Additional data must be provided for each battery on the number of life cycles between failures for each discharge depth percentage displayed in red 1HOGA calculates cycled energy throughout battery life for each Discharge Depth Depth in Life Cycles Cycles pair provided Depth
66. 4 65kwW h m2 Load2 2 18kwW h day I 911 4 2 Inf F 1 Base Pr 1 x1 1 x1 x1 NPC 12409 CO2 Emissions 104 kg yr Unmet load O kWh yr 0 Days range INF E renewable 98 of demand Levelized cost of energy 0 62 k Wh Components PV generator 1350 wp 60 4C Generator 1900 VA Batteries bank of 11232 Wh Batt charge reg 54 A Inverter 500 VA Rectif 501 Ww SENSIT ANALYSIS 3 Rad 2 5 58kW h m2 Load1 3 63kw hed a I g l 4 2 Inf F 1 Base Pr 1 x1 x1 17 x1 NPC 14521 CO2 Emissions 105 kg pr Unmet load O kWh yr 0 Days range INF E renewable 100 of demand Levelized cost of energy 0 44 kWh Components PV generator 2430 Wp 60 4C Generator 4000 V Batteries bank of 9360 Wh Batt charge reg 96 A lnverter 500 VA Rectif 01 SENSIT ANALYSIS 4 Rad 2 5 58k Wh m2 Load2 2 18kWh day 1 gj1 4 2 Inf F 1 Base Pr 1 x1 x1 1 x1 NPC 11447 CO2 Emissions 83 kg yr Unmet load O kwhzyr 0 Days range 3 3 E renewable 100 of demand Levelized cost of energy 0 58 kwh Components PW generator 1620 Wp 60 Batteries bank of 11232 Wh Batt charge reg 64 A Inverter 500 VA Rectif Ow SENSIT ANALYSIS H 5 Rad 3 7 44kwW h m2 Load1 3 63kw hed a 1 gj1 4 2 Inf F 1 Base Pr 1 1 x1 1 x1 NPC 14168 CO2 Emissions 154 kag yr Unmet load O kWh yr 0 Days range INF E renewable 96 8 of demand Levelized cost of energy 0 43 kWh Components PY
67. 47 kW de A wm Multiplier Gearbox Efficiency 98 x 35 Electrical Generator Efficiency 30 x ES Cost for Electronics and Electrical generator 500 kw 25 Emissions CO2 equiv manufacturing 5 g C02 equiv 4 kWh generated ELECTRICAL EFFICIENCY s a o w 0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100 MAX FLOW The table may be accessed as explained in previous sections Hydro turbines data The general data for each turbine include Name Voltage Type DC or AC in the pop up menu Flow maximum l s Minimum pressure height m Maximum pressure height m Acquisition Cost Useful Lifespan years and Operation and Maintenance Costs yr for each turbine Additional data must be provided on turbine efficiency as a function of load 1 e versus percentage of maximum flow Turbine performance is displayed in the chart We can add individual turbines from the database More data Data must be displayed outside the chart on the performance of the multiplier gearbox and of R Dufo L pez HOGA User Manual 95 electric generators as well as on the specific cost for these kW Any converter losses must be included for DC turbines with a voltage different from that of the DC bus As shown for the generators above DC turbines will be connected to the DC bus and AC turbines will be connected to the AC bus The default screen shows a turbine conn
68. 481 408 7 510 Results corresponding to characteristic cases combinations of data AVERAGE AVERAGE StdDv AVERAGE 3StdDv AVERAGE StdDv AVERAGE 3StdDv 511 Case Rad kWh m2 day Wind m s W_flow l s Load kWh day C total NPV S Energy cost S kwh Emission kgCO2 512 500 4 65 3 32 3 7 04 28915 1 0 45 299 8 513 501 4 65 3 32 3 7 34 30204 3 0 451 341 5 514 502 4 65 3 32 3 7 94 35763 6 0 494 526 4 515 503 4 65 3 32 3 6 74 28078 9 0 457 273 1 516 504 4 65 3 32 3 6 14 27007 7 0 482 236 6 517 505 4 85 3 32 3 7 04 28276 3 0 44 277 9 518 506 4 85 3 32 3 7 34 29184 8 0 436 306 8 519 507 4 85 3 32 3 7 94 32599 8 0 45 420 9 520 508 4 85 3 32 3 6 74 27542 7 0 448 254 8 521 509 4 85 3 32 3 6 14 26751 0 478 228 522 510 5 25 3 32 3 7 04 27255 8 0 424 245 2 523 511 5 25 3 32 3 7 34 27908 7 0 417 265 2 524 512 5 25 3 32 3 7 94 29621 7 0 409 321 9 525 513 5 25 3 32 3 6 74 26949 8 0 438 234 4 526 514 5 25 3 32 3 6 14 25911 5 0 463 219 4 527 515 4 45 3 32 3 7 04 30002 7 0 467 334 7 528 516 4 45 3 32 3 7 34 32187 2 0 481 408 7 529 517 4 45 3 32 3 7 94 39263 6 0 542 643 530 518 4 45 3 32 3 6 74 28776 2 0 468 295 531 519 4 45 3 32 3 6 14 27225 7 0 486 244 1 532 520 4 05 3 32 3 7 04 35469 5 0 552 518 5 533 521 4 05 3 32 3 7 34 39035 6 0 583 637 5 534 522 4 05 3 32 3 7 94 47546 6 0 657 904 7 535 523 4 05 3 32 3 6 74 31968 1 0 52 401 6 536 524 4 05 3 32 3 6 14 28364 6 0 507 282 7 537 Results corresponding to case shown in simulation 538 Case Rad kWh m2
69. 96 1 3 8 44 386 2 February 6 4 65 0 A 96 0 3 8 6 4 316 6 March 95 55 9 4 55 95 9 E 10 7 254 37 April 12 2 51 9 5 51 95 5 3 6 14 5 174 76 May 16 8 47 9 6 31 95 6 3 0 20 4 62 213 June 214 43 0 7 10 95 8 2 8 26 2 8 343 The user must then select the methodology to be used for calculation of hourly irradiation values on an inclined surface Available methods include Graham s 1990 17 which accounts for statistical variability or Liu and Jordan s 1960 18 and Hay and Davis 1978 19 and Rietveld 1978 20 with correlations Liu and Jordan 1960 18 Collares Pereira 1979 21 y Erbs et al 1982 22 Calculation Method for Hourly radiation C Liudordan Erbe et al e Collares Perelra amp Aabl Graham Import Hourly Data File 1 1 1 1 Data source O Monthly Average ai Import Hourly Data File in kHz Import For the Import Hourly Data File option the file must have the following format irradiation data on a horizontal surface expressed in KkWh nY and laid out in rows with each row corresponding to each 1 hour interval A total of 8 760 rows will be displayed sorted by date and time 1 e the first row will refer to irradiation data on a horizontal surface expressed in kWh m for J anuary 1 at 12 a m 00 00 with the second row including data for January R Dufo L pez HOGA User Manual 64 1 at 1 a m 01 00 and so on Click on Import to use the desired file SHADOWS
70. A Mutation Uniform 35 See best 10 100 N DE CASOS A EVALUAR Y TIEMPO ESPERADO Computation speed 52 2 cases second EVAL ALL POB TODAS C GEN ALG ALL MAIN ALG COMB COMPONENTS 468 16 3 4188 224 47 95322 1x468 1 SEC ALG COMB STRATEGY 7 700 95 9500 ALG PCPAL ALG SEC CASOS A EVALUAR TIEMPO ESPERADO OPCION1 M ENUM M ENUM 468 100 Oh 0 9 OPCI N 2 M ENUM ALG GEN 44460 9500 Oh14 11 OPCI N 3 ALG GEN M ENUM 224 47 9 Oh0 4 OPCI N 4 ALG GEN ALG GEN 21280 4547 Oh6 4 Optimization by means of enumerative method evaluating all combinations It is guaranteed to obtain the optimal solution It is recommended that the user let HOGA select the parameters of the optimization Annex I explains details on genetic algorithms and the selection of parameters optimization SIMULATION START User must decide the time of the year when the simulation is started default January 1 Oh Simulation start hour day 1 month 1 THE WORST CASE METHOD PV ONLY SYSTEM SETTING COMPARISONS An option is available to compare the results obtained through a hybrid system and those provided by a pure Photovoltaic system PV only calculated according to the Worst Case Method For this option a number of days must be introduced for the battery to supply the load Please note that PV panels and batteries must be selected for this option to be available Compare wit
71. AT in PRO version in the components area in the other versions AUXILIARY or selecting Auxiliary in the Data menu Auxiliary equipment includes Battery Charge Regulators and AC DC Converters rectifiers PV battery charge controllers The photovoltaic battery charge controllers to be considered must be added in the table We assume that the wind turbines include their own battery charge regulators In the case of bidirectional controllers inverters with battery charger included with the option Battery charger selected see next section if in a particular combination of components used such an inverter regulators in this table will not be taken into account Once simulated each combination of components and strategy for each case HOGA determines the maximum intensity required by the charge controller and 1t chooses the charge controller such that its maximum rated current is greater than the maximum expected in the system If no controller of the table meets this requirement the controller is considered as a generic one taking into account that the acquisition costs for these generic controllers are related to the maximum intensity with a fixed independent value and an additional parameter which is multiplied by the value of the maximum intensity We can add from database individually Add from database button or we can force to be included in the table only the PV battery controllers of a family which ar
72. Acid Battery Storage Model for Hybrid Energy Systems Solar Energy 1993 50 5 399 405 25 Copetti JB Chenlo F Lead acid batteries for photovoltaic applications Test results and modeling J Power Sources 1994 47 1 2 109 18 26 Copetti JB Lorenzo E Chenlo F A general battery model for PV system simulation Prog Photovoltaic 1993 1 4 283 92 27 Schiffer J Sauer DU Bindner H Cronin T Lundsager P Kaiser R Model prediction for ranking lead acid batteries according to expected lifetime in renewable energy systems and autonomous power supply systems J Power Sources 2007 168 1 66 78 28 Downing SA Socie DF Simple Rainflow Counting Algorithms International Journal of Fatigue 1982 4 1 31 40 29 The Hybrid Power System Simulation Model Hybrid2 http www ceere org rerl projects software hybrid2 30 Dufo L pez R Bernal Agustin JL New Methodology for the Generation of Hourly Wind Speed Data Applied to the Optimization of Stand Alone Systems Energy R Dufo L pez HOGA User Manual 190 Procedia Volume 14 2012 Pages 1973 1978 Presentado en el 2011 2nd International Conference on Advances in Energy Engineering ICAEE 2011 Bangkok Thailand December 26 2011 31 Gregory J M Peterson R E Lee J A Wilson G R 1994 Modeling wind and relative humidity effects on air quality International Specialty Conference on Aerosols and Atmospheric Optics Radiative Balance and Visual Air Qu
73. BATTERIES ENERGY Wh 4 January COMPONENTS ENERGY wh Days displ 9 7 Discharge Batteries ff PY panels Plimit Charge BATTERIES ENERGY wh E a 7 E to supply batt Electrolyzer P2 71 Soc I 7 E max disch batt E H2 tank HHY H2 FJ P1 71 SOC limits E 7 Charge Batteries Fuel Cell P critical Gen Cap Max 7 Excess Energy Y Unmet Load ERA man ae re P critical FC SOC setpoint Gen max 7 water tank wh from pumpling Y Wind Turbinas E Pmin Gen SOC setpoint FC Hydro Turbine E Bought to AC grid E Y Water pump a Pmin FC y 7 AC Generator E sold to AC grid soc 0 1 T full ch Pmax input Inverter PP me Gen H2 TANK setpoint HH H2 full charge Back Save Simulation Data Save Prob Data COMPONENTS PY generator 3240 wp slope 603 wind turbines group DC 546 W AC Generator 1900 VA Batteries bank 9360 Wh Inverter 500 V Rectifie AC DC 496 w ESTRATEGY LOAD FOLLOWING Pigen INF W Pmin_gen 570 SOC stp gen 20 SOC min 20 The whole load is covered all the hours of the year If you click the button Save Prob Data the results of the N 57 Probability variables caries are saved in Excel format If you open the file with Microsoft Excel it reports a message you must answer Yes and it opens correctly In Microsoft Excel you should save the Excel file as xlsx format in Excel use Save As and choose file format xlsx
74. C Generator detailed Water load Total Load 0 3 0 2 0 1 O 1 000 2 000 3 000 4 000 5 000 6 000 7 000 8 000 Hydro Turbine 0 1 000 2 000 3 000 4 000 5 000 6 000 7 000 8 000 Fuel Cell 0 1 000 2 000 3 000 4 000 5 000 6 000 7 000 8 000 Batteries Charg 0 6 Pe RE 0 2 0 O 1 000 2 000 3 000 4 000 5 000 6 000 7 000 8 000 Unmet load by the standalone system HOURLY ENERGY DURING THE YEAR kWh PV Generator 06 Re a 0 44 0 2 0 0 1 000 2 000 3 000 4 000 5 000 6 000 7 000 8 000 AC Generator 0 1 000 2 000 3 000 4 000 5 000 6 000 7 000 8 000 Electrolyzer pie ae eee ne Pee 0 1 000 2 000 3 000 4 000 5 000 6 000 7 000 8 000 0 O 1 000 2 000 3 000 4 000 5 000 6 000 7 000 8 000 Purchase E from AC grid A ANN AA AA AAA A Wind Turbines ya iii 2 FATT SOT TT Re aad ee 0 0 1 0002 000 3 000 4 000 5 000 6 000 7 000 8 000 Excess Energy i p 0 1 000 2 000 3 000 4 000 5 000 6 000 7 000 8 000 Energy HHV of H2 in H2 tank Li 0 1 000 2 000 3 000 4 000 5 000 6 000 7 000 8 000 O 1 000 2 000 3 000 4 000 5 000 6 000 7 000 8 000 Sell E to AC grid 0 I O 1 000 2 000 3 000 4 000 5 000 6 000 7 000 8 000 Monthly and annual average power tab This tab displays for each month 1 12 and for the full year the average power kW supplied by different technologies stacked bar and the average values of the power consumption unmet
75. C100 C20 and C10 columns are replaced by columns for k 1 h c and Qmax Ah These values must be provided by the battery manufacturer Add Battery Zero Add Batteries family DPZ S Hawker C nom Yn DPZS Hawker TWS 390 DPZS Hawker TVS 550 DPZS Hawker TYS 816 JPZS Hawker TYS 1 1340 PZS Hawker TZ5 1 1940 PZS Hawker TZS 1 2240 PZS Hawker TZ5 2 2800 PZS Hawker 125 2 3080 DTAEE 3360 Fixed Operation and Maintenance Cost Acq C O0 amp M SOC Self Cost unit 164 9 202 298 578 664 308 Batteries Model Ah Schuhmacher 1993 KiBaM Manwell McGowan 1993 Copetti 1994 Schiffer 2007 Temp J 18 F18 M20 420 Bat GC J 22 422 20 020 V Except Schiffer model consider Tmean gt T flotat life M 22 N 18 1 65 2 02 2 98 412 5 78 6 64 8 9 08 10 1 50 E yr Data J 22 D18 KiBaM Model Calculate Mean PFC 20 163 2 268 388 448 560 672 Cycles to failure Global min disch Imax Effic 85 85 85 85 85 85 85 Float life at20 C KiBaM Model Cycles to Failure vs Depth of Discharge c Cmax 12000 12000 12000 12000 12000 12000 12000 12000 12000 6500 6500 6500 6500 6500 6500 6500 6500 6500 4250 4250 4250 4250 4250 4250 4250 4250 4250 3100 3100 3100 3100 3100 3100 3100 3100 3100 2500 2500 2500 2500 2500 2500 2500 2500 2500 Equivalent CO2 emissions m
76. CASES TIME EXPECTED OPTION 1 EvAL ALL EVAL ALL 468 100 mos OPTION 2 EVAL ALL GEN ALG 44460 900 0h14 11 OPTIONS GEN ALG EVAL ALL 224 479 mos OPTION 4 GEN ALG GEN ALG 21280 4547 DhE 47 Optimization by means of enumerative method evaluating all combinations It is guaranteed to obtain the optimal solution Notes If the battery model is the Schiffer much more accurate than the others see ref 38 the computation time is several times higher as the simulations take much more time This is already taken into accoun byt HOGA to estimate the computation time If control strategies is marked Try both the calculation time is somewhat higher This already takes into account HOGA It is recommended to let HOGA select optimization parameters However if the maximum execution time we allow is too small HOGA shows the minimum time to be spent in the optimization to get the optimal solution or a solution near the optimal with high probability The parameters are displayed pushing Display Parameters button R Dufo L pez HOGA E PARAMETERS OF THE OPTIMIZATION MAIN ALGORITHM OPTIMIZATION OF COMPONENTS OPTIMIZATION METHOD GENETIC ALGORITHMS 1 EVALUATE ALL COMBINATIONS o EVALUATE ALL COMB User Manual M TODO DE OPTIMIZACI N GENETIC ALGORITHMS Mutation Uniform 1 EVALUATE ALL COMBINATIONS o EVALUATE ALL COMB ALGORITMO SEC OPTIMIZACI N ESTRATEGI
77. Dland JOBS Sensitibity Analysis Probability Analysis CALCULATE E Save Table as Excel HOGA User Manual 143 4 3 Optimizing with No Genetic Algorithms Enumerative Method If the maximum execution time allowed is higher than the time needed to evaluate all combinations 1HOGA will select the EVALUATE ALL COMB option For example if the maximum execution time is as default 15 minutes and the number of combinations of components and control strategies 1s low 1n this example only 312 which can be evaluated in 7 seconds then HOGA will evaluate all possible combinations OPTIMIZATION PARSMETERS SELECTED Er o IHOGS USER Maximum execution time 7 Display Parameters O h 15 min NUMBER OF CASES AND TIME EXPECTED Computation speed 46 512 cases second EVAL ALL POP ALL GEN ALG ALL MAIN ALG COMB COMPONENTS 312 11 3 934 154 43 555 1531 2 SEL ALG LOMB STRATEGIES 1 3 30016 122 122004 MAIN ALG SEC ALG NUMBER OF CASES EA TIME EXPECTED OPTION 1 EVAL ALL EVAL ALL 312 100 Oh 0 7 OPTION 2 EVAL ALL GEN ALG 368064 12200 Oh 13 35 OPTION 3 GEN ALG EVAL ALL 154 49 43 Oh 0 3 OPTION 4 GEN ALG GEN ALG 18708 6021 862 Uh 43 Optimization by means of enumerative method evaluating all combinations Itis guaranteed to obtain the optimal solution This 1s also possible 1f you select in Parameters of the
78. E O amp M P TOTAL COST NPC 29441 5 Financial Cost NPV initial payment annual quotas 17851 5 m Lo Total Cost of Hydro Turbine NPC 0 Total Cost of AC Generator NPC 1361 3 1 000 500 0 5 10 15 20 25 0 5 10 15 20 25 Total Cost of Inverter NPC 1140 9 Total Cost of Batteries Bank NPC 5057 4 0 Pagel of 2 When you close the report screen appears asking 1f you want to save the results of the cash flows in the form of Excel sheet Save Data Do you want to save cash flow If you click Yes you save the file and when you open it the cash flow of costs and incomes of the years of the system lifetime are shown for each component and also for purchasing or selling energy from the grid etc For each cost or income for each year it is shown the cash of the year and the actualized cash NPC Also total values for each component and for each year are shown R Dufo L pez HOGA User Manual 174 Al f Project 1 hoga Solution 0 ar T D E F G H Le LT EN PY PO N o p a R Project 1 hdiga Solution 0 a 2 3 CASH FLOW THROUGHOUT SYSTEM LIFETIME _ 4 CASH FLOW OF COSTS AND INCOMES _5 Initial cost of investment 15884 3 S included installation and initial variable costs of 693 8 Loan of 80 96 6 All values in currency Costs Incomes For each component cahs flow includes initial acquisitio
79. ENSE ESET a sername Gary Cooper Kew 1 MN Key 2 7 IS VALIDATE E mail address where vou want to receive the activation key garyeoopertajok rg jk Request activation key HOGA User Manual 23 Then you click on Request activation key Under the button Request activation key a message appears indicating to copy the lower window text and email it Send e mail to rdufo O unizar es Subject Activation IHOGA 2 0 requested by user name Lora copy and paste in the e mail Warning Before you click the Close Program button make sure you have copied the contents of the window and it was sent by e mail to rdufoO unizar es with the subject HOGA 2 0 Activation requested by Soon you will receive by e mail the activation key HE LICENSE lo 51 x sername Gary Cooper Key 2 a VALIDATE E mail address where you want to receive the activation key garycoopertajokina ik Request activation key Copy and paste the text in the window below and send it to rdufo unizar es with the subject Activation HOGA 1 0 requested by You will receive the activation key send e mail to r subject Actwaci Text Gary Coop EF ZMHA 67194 1331 20 20 712568 y Close program Then clicking on the Close Program button 1t appears a screen asking for confirmation and the program closes The next time you boot the software HOGA asks for the activation key Copy and past
80. ERIES DURING 1 YEAR 3854 Range 0 15 DOD 5 25 DOD 25 35 DOD 35 45 DOD 45 55 DOD 55 65 DOD 65 75 DOD 75 85 DOD 85 100 DOD 3855 Cycles 95 318 1 2 o o o 2 o 3856 R Dufo L pez HOGA User Manual 160 If there are days when the whole load is not covered by the standalone system there is energy not served by the standalone system which will be purchased from the ac grid if there is AC grid and the purchasing is allowed the days when not all the energy is covered by the standalone system are shown later 4 4 2 Simulation in case of probability analysis Only in PRO version If we performed the optimization with the option of probability analysis in the simulation screen 1s will be displayed the case that we have chosen on the screen of probability analysis see next figure and end of section 3 18 In the simulation show the case obtained with the following data Irradiation Wind Speed Water flow Average Average h Average kd lude hourly variability Average Std Dev Average 5td Dew In verage Std Der in the last two charts show the probability distribution of Average 3Std Dey A A en A O AT Lt Larra 4 1 By clicking on SIMULATE as shown in 4 6 2 the N series are calculated and also other number of probability variables additional series combinations of average average Std Dev average 3Std Dev average Std Dev average 3Std Dev of different variables taken into
81. GA y A NEN VENNE DR D a O O A VENNI A i J K L M N jo RG Project 1 H GA 2 Gen NPC S Em CO2 kg yr Unmet kWh yr Unmet Days range Cn Ah Isctidc A Renewable fractio 3 EE 0 42391 86 275 76 0 0 6 69 9 48 100 5 1 42391 86 275 76 0 0 6 69 9 48 100 6 2 21701 3 135 26 0 0 1E 15 7 37 99 14 Ed 3 21701 3 135 26 0 0 1E 15 7 37 99 14 8 4 21701 3 135 26 0 0 1E 15 7 37 99 14 5 21222 45 176 17 0 0 1E 15 5 92 96 82 10 6 20824 29 133 88 0 0 1E 15 5 27 98 84 E 7 20824 29 133 88 0 0 1E 15 5 27 98 84 12 8 20824 29 133 88 0 0 1E 15 5 27 98 84 13 9 20824 29 133 88 0 0 1E 15 5 27 98 84 14 10 20824 29 133 88 0 0 1E 15 5 27 98 84 15 11 20824 29 133 88 0 0 1E 15 5 27 98 84 16 12 20824 29 133 88 0 0 1E 15 5 27 98 84 17 13 20824 29 133 88 o 0 1E 15 5 27 98 84 18 14 20824 29 133 88 0 0 1E 15 5 27 98 84 19 20 21 22 E 24 25 26 27 28 2 30 31 32 In Microsoft Excel you should save the Excel file as xlsx format in Excel use Save As and choose file format xlsx then the next time you open the xlsx file Excel will not ask you any question R Dufo L pez HOGA User Manual 141 4 2 Multi Objective Optimization If on the main screen of 1HOGA Optimization tab see section 3 1 4 you have selected Multi objective the optimization results will be different OPTIMIZATION TYPE MONO 7 MULTI OBJECTIVE MONO OBJECTIVE o MULTI
82. H2 in order to start generating electricity In the case of the figure the fuel cell requires at least one hydrogen mass flow rate of 0 008 kg h so that 1t can generate useful electrical power If the fuel cell uses H2 from the tank previously generated by the electrolyzer in the simulation if during a certain time no more than 0 008 kg in stored in the tank the battery can not generate any power during that time and therefore will not work during that time R Dufo L pez HOGA User Manual 120 FC2 Consumo kg h y Eficiencia PCI O 0 15 pa O To A 0 1 e fa Ta gt 0 05 a DO rE o cu 0 LU 0 1 2 OUTPUT POWER kW Rated Power 2 kW tis needed at least 0 008 kahh to generate electrical power Origin of fuel used by the fuel cell The initial screen displayed corresponds to the Fuel Cell Click on the check boxes bottom right to select the origin of the fuel to be used by the fuel cell The default value is H2 produced in Electrolyzer This implies that an electrolyzer is in operation to generate H2 with excess energy H is stored in the tank and is used by the fuel cell to produce electricity when necessary Fuel from H2 produced in electrolyzer C Exterrial If the origin of the fuel 1s External no electrolyzer will be required In this case use of a tank will depend upon the fuel supplier this is not the Hz tank and the check box is enabled to include exclude an electro
83. I s Load kWh day C total NPV S Energy cost S kwh Emission kgCO2 10 0 4 65 3 32 3 7 04 28915 1 0 45 299 8 as 1 4 91 3 32 3 7 04 28143 2 0 438 273 5 12 2 4 91 3 32 3 6 77 27479 4 0 445 252 7 13 3 4 7 3 32 3 6 85 28272 6 0 452 277 7 14 4 4 55 3 32 3 7 39 31483 4 0 467 385 15 5 4 82 3 32 3 7 54 30027 8 0 436 335 7 16 6 4 52 3 32 3 7 03 29560 9 0 461 319 5 17 7 4 63 3 32 3 6 87 28525 8 0 455 286 5 18 8 4 44 3 32 3 7 11 30513 5 0 471 352 as 9 4 63 3 32 3 6 31 27192 8 0 473 243 20 10 4 76 3 32 3 7 3 29432 4 0 442 315 5 a 11 4 48 3 32 3 6 45 27856 1 0 474 265 6 22 12 4 86 3 32 3 6 98 28136 4 0 442 273 4 23 13 4 73 3 32 3 6 89 28302 8 0 45 278 7 24 14 4 72 3 32 3 7 52 30795 1 0 449 361 6 25 15 4 8 3 32 3 7 38 29578 8 0 44 320 1 26 16 4 65 3 32 3 7 26 29791 5 0 45 327 4 27 17 4 43 3 32 3 6 98 29683 5 0 466 325 8 28 18 4 86 3 32 3 7 13 28500 1 0 438 285 6 29 19 4 81 3 32 3 7 17 28784 0 44 295 2 30 20 4 64 3 32 3 6 83 28356 2 0 455 280 8 31 21 4 54 3 32 3 7 38 31544 8 0 468 387 3 32 22 4 78 3 32 3 6 92 28204 2 0 447 275 6 33 23 4 48 3 32 3 6 76 28744 3 0 466 294 34 24 4 64 3 32 3 6 54 27604 4 0 463 257 35 25 4 55 3 32 3 6 71 28355 3 0 463 280 7 36 26 4 58 3 32 3 7 29104 0 456 306 1 27 5 06 3 32 3 7 03 27691 6 0 432 258 3 38 28 4 69 3 32 3 6 79 28171 7 0 455 274 2 4 gt 3xks Pd DO m j 0 Al Y Do fe Project 1 hoga Solution 0 4 MI O ISO E O IV TEST O TEST OU SY VO A 509 499 4 45 3 32 3 7 34 32187 2 0
84. IHOGA Version 2 2 User Manual 6 November 2013 Dr Rodolfo Dufo L pez rdufo unizar es Electrical Engineering Department University of Zaragoza Spain HOGA User Manual R Dufo L pez HOGA User Manual 2 News in HOGA 2 2 from 2 1 Added the possibility of forcing the AC generator to run all the time to generate the AC grid Added the possibility of connecting the PV generator to the AC bus Added the possibility of connecting the fuel cell and the electrolyzer to the AC bus Added access toll and support toll if applicable for the purchase of electricity from the AC grid Added transfer toll for the injection of electricity to the AC grid Removed the option of the project type of control strategy optimization only Added table for photovoltaic batteries charge controllers Once simulated each combination of components the regulator is selected as the minimum of the table which rated current 1s higher than the obtained in the simulation Added features for inverters battery charger bi directional converter battery charge controller The text which shows the optimal system characteristics includes the names of the components and this text can be copied and pasted The report includes the names of the components The minimum power of the rectifier battery charger for the AC generator is associated with the AC generator power Changed 1HOGA icon R Dufo L pez HOGA User Manual
85. LOAD w DC LOAD W H2LOAD kg WATER m3 day FROM WATER TANK PREVIOUSLY PUMPED PURCHASE SELL ENERGY Purchase from AC grid Unmet Load Non Sell Excess Energy to AC grid Served Energy by Stand alone system Sell surplus H2 in tank difference between the HZ in the tank at the Fixed price E kwh 0 15 Hourly price Peal es en E dica corona eae as o Pr sell pr purchase x 1 Annual Inflation EL Emission kglo27kh 3 0 4 Annual Inflation 55 3 Pmax kw Fixed Cost P Er Max Power kw 100 le E 1000 0 Energy Generation Toll Traneter Toll Eta SZ Fixed Transfer T price Ek 0 0005 Hourly Price Access Toll Price Eh J Fixed Access T price Erkwh 0 1 Hourly Price Data to compare with electrical supply only from AC conventional grid Price Support Toll applied in Spain Eta ho Sel consumption and Met bettering v Fixed Support T price kih O Hourly Price Total cost installation of AC grid 3000 E The cost of the support toll will be added to the E purchased SUE h O amp M annual cost of grid 100 Total tax for electricity costs bought tolls Et 0 Total tax for electricity sold Et 0 Purchasing from AC grid Unmet Load Non Served Energy by Stand alone system The energy not supplied by the hybrid stand alone system can be purchased from the AC grid if it is selected rchase from AC grid Unmet Load Non erved Energy by Stand alone system J Fined price Erkwh 0 75 Hourly p
86. NF 71 968 05 SIMULATE REPORT Energy Storage 4 days range 14 16483 179 0 0 INF EA 96 8 t SIMULATE REPORT Max bat parallel gt Cn min v Max PY pan parallel gt P min 4 lil j Max wind t parallel gt P min er A mee E COMPONENTS 2s x 8p PY panels of 135 W ER 602 4 12s x 1p batteries of 468 Ach 2 AC Generator 4 kVA 2 Inv 500 V 2 Rect 1080 47 2 Unmet load O Sensitivity Analysis 4 NPC 16493 0 5 kWh a CALCULATE STRATEGY LOAD FOLLOWING P1 gen INF Pmin_gen 12004 Peritical_gen 0 w SOC setpoint_gen 20 SOC min 20 Sensitivity Analysis Summary Save Table as Excel We can see the results of any other analysis by selecting the number of analysis down or selecting each individual case analysis variables For example in the following screen is selected Sensitivity Analysis 3 corresponding to Wind 1 Rad 2 Load 1 l g 1 Inf F 1 Pr and results are shown in the table next figure R Dufo L pez HOGA User Manual 179 Project Data Calculate DataBase Report wf LOAD RESOURCES Y SOLAR WIND HYDRO COMPONENTS Y PV PANELS WIND TURB HYDRO TURB Y BATTERIES Y INVERTERS Fl Sketch 7 Chart S BB CO2 EMISSIONS kg year ab un MS lo Windl 3 32m s y Rad 2 5 58kwh m2 Loadl 3 63kWh dia SS ee Inf F 1 Base y Y AC GENERATOR H2 F C Elyzer gen Total Cost NPCJ
87. NPC for the system in mono objective optimization For multi objective optimization 2 5 6 11 15 16 1HOGA will seek solutions with low NPCs as well as low CO emissions or unmet load In version 2 0 PRO two more potential objectives to maximize have been added the Human Development Index HDI and Job Creation The user decides whether the inverter may be optimized or it has a fixed value with its rated power higher than the maximum AC load power All remaining elements battery charge regulator rectifier hydrogen tank are optimized by HOGA with respect to each other and to the control variables in use The secondary algorithm obtains the most appropriate control strategy combination of control variables see Annex 2 for details of the control strategy for minimum costs and for any given component setup provided by the main algorithm The total cost may thus be calculated referred to the initial installation time NPC for each possible solution obtained from both algorithms and including e Initial system costs acquisition of system components In most cases where optimization is applied through 1HOGA cash flows are usually expenses only purchasing replacement maintenance and fuel costs etc with no income The different costs throughout the whole of the study period are referred to the initial time of the investment using the discount rate approx interest rate minus inflation rate thereby producing the
88. NPC The lower the NPC value the better the investment It is possible to use the option in 1HOGA to sell surplus hydrogen and electric energy to the AC grid it is also possible to purchase energy from the grid to compensate for unmet load by the hybrid system In those cases sales are accounted for within iHOGA as negative values since they must be subtracted from component replacement and maintenance expenses We may thus achieve an income from energy sales which is higher than system costs resulting in a negative value for NPC This means that our facility will achieve a net benefit positive values meant expenses i e costs A larger negative value for our NPC will indicate a more profitable system R Dufo L pez HOGA User Manual 14 e Fuel costs for the AC generator usually fuel oil e Fuel costs for the fuel cell in case the fuel cell uses external fuel 1 e fuel not generated by an electrolyzer e Operation and maintenance costs e Replacement costs for components whose lifespan is lower than the study period up to 25 or 30 years usually the same as the useful lifecycle of PV panels e Incomes from sales of surplus hydrogen and electric energy to the AC grid e Incomes from sales of components whose lifespan is not over when study period 1s finished This income is calculated assuming that the component has a residual value proportional to the difference between its lifespan and the time elapsed betwee
89. Optimal Slope Metheorological data form NASA web Optimize FV panels slope during the optimization of the system Longitude E 44 0 56 Data source imp Calculation Method for Hourly radi tor o Monthly Average Import Hourly Data File in kh Data Source for Monthly Average Daily Radiation Radiation Horizontal Surtace kW h m Irradiation ar horiz January len Februrary 259 March 4 03 April 5 4 Iradiation av till sur htm aff kth me 431 kimh me D1 kWh m 4 09 K4h m2 E Liudordan Erbs et al Tracking system No Tracking a Collares Pereira amp Rabl 6 Graham Summer HORIZONTALMONTHLY AVERAGE DAILY RADIATION HORIZONTAL SURFACE a Official hour advances a E ES A SES 2 hto solar hour May 6 13 June E July fa August B3 September 5 13 October 3 59 November 2 2 December 1 5 SHADOWS Daily Average Irradiation Honz Surf Total 4nnual Irradiation Horiz Surf DK Calculate Draw Data must be input on ground reflectance on the top right typically 0 2 From day 30 a kama of month 3 B26 kM heme 8 61 kM here 6 04 kytheme2 Winter 5 55 kh rie Official hour advances 2 96 Kw h m2 Fo B 1 MONTH 63 kM heme Force Until day 26 of month 10 h to solar hour cloudy consecutive days only difuse irradiation in month Enero 44 ki h mo 1612 97 kha Daily Average Irradiation Plane of PY 4 64 ka heme T
90. RE OA het ote Rowe cee Pa Unmet load by the standalone system Purchase E from AC grid Sell E to AC grid Annual values tab This tab displays total annual energy kWh R Dufo L pez HOGA User Manual 155 Hourly simulation Hourly values separately Monthly and annual Average Power Monthly values Annual values Hydrogen detailed AC Generator detailed Water load Energy kWh TOTAL ANNUAL ENERGY kWh LOAD UNMET PURCH EXCESS SOLD PV GEN WIND T Charge BAT Disch BAT Hydrogen detailed tab Values of hydrogen consumed and generated for each month in kg and kWh energy are displayed Also hydrogen values accumulated in the tank at the end of each month The example figure of this simulation corresponds to a system different from the simulation seen before Hourly simulation Hourly values separately Monthly and annual Average Power Monthly values Annual values Hydrogen detailed AC Generator detailed Water load ww ho Hydrogen mass kg o MONTHLY HYDROGEN CONSUMPTION AND PRODUCTION kg AND H2 STORED IN TANK AT THE END OF EACH MONTH EJ H2 Load E H2 produced by Electrolyzer EH H2 consumed by Fuel Cell from H2 tank MI H2 consumed by Fuel Cell external hydrogen H in tank at the end of the month MONTHLY ENERGY PRODUCED BY FUEL CELL AND CONSUMED BY ELECTROLYZER kWh 1 2 3 4 5 6 T 8 9 10 11 12
91. T LOAD 0 Ren frac mean 98 1 Std Dev 1 13 RENEWABLE FRACTION ow cr Tul th 92 93 94 95 96 97 Batteries lifetime mean 19 19 yr Std Dev 0 75 BATTERIES LIFETIME yr pS eee wee 16 17 18 PV gen energy mean 3358 kWhi yr Std Dev 143 3 ENERGY GENERATED BY PV GENERATOR kWh yr 3 000 3 200 3 400 3 600 Charge energy in Battery bank mean 651 kWh yr Std Dev 22 6 ENERGY STORED IN BATTERIES BANK kWh yr 0 Hours running AC Generator mean 87 h Std Dev 54 5 0 Pagel of 3 R Dufo L pez Irradiation mean 4 66 kWh m2 day Std Dev 0 2 AVERAGE DAILY IRRADIATION kWh m2 day Water flow irrelevant there is no hydro turbine AVERAGE WATER FLOW l s Lev cost of energy mean 0 46 kWh Std Dev 0 02 LEVELIZED COST OF ENERGY currency kWh 042 044 046 048 05 052 054 0 56 CO2 Emissions mean 313 95 kgCO2 yr Std Dev 59 62 CO2 EMISSIONS kg y r Excess E mean 665 kWh yr Std Dev 158 9 EXCESS ENERGY kWh yr pee RA ih IAI i re 400 600 800 1 000 AC gen fuel mean 25 67 litre yr Std Dev 16 09 AC GENERATOR FUEL CONSUMPTION ud yr 20 40 60 80 100 12 Wind turbines group energy mean 119 kWh yr Std Dev O ENERGY GENERATED BY WIND TURBINES kWh yr 0 Energy of AC generator mean 50 kWh yr Std Dev 31 1 ENERGY GENERATED BY AC GENERATOR kWh yr 0 ti TRA Po 50 100 150 200 Annual cost of fuel of AC Generator mean 43 4 yr Std Dev 27 2 Mm PY ersz
92. ULATE REPO Max bat parallel gt Cn min Max PY pan parallel gt P min Max wind t parallel gt P min HDI and JOBS oensitibity Analysis Probability Analysis i CANCEL Cases evaluated 1723 of 3596 48 Elapsed time 34 Remaining time Oh 0 38 Each table row corresponds to the best solution for each generation NPC is shown in red with annual equivalent CO emissions including emissions from combustion of fuel in the AC generator emissions from energy bought to the electrical grid and emissions from the manufacturing of the components of the system divided into the life of the system in green In blue the variables related to constraints are shown it is shown the unmet load in kWh year and in Days range for the average daily load of the year the value of the division between the rated capacity of the battery bank and shortcut current of the photovoltaic generator plus current form wind turbines at 14 m s Cn Ah Isc Idc A the renewable fraction covering the demand and the levelized cost of energy of kWh kWh These values along with many others are also observed in the table When one or more rows show the value INF under the C total column NPC the combination of system components and or control strategy for that row does not meet the constraints we have indicated maximum unmet load allowed number of days range Cn gt N times Isc gen Photov
93. V controller with or without MPPT 1f checkbox below the table 1s or 1s not selected WK INVERTERS AND BE DI CONVERS oan oem wwe Le Se Add from Database STECA SOLARIK PI 550 v Without Rectifier charger Rectifier w o PY controller Include only WDC suitable from family STECA gt Rectifier MPPT PY controller GENERAL DATA 650 1200 ia 1800 NO 2300 NO Control Data MPPT STECA SOLARIX 1200X4 Y Select the minimum inverter required to supply the maximum AC load Select inverter a EFFICIENCY 96 ben SERGE a 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100 OUTPUT POWER OF RATED Average power is 16 8 of rated power of the selected inverter Inverter average efficiency considered will be 92 3 Select the Minimum Inverter required to Supply the Maximum AC Load The default option is checked on the Select Inverter dialogue box so iHOGA will Select the Minimum Inverter required to Supply the Maximum AC Load This requires using the inverter with the lowest power in order to supply the maximum power required by the AC loads This 1s the most common case When the inverter can not supply all necessary AC power AC consumption will not be catered for W Select the Minimum Inverter required to Supply the Masimum AC Load Select inverter In this case click on Select Inverter first A chart will be displayed with the maximum AC po
94. W C Ser value fw 11000 ES E 3 1 4 FINANCIAL DATA tab Data for financial calculations must be provided as follows see figure below lifetime of the system or period of study usually the same as the lifecycle for the PV panels ca 25 or 30 years cabling and installation costs fix cost percentage of total cost nominal interest rate I and expected general inflation rate g The programme uses these last two indicators to calculate the discount rate with a value close to subtracting one from the other Discount Rate L 9 1 g 100 This value will then be used to update the different costs affected by the general inflation rate operation and maintenance costs as well as the cost of replacing the elements which do not have a specific inflation rate throughout the whole of the study period as referred to the initial time of investment thereby producing the NPC GENERAL DATA OPTIMIZATION CONTROL STRATEGIES FINANCIAL DATA RESULTS CHART FINANCIAL DATA Loan constant quota French system Nominal interest rate price of money 4 s Annual real discount ratel 2 Amount of loan 50 Annual inflation rate O amp M 2 1 96 E of the initial cost of investment Loan Interest 7 Es System lifetime 25 years Duration of loam 10 pears Currency Dollar Installation cost and variable initial cost EMO Fin 2 of total initial cost R Dufo L pez HOGA User Manual 42 Change Currency The de
95. Wh on January 1 at 01 00 hours i e 2 000 W for 1 hour In this case the values would be displayed as a ramp going from 0 Wh at 00 00 to 2 000 Wh at 01 00 The ramp is simpler to visualize than 1 h steps less accurate though what is really happening is that the generator is supplying 0 W between 00 00 and 01 00 and 2 000 W between 01 00 and 02 00 Total consumption equals the sum of AC DC electrical consumption H consumption converted to HHV of H2 Water consumption energy needed to have pumped previously Select any or all the check boxes to view individual or global consumption values The chart also shows the value of the energy for the Hz tank HHV H at the start of each 1 hour period When the electrolyzer generates H5 the value of this parameter increases for the next 1 hour period The value will decrease when H from the tank is consumed externally or by the fuel cell Generation and consumption may occur simultaneously In this case the energy of the H tank will vary accordingly The value of the water tank is the energy needed to have previously pumped the water from the river to the water tank The value of the SOC parameter for the batteries will increase when a net charge is produced and will decrease when a net discharge occurs When neither charge nor discharge are present SOC decreases self discharge battery coefficient Parameter values may be too small to visualize in case one of these parameter
96. You could set a more extreme combination to display in the simulation for example set to AVERAGE 3 STD DEV the load consumption and set irradiation data and wind flow to the AVERAGE 3 STD DEV this case would the far worse as it is almost impossible to have values greater than the mean 3 standard deviation or less than mean 3 standard deviation After the optimization for each combination of components and control strategy in the report R Dufo L pez HOGA User Manual 133 see section 4 6 1 graphics display probability distribution of different results and in the last two graphs you can choose which results to see In the probability analysis report in the last two charts show the probability distribution of Hours running 4C Generator her Annual cost of fuel of AC Generator curency yr pr If when clicking at any cell of the results table you do not want to update the results of the row where you clikc select the last ckeck box by default not checkec so by default when you click a cell N simulations of its solution are done and its row is updated with the average values of the results When clicking at any cell of the results table do not update results R Dufo L pez HOGA User Manual 134 R Dufo L pez HOGA User Manual 135 4 CALCULATING THE HYBRID SYSTEM Once all data is introduced onto the system the Calculate button is enabled in the main screen Click o
97. a http www retscreen net A very good Canadian site where programmes may be downloaded on solar wind and hydro resources The data available correspond to readings from weather stations around the world as well as information on components prices etc For all the world http eosweb Jarc nasa gov cgi bin sse grid cgi email na http eosweb larc nasa gov sse RETScreen As explained before for wind data using EPW meheorological data solar irradiation will be in Microsoft Excel in the column N 8760 hourly values in kWh m2 They must be divided by 1000 For Europe Africa and the Mediterranean http re jrc ec europa eu pvgis apps radmonth php 8 Where can I obtain data on system components such as characteristics prices etc Apart from HOGA databases and manufacturers web sites you may download applications from http www retscreen net Information is available here on the characteristics estimated costs for different renewable energy components 9 What values should be assigned in the genetic algorithms for the following R Dufo L pez HOGA User Manual 185 parameters number of generations population mutation rate breeding rate HOGA can select them this is recommended If you want to select them yourself you must know that this basically depends upon the time available and on the accuracy required for calculation of results Better solutions will be obtained for larger population
98. age of annual Unmet Load allowed 100 annual Unmet load Total annual Energy Required by the system The Unmet Load is the energy demanded by the load and not supplied by the standalone system energy not served by the standalone system CONSTRAINTS HH asimum Unmet Load allowed 1 annual Unmet load can be covered by AC grid if it exists and itis allowed in LOAD AC GRID window More Constraints IHOGA assigns an infinite NPC value to every element combination that does not meet the requirements for Maximum Allowed Unmet Load This indicates that the system is not acceptable and will not fulfill our requirements R Dufo L pez HOGA User Manual 32 It will be possible to purchase energy from the AC grid in some cases to compensate for unmet load by the hybrid system this option 1s shown within the LOAD AC GRID screen section 3 2 In these cases we may select a percentage of energy to be purchased from the grid This value must be introduced in the field defined as Maximum Unmet Load allowed More constraints Clicking the More constraints button to access a screen showing all the possible restrictions to fix AK CONSTRAINTS i a e IF a combination of components and strategy does not meet any of the following restrictions this solution will be discarded for that combination tt Iz assigns infinite cost Maximum Unmet Load allowed 2 of annual load Minimum number of day
99. ality 32 Rivas Ascaso D M Aplicaci n inform tica para el dise o de sistemas h bridos de generaci n de energ a el ctrica Proyecto fin de carrera Ingenieria Industrial C P S Univ Zaragoza Sept 2004 Dirigido por Bernal Agust n J L y Dufo L pez R 33 J J Lander J Electrochem Soc 103 1956 1 8 34 P Ruetschi B D Cahan J Electrochem Soc 105 1958 369 377 35 Skarstein O Ulhen K Design Considerations with Respect to Long Term Diesel Saving in Wind Diesel Plants Wind Engineering 1989 13 2 72 87 36 Barley C D Winn C B 1996 Optimal dispatch strategy in remote hybrid power systems Solar Energy 58 4 6 pp 165 179 37 Rojas Zerpa Juan Carlos Planificaci n del suministro el ctrico en reas rurales de los pa ses en v as de desarrollo un marco de referencia para la toma de decisiones Tesis Doctoral Universidad de Zaragoza 2012 38 Dufo L pez R Lujano Rojas JM Bernal Agust n JL Comparison of different lead acid battery lifetime prediction models for use in simulation of stand alone photovoltaic systems Applied Energy Volume 115 February 2014 Pages 242 233 R Dufo L pez HOGA User Manual 191 R Dufo L pez HOGA User Manual 192 ANNEX 1 Genetic Algorithms Genetic algorithms 11 12 are used in computers to carry out simulations for breeding mutation and selection that are present in nature All possible solutions provided by
100. ally start the diesel generator some types allow the generator to charge the battery to 95 SOC default can be modified only in PRO version every few days or every number of complete cycles equivalents In that case check the box lower part of the window of the battery charger in PRO version in the rest of the versions in lower part of the window of the battery If there ls an AC Generator every 14 days or 8 equivalent full cycles generator charges batteries at least upto 35 3 10 3 KiBaM Model When the KiBaM model is selected the table widens and the chart shrinks to accomodate an additional graph Select Calculate to make HOGA obtain the parameters needed for the model or Data for direct data introduction EJB ati Model f Calculate f Data New columns are displayed when Calculate is selected see figure below right hand side C100 C20 and C10 all of them in Ah These values correspond to battery capacities for 100 20 and 10 hour discharge regimes The longer it takes a battery to discharge the more energy is provided so C100 will be larger than C20 which will in turn be larger than C10 This data is supplied by the battery manufacturer HOGA calculates discharge intensities in A for the 3 discharge regimes provided e g for a 100 hour regime this will be C100 100 Discharge intensity is then displayed versus battery capacity Additional values are shown under the chart for th
101. ank sell H2 residula variable values of components at the end of sy stem lifetime mean 5422 yr Std Dev 1851 Cost of purchasing Eto AC grid NPC mean 0 Std Dev 0 Incomes of selling Eto AC grid NPC mean 0 Std Dev O Variable cost of batteries NPC replacement residual mean 478 Std Dev 81 6 Variable cost of AC gen NPC 0 amp M replacement residual mean 318 Std Dev 200 5 AC gen fuel cost NPC mean 2498 Std Dev 1573 1 Cost of regulator rectifier NPC acquisition replacement residual mean 2127 Std Dev 3 1 Variable cost of Hectrolyzer H2 tank NPC 0 amp M replacement residual mean 0 Std Dev 0 Variable cost of Fuel Cell NPC 0 amp M replacement residual mean 0 Std Dev 0 Cost of purchasing external fuel for Fuel Cell NPC mean 0 Std Dev 0 Incomes of selling H2 for external use NPC mean 0 Std Dev 0 m RESULTS OF CHARACTERISTIC CASES combinations of Irradiation Load Values mean mean SD mean 3SD mean SD mean 3SD DATA Irradiation 4 65 KWh m2 day Load 7 04 kWh day RESULTS Total Cost NPC 28915 Lev cost of E 0 45 kWh Unmet load 0 Emissions 299 8 kgCO2 yr Renew Frac 98 4 Excess E 651 kWh yr Batteries lifetime 19 32 yr AC gen fuel 21 83 litre yr DATA Irradiation 4 65 kWh m2 day Load 7 34 kWh day RESULTS Total Cost NPC 30204 Lev cost of E 0 45 kWh Unmet load 0 Emissions 341 5 kgCO2 yr
102. anufacturing 55 SOC at the begining of simulation 100 Z of SOCmax OPZS Hawker TZS 24 de 3360 Ah 20 30 40 50 60 Depth Of Discharge 70 2050 2050 2050 2050 2050 2050 2050 2050 2050 1800 1800 1800 1800 1800 1800 1800 1800 1800 1 500 1 500 D 7 1600 1500 0 36 1600 1500 0 32 1600 1500 042 1600 1500 0 36 1600 1500 0 36 1600 1500 031 1600 1500 0 39 1600 1500 0 39 kg CO2 equiv 4 kWh capacity Lifetime calculation using model Equivalent cycles 9 Rainflow cycle counting Modified R Dufo L pez Number of full equivalent cycles 1254 3 Annual Inflation Rate expected gt for Batteries Costs Max Variation of Wind Batteries expected e g for an expected 60 reduction on current Batteries cost introduce 60 The limit is reached in 45 4 years HOGA User Manual 102 3 10 4 Schiffer Model Only in PRO version If you choose the model Schiffer batteries defined in the table should be of the same family ie Should have similar parameters changing only the size If we chose the model Schiffer it appears under the coefficient of variation of voltage with temperature the Schiffer Bat Data button which when clicked shows the next window AE Aging batteries model data E de Aging batteries model shown in Schiffer et al 2007 B AAA Potential of reference electrode Hg Hg2504 0 653 Y Batteries data OPZS y all batterie
103. ar 4 44 MARCH Feb 4 44 Mar 4 34 Apr 4 24 May 3 64 Jun 3 44 Jul 3 74 Aug 3 54 Sep 3 44 Oct 3 84 Now 414 Dic 4 34 Nm N MH MH MH MH MH BM Mh MH Mh Velocidad mis 01234567 8 9 1011 12 13 14 15 16 17 18 19 20 21 22 23 24 Horas Form Factor b 2 Autocorrelation factor 0 82 Force O consecutive days with wind lt 3 m sin month January Y Av sp year m s Ew dl Visualize montlhy wind speed night speed ampltude Calm is considered s Scaled Average Speed m s Sraa kT 396 Form factor of the wind speed serial 2 1 lt 3 m s A description is provided below for the parameters mentioned above 29 Form Factor Variations in wind speeds for a given site are usually described using Weibull s probability function This function is in turn determined by its mean using also the scale factor and by R Dufo L pez HOGA User Manual 74 1ts Form Factor Once the average speed 1s known for a site the probability distribution may be deduced for different wind speeds using the value of this Form Factor The figure below displays the probability density function f for a site with an average windspeed of 5 m s and a Form Factor b of 2 The dashed line corresponds to the distributions for the same average speed but with Form Factors of 1 5 and 2 5 Hence lower b values correspond to wider distributions as shown below wind speed ms Autocorrelation Factor
104. ate all combinations or genetic algorithms for both the main algorithm combination of components and the secondary algorithm control strategy and the calculation time used in each case In this case it is selected enumerative method for the combination of components and also for the control strategy there is only one combination as in this case the control strategy will not be optimized as the time expected is 9 seconds lower than 1 minute If the time allowed by us is lower than the time needed for the enumerative method IHOGA will use the genetic algorihtms to optimize the system in the time allowed However 1f the time allowed is so low that it is not enough to ensure a minimum probability of obtaining the optimial solution by mans of the genetic algorithms IHOGA will take the minimum time that it considers correct to run the genetic algorithsm as by default the checkbox Minimum time for the genetic algorithms E E is selected If this checkbox is not selected the time R Dufo L pez HOGA User Manual 34 allowed will always be the time used by IHOGA even if this time is not enough to ensure a minimum probability of obtaining a good result NUMBER OF CASES AND TIME EXPECTED Computation speed 52 7 cases second EVAL ALL POP ALL GEN ALG ALL MAIN ALG COMB COMPONENTS 468 16 3 4188 224 47 8632 12458 SEC ALG COMB STRATEGIES 1 7 700 95 95005 MAIN ALG SEC ALG NUMBER OF
105. ated as follows if not taken into account the effect of ambient temperature P Pn G Npanels_serial Npanels_parallel LF Where Pn is the nominal power peak power Wp of the PV panels A box appears to consider the effect of temperature as in this case the power depends on the ambient temperature Calculation of number of panels in series taking into account the maximum power voltage instead of the nominal voltage of the PV panels In small PV systems with storage batteries the number of panels required is calculated according VbusDC Vn_panel where VbusDC is the rated voltage DC fixed by batteries R Dufo L pez HOGA User Manual 86 and Vn_panel is the PV panel rated voltage typically 12 or 24 V In systems with high power which include DC DC conversion and MPPT grid connected systems normally the number of PV panels in series is calculated as VbusDC Vmax_p_panel where Vmax_p_panel is the voltage of maximum power of the PV panel In this case you must check the Calculate the number of panels shown in the figure below and indicate the value of Vmax_p_panel Vn panel so that 1HOGA will know the value of Vmax_p_panel from Vn_panel Normally for PV panels rated voltage 12 V the voltage of maximum power is about 17 or 18 V For example if 17 7 V the ratio will be 17 7 12 1 475 this value that must be introduced Masinum Power Pont Tracking MPPT M Calculate number of PY panels in sereal a
106. ault databases and default data are not altered However the next time you create a new project 1t will ask 1f you want to change the default currency If we click OK the new currency will be the default in 1HOGA and economic values used by default and cost data of the databases are multiplied by the factor that we have set as an equivalence between currencies The next time that we create a new project or open an existing project the program will no longer ask for the exchange However in each project you can define a currency different than the default currency Create a new Project When New Project 1s selected a name and path will be required to save the new project R Dufo L pez HOGA User Manual 27 New project Guardar en CO Proyectos r C Estrat Multiob 5 GeneracionH Documentos Pueblo recientes 5 p diesel a 4 Estrat Multiob 8 GeneracionHe Escritorio 8 Pueblo E py diesel Miz documentos Mi PC Mis sitios dered Nombre My project Tipo HOGA project hoga Lancelar After clicking on Save the application creates a file with the name chosen by the user and the hoga extension as well as a folder with the same name as the project file The folder contains the tables and files needed to run the project N B Please ensure to select a full access path to every project file with less than 55 characters In case a longer path is provided
107. ax charge batt PY panels Electrolyzer E H2 tank HH H2 Fuel Cell E to supply FC E max FC E Bought to AC grid E sold to AC grid Plimit Charge P2 E P1 P critical Gen P critical FC Pmin Gen Prin FC H2 TANK setpoint HHY H2 BATTERIES ENERGY Wh Y SOC 4 SOC limits Cap Max SOC setpoint Gen SOC setpoint FC SOC 0 1 T full charge Back Save Simulation Data Save Prob Data Excess Energy COMPONENTS PY generator 1350 Wp slope 60 Wind turbines group DC 546 w Batteries bank 9360 Wh Inverter 500 VA ESTRATEGY LOAD FOLLOWING SOC min 20 Months when it is not supplied the whole load by the standalone system January February March May June July November December a when it is not supplied tha whole load bv the standalone svstem 4 1 5 1 6 1 7 1 8 1 9 1 1041 1141 1271 1371 1471 1541 1641 1771 1871 2041 2171 22 1 an rad 4 m l By clicking the SOC 0 1 button the following screen appears which displays the status of battery charge for 30 days this simulation corresponds to a system different from the simulation shown before BATTERIES ENERGY wh SOC SOC limits Cap Max C SOC setpoint Gen SOC setpoint FC SOL 0 1 T full charge At the bottom it shows the number of cycles of each interval of depth of discharge DOD throughout the entire year R Dufo L pez HOGA User Manual 152 MK Graph E i E
108. bility pr E 2 a o Average Irrad kWh m2 day Hourly variability in the series O Hourly variability in the series O Analyze variability of wind speed Analyze variability of water flow WIND SPEED AVERAGE VALUE Mean 3 32 m s a co Standard Deviation 0 5 m s Mean 3 375 Std Dev 0 209 m s Probability ona wei rin Maximum 3 87 Min 2 94 m s a 4 z Average Wind speed m s Hourly variability in the series O Each of the N time series load irradiation wind and water flow 1f any 1s generated randomly by the average value obtained by following the Gaussian distribution multiplying that value by the time values 8760 h of each original series obtained on their screens and R Dufo L pez HOGA User Manual 132 dividing by the original average value That is each time series 1s proportional to the original During optimization each combination of components and control strategies is simulated N times Each of these simulations includes a random series of load consumption following its mean and standard deviation a random series of irradiation in case there are panels following its mean and standard deviation a random series of wind in the case there are wind turbines and following its mean and standard deviation and a random water flow in case there can be hydro turbine and following its mean and standard deviation Each of these N simulations gives results of
109. by 365 Nominal capacity of the battery bank Ah lt CR times the shortcut current of the PV array current from Wind Turbines group at 14 m s A so that the batteries can be charged properly by the photovoltaic generator and the wind turbines If this inequality combination fails the R Dufo L pez HOGA User Manual 33 combination of components and control strategy it is discarded This restriction is only taken into account if there is present in the system a PV generator and a batteries bank Minimum renewable Fraction Minimum percentage of load to be covered by renewable If a combination does not fulfill this fraction 1s discarded Levelized Cost of Energy kWh Maximum allowed for the kWh price If a combination does not comply with this maximum value is discarded SELECTION OF THE PARAMETERS OF THE OPTIMIZATION The parameters of the optimization can be selected by 1HOGA default or by the USER DPTIML S TI0N PARAMETERS SELECTED Er o HOGA USER Maximum execution time T h 15 min Display Parameters v Minimum time for the genetic algorithms If the parameters are selected by 1HOGA the user must decide the maximum time to execute the optimization default 15 min If we change the value of the maximum execution time to 1 minute the next screen appears where we are informed about the computation speed and about the selection of the optimization parameters enumerative method evalu
110. call Paischarse will be supplied by the batteries the AC generator or the fuel cell This process will be called DISCHARGE IHOGA will determine the cost of energy supply for each element the batteries the AC generator or the fuel cell This cost depends on replacements useful lifespans fuel prices as for the AC generator etc The figure below shows an example of costs associated to energy supply for different elements as a function of power R Dufo L pez HOGA User Manual 200 Cost P1 1 Pl gen P2 Paischarge Costs of supplying energy DISCHARGE process In the example provided by the figure above the optimum discharge strategy will be as follows For Paischarge lt P1 it will be best to supply energy with the batteries Should these not have enough capacity for all of Paischarge the rest Prack Paischarse Poat Will be supplied by the AC generator provided Pjck lt P2 Otherwise energy will be supplied by the fuel cell For P2 gt Paischarse gt P1 energy should be supplied from the generator Should this not have enough capacity for all of Puischarge the rest Pick Paischaree Peen Will be supplied by the batteries provided Pick lt Plcey Otherwise energy will be supplied by the fuel cell For Paischarse gt P2 it will be best to supply energy from the fuel cell Should the cell not have enough capacity for all of Paischarge the rest Prack Paischaree Pcen will be provided b
111. calm winds 12 35 hours 1 5 consecutive days AUGUST 438 hours of calm winds during the whole month 582 of time 18 2 days Maximum number of consecutive hours with calm winds le 71 hours 3 consecutive days SEPTEMBER 448 hours of calm winds during the whole month 52 of time 18 7 days Masimum number of consecutive hours with calm winds is 54 hours 2 2 consecutive days OCTOBER 412 hours of calm winds during the whole month 55 of time 17 2 days Maximum number of consecutive hours with calm winds Iz 38 hours 1 6 consecutive days NOVEMBER 321 hours of calm winds during the whole month 44 of time 13 4 days Maximum number of consecutive hours with calm winds iz 40 hours 1 7 consecutive days DECEMBER 282 hours of calm winds during the whole month 34 of time 11 7 days Haxirnum number of consecutive Hours with calm winds iz 34 hours 1 4 consecutive days Into Into Into Into Into Into More info can be seen clicking the button Info for each month Click on OK to return to the main screen R Dufo L pez HOGA User Manual 78 3 5 Hydraulic Resources The Hydraulic Resources screen may be accessed by clicking on Hydro Resources area or selecting Hydro in the Data menu HE HYDRO n EE Head vertical change in elevation between the head water level and the balwater level H m Losses in power canal and draft tube 2 m Avallable head H H
112. can pass from one to the other boxes using the arrow keys on the computer keyboard We can also move through the ranks with the table browser This browser can also add or delete rows Also when we edit any box changing its value we can click on it twice so the number moves to the left side of the box and appears with a blue background or by clicking on Bi x l When a cell is being edited the components lv x are enabled in the browser The first serves to validate while the second 1s used to cancel editing and restore the previous value If we do not press anything when we finish editing it is automatically validated Components PV panels Wind Turbines and Batteries should be arranged by families because in this way then you can import entire families when you define the components used in the optimization For 1HOGA to understand that a component belongs to a family first should be the name of the family then and then after a space the name of the component For example the panels SiM12 Atersa A10J and SiM12 Atersa A20J are two panels of the same family SiM12 Atersa SiM Sterza 4101 12 0 68 10 bd SIM Sterza 420 12 1 32 20 103 For each table costs of all components of the table can be multiplied by a factor defined 1f pressing button Multiply costs of by factor Multiply costs of PY Panels and O amp M by factor 1 Components used in the component
113. ch component PRE SIZING button helps you to choose the maximum number of components in parallel 4 After I select a certain component how can I enable the option to include exclude the component in from the system Insert an additional row into the component table Assign zero value to power cost and operating and maintenance costs This allows the hybrid system to use or not the component R Dufo L pez HOGA User Manual 183 since this has O power and O cost 5 When saving or opening a project the following error message is displayed File name is too long for a Paradox version 5 0 table The Paradox tables used by HOGA accept a maximum number of 70 for the characters to be used on the access path defined by the user 15 characters are used at least by several combinations of table directories and table names so the maximum number of characters for any project directory and folder should be limited to 55 As an example for a project saved with the name Test in My Documents the access path would be C Documents and Settings Rodolfo My Documents Test with 55 characters Any longer names for the project would result in problems It is recommended that all projects be saved to the root directory rather than to the My Documents folder 6 Where can I get data on wind speed Hourly wind data are not free of charge but may be downloaded from the Instituto Nacional de Meteorologia National Weat
114. cnccccnccicicinonsss 135 4 1 Mono Objective Optimization cccccccccnnnncncnnnnnnnnnnnancnnnnnnnnnonnnnnnnnnnnnnnnnnnnnannnnnnnnnnos 137 4 2 Multi Objective Optimization cccccccccccssssssececceceeaeesseeecccceesaeeeseeececeeeeaaas 141 4 3 Optimizing with No Genetic Algorithms Enumerative Method 143 AA RESULTA Dl cana estr ico 146 4 4 1 System Simulation Screen ooooonccnnnccccnnonooncnnnnnnnnnnnnonnnnnnnnnnonnnnancnnnnnnnnnnnnnnos 148 4 4 2 Simulation in case of probability analysis Only in PRO version ee 160 4 4 3 Simulation if the batteries model is Schiffer Only in PRO and version 163 4 4 4 Modifying Values in the Results Table oooonccccncccononoccccnnnnnnnnnnnnos 169 A O IO OE PO II RR 169 RN OS A oO Un 172 dO ZOO MMM ON MAS tad alicia aaa nano 176 A ASIAN ANA OO per ias ear seo E E I AE E 177 4 7 Summary of the sensitivity analysis cccccccssssssssssscccccsssssssssscccccsssessssssscccssees 180 5 REQUENTLY ASKED QUESTIONS inssssscscsinsedeseasevessssiacennswantevecssvsscnstactssosscuense 182 REFERENCES asian dc ca a ii a as 188 ANNEX 1 Genetic Algorithms ssssssseeeccccscsssccceoccssssececcccsssssccccecssssssececocssssssseceesso 192 Main algorithm optimization of components occcoooccncccnnnncnnnnnnnnnonanenonnnonananannnos 194 Secondary algorithm optimization of control Strategy oooooooonncnnnnnnnnnnnnnnnnnnnos 196 ANNEX 2 Control EE AUC
115. connect 450 Equalization Charging voltage Equalization duration 2 Equalization activated If SOC 40 Use az Low SOC for Disconnect the value of SOC min used Equalization activated if no equalization in the optimization and use as Los SOC for Reconnect same nor boost charge during 30 days SOC minplusa 10 2 Temperature compensation only for Copetti model 5 roy Pl IF there ig an AC Generator every 14 daps or 8 equivalent full cycles generator charges batteries atleast up to 95 OK At the bottom we should indicate the characteristics of the control of charging and discharging the batteries if the charge regulator and the rectifier are PWM or ON OFF the two devices charge regulator and rectifier are supposed to perform same control After choosing the type of control PWM or ON OFF we must select the controller parameters those of the manufacturer of regulators or rectifiers that we will use they have to be suitable for the batteries that we will use In the case of PWM control we must enter data of charge in several stages typically three R Dufo Lopez HOGA User Manual 100 stages bulk absorption and flotation and also data for equalization charge If the model is Copetti also we must indicate the coefficient of variation of the voltage with temperature mV C Controller to switch Diesel genset to charge batteries If there 1s a controller charge discharge batteries controller that can automatic
116. ctive including Human Development Index HDI and creating jobs these two objectives are maximization PVPANELS ES BATTERIES BANK Charge Reg H2 TANK n 2 FUEL oad CELL WIND TURBINES HYDRO TURBINE AC load AC GENERATOR Elements for a generic case R Dufo L pez HOGA User Manual 9 The PV generator can be connected to DC bus default or to AC bus including an invertir Also wind turbines can be defined as connected to DC or AC bus Fuel cell and electrolyzer also can be in DC bus default or AC bus with inverter and rectifier For example in next figure all components are in AC bus The hybrid system may comprise the following elements photovoltaic PV panels wind turbines hydraulic turbines fuel cells Hz tanks and electrolyzers as well as batteries battery charge regulators inverters DC AC converter rectifiers AC DC converter and AC generators these will be a non renewable source for non renewable fuels but it can be a renewable source if the fuel is biogas or another renewable fuel All elements may be present simultaneously and the user may decide to include only some of them as part of the desired hybrid system Different system loads are possible e Electric AC loads electric devices using AC electric energy e Electric DC loads electric devices using DC electric energy e Hydrogen loads production of H2 for external consumption e g el
117. d However you can choose up to 4 cases of Net Mettering Net Mettering Energy Annual Net Mettering Energy Monthly Net Metterng Energy Annual Net Metternng Energy Monthly o Met Metternng Cost Annual Net Mettering Cost Annual Net Mettering Cost Monthly R Dufo L pez HOGA User Manual 57 Net Mettering Cost Monthly Energy Annual option means that the energy bought to the AC grid during the year must be higher or equal to the energy sold to the AC grid It is mandatory in some countries in the case of net metering For Energy Monthly the energetic net mettering must be monthly The two last cases correspond to cases where the net mettering is economic not energetic The cost of energy bought to the AC grid during the year or the month must be higher or equal to the cost of energy sold to the AC grid during the same period If on the panel of hourly prices we have defined various No Net Meltering Met Metternng Energy Annual selected same cases as shown before but PERIODS Net Mettering Energy Monthly Met Mettenng Cost Annual Met Metternng Cost Monthly added This cases are same as the 4 cases explained Net Metering E Armual PERIODS Met Metternng E Monthly PERIODS Net Metternng C Annual PERIODS Net Mettenng C Monthly PERIODS hourly periods there are 4 additional cases which can be before but the net mettering is applied for each hourly
118. d Hydro and Components as well as for Pre sizing Calculate and Report for the Y INVERTERS menus are enabled for components already selected see section 3 1 3 above on Selecting Components Y CHARGE BAT DC Voltage 24 Y AC Voltage 230 Y PRE SIZING Energy Storage 4 days range Max bat parallel gt Cn min Max PY pan parallel gt P min ag f Or buttons Max wind t parallel gt P min Once a screen has been accepted a validation sign is shown for buttons and submenus HDland JOBS Sensitibity Analysis a for submenus Probability Analysis CALCULATE Ej REPORT R Dufo L pez HOGA User Manual 44 After all the required screens are accepted for all components selected the Project C HO a Data Calcu LA New 8 Open E Save Ctri G The options available under the Project menu are Create New Project E Save as By ext Open Project Save Current Project shortcut Ctrl S Save As alternative Calculate button and menu are enabled Once the system is calculated the Report button and menu are enabled report for the best solution name for current project and Exit Please ensure that a backup copy for any project to be modified is available before changes are applied Note that the tables containing the values for system components and results are modified as soon as changes are applied to any project
119. d for R Dufo L pez HOGA User Manual 51 loads defined previously and known or estimated hourly values for a full year 365 24 8 760 hours for AC DC and H2 Click on Import to open the text file The format of the file must meet certain requirements hourly consumption values in watts for AC and DC and kg for H2 must be sorted in rows with a total of 8 760 3 26 280 rows The first 8 760 rows in watts will correspond to the AC consumption for each hour sorted by date e g with the value for January 1 on the first row the value for January 2 on the second row and so on The next 8 760 rows in watts will correspond to hourly DC consumption with the last 8 760 rows relating to hourly Hz consumption in kg P consumo txt Bloc de notas Ancho Eddc n Formato Ver Ayuda Boo 0000 606 0000 600 0000 0 1200 o January 1st 1000 0000 1000 0000 500 0000 500 0000 600 0000 500 0000 500 0000 600 0000 600 0000 1200 0000 January 2nd 1200 0000 PURCHASE SELL ENERGY tab In this tab options of purchasing or selling electricity to the AC grid must be entered Also 1f there 1s Electrolyzer in the system and H2 is produced we can sell surplus H2 in tank difference between H2 in tank at the end of the year and at the beginning Data to compare with electrical supply only from AC conventional grid must also be entered R Dufo L pez HOGA User Manual 52 AC
120. d for Output Power as a function of wind speed from 1 up to 26 m s 1 e the output power curve as shown in the chart below For DC wind turbines R Dufo L pez HOGA User Manual 90 with a DC voltage different from the voltage for the system s DC bus losses must be accounted for at the DC DC converter which connects the wind turbine to the DC bus DC turbines will be connected to the DC bus and AC wind turbines will be connected to the AC bus The default screen shows a wind turbine connected to the DC bus This may obviously be changed Wind turbines connected to bus We can define for each turbine which bus is connected to default option or we can force all turbines considered in the system to be at DC bus or at AC bus Wind Turbines connected to bus o Defined in Type llta DC bus All to AC bus Add or remove wind turbines We can add or remove turbines as shown for photovoltaic panels in previous section We can also add individual turbines from the database or entire families Roughness Surface roughness class and height above sea level must be selected Use the pop up menu on the left to select the type of ground rugosity Class 0 by default HOGA will then automatically display the corresponding length m and a description of the class Height above sea level In the bottom left area we put the altitude above sea level of the geographic location and the program gives information under
121. day Wind m s W_flow l s Load kWh day C total NPV S Energy_cost kWh Emission kgCO2 539 525 4 45 3 32 3 7 34 32187 2 0 481 408 7 540 541 Values MINIMUM MAXIMUM AVERAGE and STD DEV of each result obtained in the 500 series 542 VALUE Rad kWh m2 day Wind m s W flow I s Load kWh day C total NPV S Energy cost S kwh Emission kgCO2 543 MINIMUM 4 03 3 32 3 6 09 26845 8 0 417 231 2 544 MAXIMUM 5 19 3 32 3 7 99 37378 2 0 571 581 1 545 AVERAGE 4 67 3 32 3 7 03 29215 5 0 455 309 5 546 STD DEV 0 19 0 0 0 3 1598 2 0 017 52 9 Mm rm 3 xks TZ 0 I y ISTO R Dufo L pez HOGA User Manual 163 4 4 3 Simulation if the batteries model is Schiffer Only in PRO and In the case of using the battery model Schiffer the simulation is performed until the end of the lifespam of the batteries For example in the case of the figure below the batteries lifespam is 9 31 years Simulation of the first 10 years The first change of batteries is Year no 10 April 23 Batteries lifetime 9 31 years i 11 000 10000 E E S E 1 ON The following figure shows the simulation of the first 10 years 3649 days display You can see how 1n the year 10 on April 23 the maximum capacity of the battery brown curve has dropped to 80 of its nominal value 9360Wh 80 100 7494 Wh indicating that battery has exhausted its useful life and must be replaced This day the batteries are replaced Simulatio
122. duced for the different fields in every month which will be displayed in the chart Data is provided for Saragossa by default Pressing Metheorological data from NASA Web opens a web browser window that shows the monthly average data on the location that we will have indicated on top left by latitude northern hemisphere the southern hemisphere and longitude East West R Dufo L pez HOGA User Manual 63 8 NASA Surface meteorology and Solar Energy RETScreen Data Mozilla Firefo Archivo Editar Ver Historial Marcadores Herramientas Ayuda E EL PA S el peri dico global en espa ol Video Tutoriales C Builder 2010 eosweb larc nasa gov cgi bin sse retscreen cgi email rets 40nrcan gc ca8istep 1 amp lat 41 66 amp lon 0 86 amp submit Submit Pe Buscar 35 C Y m SSE ES Find A Different Location Accuracy Methodology Ey ATMOSPHERIC 4 SCIENCE NASA Surface meteorology and Solar Energy RETScreen Data 3 DATA CENTER Latitude 41 66 Longitude 0 86 was chosen Unit Climate data location 4 Latitude N 41 66 Longitude E 0 86 Elevation m 512 Heating design temperature 0 61 Cooling design temperature E 28 35 Earth temperature amplitude p 20 77 Frost days at site day 24 Daily solar s Month Air temperature aaa E radiation ne Wind speed e SET is humidity E pressure temperature degree days degree days horizontal C kWh m d kPa m s y E C d C d January 5 0 71 8 1 93
123. e Save As and choose file format xlsx then the next time you open the xlsx file Excel will not ask you any R Dufo L pez HOGA User Manual 175 question If the project type is Optimize strategy only fixed components instead of the report HOGA displays a circular chart where data of costs of the different system components throughout the system s lifespan is shown All data is referred to the initial time of investement NPC LIFETIME COSTS NPC DISTRIBUTION R Dufo L pez HOGA User Manual 176 4 5 Zooming on Charts The zooming option is available for graphical data on algorithm evolution Pareto representation simulation consumption and resources irradiation wind and hydro Draw a window with your mouse over the area to be enlarged click from top left to bottom right Mono obejctive optimization Total no of evaluated cases 92 Time 2 Slo ei ae ta o L 238 000 E ae i 236 000 a D E TE E 234 000 A LU Li 232 000 a LE o o E 230 000 LU 228 000 226 000 1 6 1 65 a 1 75 1 5 1 05 1 3 1 95 2 2 05 ai ais 22 2 25 GENERATIONS Sketch w Chart To undo the zoom window click and drag from bottom right to top left R Dufo L pez HOGA User Manual 177 4 6 Sensitivity Analysis If performing a sensitivity analysis 1e if entered in the screen of the sensitivity analysis some cases 1HOGA will calculate each sensitivity analysis i
124. e o y a a Lol O es se SOC batteries Y y aki i AY Pen 0 85 0 8 0 75 0 7 9 0 6 1 2 3 4 85 6 TBE SUNRE HEK ETE Ae Beh SD AH ae eS January J 130 BACK Days displ Cycles 0 15 D0D 306 15 25 D0D 54 25 35 DO0D 9 35 45 D0D 10 45 55 D0D 2 55 65 D0D 1 65 75 D0D 1 75 85 D0D 1 85 100 D0D O By clicking the T full charge button the following screen is shown which displays 100 days It shows the number of days since the last full charge of the battery bank SOC gt 0 95 by default green curve and the number of complete cycles since then blue curve If there is an AC generator and the option 1s activated in the screen of the batteries when a number of days or full cycles without full charge have been passed the AC generator runs to charge batteries A e HK Graph e Days and full equivalent cycles since last full charge SOC gt 0 95 in order to start the generator January April 4 100 BACK Days displ Hourly Values Separately tab This tab shows the hourly values for the different energies of the system each in a different R Dufo L pez HOGA graphic User Manual 153 This example of simulation corresponds to a system different from the simulation shown before Hourly simulation Hourly values separately Monthly and annual Average Power Monthly values Annual values Hydrogen detailed A
125. e 24 V AC Voltage 230 V COMPONENTS 2 PV panels serial x 3 pan parallel 135 Wp Ptotal 0 81 kWp Slope 60 12 Batt serial x 1 bat par Cn 390 A h E total 9 3 kWh 1 7 d range 1 Wind Turbines DC of 546 8 W at 14m s Total 0 546 kW Without Hydro turbine AC Generator of rated power 1 9 kVA Without Fuel Cell Without electrolyzer Inverter 500 VA Battery charge regulator current 32 7 A Rectifier AC DC 493 W PV WIND GEN INV CONTROL STRATEGY LOAD FOLLOWING SOC min batteries 20 96 IF POWER DELIVERED BY RENEWABLE SOURCES IS HIGHER THAN LOAD CHARGE The Batteries are charged wth the spare power from renewable POTENCIA kW IF POWER DELIVERED BY RENEWABLE SOURCES IS LOWER THAN LOAD DISCHARGE The power not supplied to meet the load will be supplied by the Batteries if they cannot supply the whole the rest will be supplied by the AC Generator Pigen INF W There is no Fuel Cell AC Generator Minimum Power 570 W Whenev er the power to be supplied by the AC Generator is lower than Pcritical_gen 0 W the AC generator runs at full power or at a rate not exceeding the Extra Report in the case of probability analysis PRO version only If we performed the optimization with the option of probability analysis the results of the general report are the average values of the results average values of the results corresponding to the N series of simulations performed in the probability analysis When closi
126. e as Excel file once saved if you open the file with Microsoft Excel it reports a message you must answer Yes and It opens correctly In Microsoft Excel you should save the Excel file as xlsx format in Excel use Save As and choose file format xlsx then the next time you open the xlsx file Excel will not ask you any question R Dufo L pez HOGA User Manual 158 Inicio Insertar Dise o de p gina pra Datos Revisar Vista Acrobat O sx amp So Ex mm Autosuma sr B Calibri Tei ju 44 E Ajustar texto General o EH Ca BF a N X IE EE i Combi ntrar a Formato Darformato Estilos de er ne eo Ordenar Buscar y 5 s 2 a bad Combinar y centrar 3 e condicional comotablay celda lt 2 Borrar y filtrar seleccionar CAES E seamen _ El Portapapeles ls Alineaci n Estilos Celdas Modificar O heene O O O O O A B 6 Project 1 hdga Solution 0 um 2 EJ COMPONENTS PV generator 3240 Wp slope 602 Wind turbines group DC 546 W AC Generator 1900 VA Batteries bank 9360 Wh Inverter 500 VA Rectifier AC DC 496 W _4 ESTRATEGY LOAD FOLLOWING Pigen INF W Pmin_gen 570 W SOC stp_gen 20 SOC min 20 5 6 ENERGY HOURLY VALUES All hourly values of energy are expressed in Wh H2 Load in HHV of H2 Fuel consumption of AC Generator Fuel Gen is expressed in litre Prices of selling and purchasing E fo _7 Cost
127. e fuel cell the electrolyzer and the inverter in order to minimize total system costs These are calculated for the total system lifespan and updated with respect to the initial time i e to the Net Present Cost NPC for In most cases where optimization is applied through 1HOGA cash flows are usually expenses only purchasing replacement maintenance and fuel costs etc with no income The different costs throughout the whole of the study period are referred to the initial time of the investment using the discount rate approx interest rate minus inflation rate thereby producing the NPC The lower the NPC value the better the investment It is possible to use the option in 1HOGA to sell surplus hydrogen and electric energy to the AC grid it is also possible to purchase energy from the grid to compensate for unmet load by the hybrid system In those cases sales are accounted for within iHOGA as negative values since they must be subtracted from component replacement and maintenance expenses We may thus achieve an income from energy sales which is higher than system costs resulting in a negative value for NPC This means that our facility will achieve a net benefit positive values meant expenses i e costs A larger negative value for our NPC will indicate a R Dufo L pez HOGA User Manual 193 the system in mono objective optimization for multi objective optimization 7 8 9 HOGA will seek so
128. e it you will have received it by e mail in the text field and press OK button A start screen appears indicating the user program and the duration of the license You must have an R Dufo L pez HOGA User Manual 24 internet connection otherwise you can not activate the software HE ACTIVACI N LICENCIA bv bv cad el E Es Clave de acivaci rn Warning All versions need internet connection to verify that the license is active If no connection is available will not work AA ee o A Project Data Calculate DataBase Report Help HOGA v 2 0 PRO improved Hybrid Optimization by Genetic Algorithms Software for the optimizacion of hybrid renewable systems by means of genetic algorithms Authorized user Fito Licence expires end of January 2014 oOo HOGA will not ask for any key data the next time you open or create a new project R Dufo L pez HOGA User Manual 25 Change the default currency which will be used by HOGA The first time you create a new project menu Project gt New 1HOGA asks if you want to change the default currency 1 e if you want to use as default a currency different from Euro Do you want to use as default currency in IHOGA a currency different from EURO E If you want a default currency different from EURO press OR If you want to keep EURO as default currency press Cancel Cancel LHOGA will
129. e loan to finance the investment By default 80 of the total initial investment cost 1s financed by loan value that the user can change Indicate the loan interest and number of years to return The loan must be on constant quota French system every year to pay the same amount 3 1 5 RESULTS CHART tab In this tab once the system is calculated we see the graph representing graphically the total R Dufo L pez HOGA User Manual 43 cost NPV of the different solutions as well as CO2 emissions In the case of multi objective it represent two objectives one in X axis and the another one in Y axis 3 1 6 System Voltage System DC and AC voltage may be introduced on the main screen bottom left DC Voltage 4 W AC voltage 230 Y If the system voltage is modified after all components have been accepted an additional screen 1s shown to ensure that the components selected may operate with the new voltage level 3 1 7 Buttons and Menus on the Main Screen K Prosser Several menus are available on the main screen top left Project Data Project Data Calculate Data ton acer Calculate Database Report and Help RESOURCES Y SOLAR A number of buttons is available left for Load AC grid loads and options Ho COMPONENTS Y PV PANELS ino ture mov best solution once this has been calculated Only relevant buttons and to buy and sell energy to AC grid Resources Irradiation Win
130. e parameters required by the KiBaM Model as calculated from C100 C20 and C10 Kinetic Model Manwell McGowan 1993 24 The required parameters are represented by c k and Qmax R Dufo L pez HOGA Add Battery Zero Add Batteries family OP2ZS Hawker Acq C nom Yn Cost PPZS HawkerTVS 390 PPZS HawkerTVS 550 DPZS HawkerTYS 816 PZS Hawker TYS 1 1340 PZS Hawker TZ5 1 1940 PZS Hawker TZ5 1 2240 PZS Hawker TZ5 2 2800 PZS HawkerTZS 2 3090 DiPZS Hawker TZ5 2 164 9 202 298 412 578 664 800 308 1010 Fixed Operation and Maintenance Cost 50 Batteries Model Ah Schuhmacher 1993 KiBaM Manwell McGowan 1993 Copetti 1994 Schiffer 2007 C O amp M SOC Self 1 65 2 02 2 98 412 5 78 6 64 8 9 08 10 1 yr 7 KiBaM Model Data 9 Calculate Temp J 18 F18 M20 A 20 M22 J 22 Bat Gc J22 A422 20 020 N18 D18 Except Schiffer model consider Tmean gt T flotat life Mean C 20 User Manual Global min disch Imax Effic 163 2 85 268 388 448 560 672 Cycles to failure 85 85 85 85 85 85 E TZS 24 de 2 Ah Float life at 20 Co 12000 12000 12000 12000 12000 12000 12000 12000 12000 Equivalent CO2 emissions manufacturing 55 6500 6500 6500 6500 6500 6500 6500 6500 6500 4250 4250 4250 4250 4250 4250 4250 4250 4250 3100 3100 3100 3100
131. e suitable for the VDC of the system and which include or not MPPT depending on the PV charge controllers include MPPT checkbox below the table if it is or is not checked R Dufo L pez HOGA User Manual 110 1 PV BATTERY CHARGE CONTROLLERS AND BATTERY CHARGER du us mae a Sta PY BATTERY CHARGE CONTROLLER 48 Y Add from data base STECA PR 1010 v H 4 ml eo Include only DE suitable and MPPT as selected form family STECA v STECA TAROM 440 40 48 48 298 NO STECA P TAROM 4055 55 48 48 1500 NO 7 lreg max 4 STECA P TAROM 4140 149 48 48 2215 NO Acquisition cost E If the controller is included in the bi di inverter the controllers of this screen will not be considered and authomatically the cost of the controller will be considered 0 Lifetime 10 years Control data PY charge controllers include MPPT All the PY charge controllers muts be of the same family same control data RECTIFIER BATTERY CHARGER CONY AC DC 230 Vac 48 Vdc Acquisition cost E 100 200 Prom kw If battery charger is included in inverter this cost will authomatically be 0 if the battery charger is included in the AC i Lifetime 10 AER Efficiency 90 z generator you must indicate here O for costs Ok In PRO version if we click Control Data button a window appears where we should indicate the characteristics of the control of charging a
132. ecause the previous results will be lost Confirm uo l Do you want to re calculate Prewious results will be lost R Dufo L pez HOGA User Manual 136 Please note that clicking on the OK button the new results shall overwrite any existing results from previous calculations The existing tables will be modified and changes may not be rolled back even clicking on the Cancel button Therefore before you recalculate if you want to save previous results use File gt Save As and you will save the project as another project for any results that need to be safely stored for reference or later use After clicking on OK a panel will be displayed bottom of the screen with a progress bar indicating the time left to conclude the calculation Additional information is provided on the number of cases evaluated the total estimated calculation time and the time elapsed since the Calculate button was pressed y CANCEL Cases evaluated 94 of 312 S04 Elapsed time 2 Remaining time Oh 015 Press CANCEL to stop the simulation The calculation will be stopped and no option will be available to resume At the end of the optimization the system layout is replaced by a table where all the results of the optimization process will be displayed For mono objective optimization a row 1s displayed for the best solution within each generation or if all the combinations are evaluat
133. ected to the AC bus This may obviously be changed Data for the calculation of life cycle emissions must be set equivalent CO2 emissions in the manufacturing of the hydraulic turbine generator auxiliary components kg CO2 per kWh of energy produced by the generator R Dufo Lopez HOGA User Manual 96 3 10 Batteries accumulators The Batteries screen may be accessed by clicking on Batteries Components area or selecting Batteries in the Data menu GY BATTERIES um Ernim Add Battery Zero Add Batteries family OPZS Hawker Float life ee Global at20 C Cycles to Failure vs Depth of Discharge a C nom Yn Cost unit min disch Imax Effic OPZS Hawker TWS 7 550 12000 31 00 2500 2050 1800 1600 OPZS Hawker TYS 816 12000 3100 2500 2050 1800 1600 OPZS Hawker TYS 12 1340 A 12000 3100 2500 2050 1800 1600 a OPZS Hawker T25 13 1940 y 12000 3100 2500 2050 1800 1600 OPZS Hawker T25 16 2240 12000 3100 2500 2050 1800 1600 A OPZS Hawker T25 20 2800 12000 3100 2500 2050 1800 1600 A OPZ5 Hawker TZ5 22 3090 f 12000 3100 2500 2050 1800 1600 D OPZS HawkerTZS 24 3360 p 12000 3100 2500 2050 1800 1600 Fixed Operation and Maintenance Cost 50 Equivalent CO2 emissions manufacturing 55 kg C02 equiv kWh capacity Batteries Model SOC at the begining of simulation 100 Z of SOCmax Ah Schuhmacher 1993 OPZS Hawker TZS 24 de 3360 Ah KiBaM Manwell McGowan 1993 Copetti 199
134. ectricity powered fuel cell vehicles Only in PRO and EDU versions e Water pumping load The programme allows for selling AC electric energy to the grid surplus unused energy purchasing AC electric energy to the grid unmet load by the standalone system or selling R Dufo L pez HOGA User Manual 10 surplus hydrogen produced in the electrolyzer and stored in the tank Simulations are also possible for feasibility studies of zero consumption renewable energy facilities connected to the grid The sale to the AC grid can be of any excess energy or not exceeding the energy purchased annually or monthly Net Mettering of energy annual or monthly with or without hourly periods You can also define the Net Mettering economical 1e to take into account instead of the energy balance the economic balance Net Mettering only in PRO and EDU versions Optimization is available through the programme both for all different element combinations as well as for system control strategies e g when energy must be supplied by different elements maximum charge level for the batteries An optimized design and control of hybrid systems may often reduce the production cost per kWh as compared with generating facilities where only one energy source is used Furthermore photovoltaic or wind powered facilities regardless of their design may well be under the safety margin that ensures a minimum level of electricity supply thr
135. ed they are sorted from best to worst at the end of the optimization whereas for multi objective optimization only non dominated or all solutions within each generation will be included in the table After the first generation 1s completed a chart 1s displayed at the top with the evolution of data through different generations mono objective or the Pareto diagram for the last generation evaluated multi objective In the chart it is shown th evolution over the generations in the case of mono objective optimization or Pareto diagram of the last generation performed in the case multi objective optimization If all combinations are evaluated enumerative method the table and graph are shown only at the end of the calculation with the combinations sorted from best to worst R Dufo L pez HOGA User Manual 137 4 1 Mono Objective Optimization An example is illustrated by the figure below for Mono Objective Optimization The example can include PV panels batteries auxiliary equipment an inverter and an AC generator In this case the calculation time set in main screen General data tab see section 3 1 3 is not enough to evaluate all combinations of the components so the genetic algorithms will be used for the components optimization af the evaluation time were enough to evaluate all see section 4 5 For example in this case 1 minute has been indicated as maximum execution time and the software must use genetic algori
136. ed consumption may be introduced on the Consumption screen This is available by clicking on the Load button or selecting Load within the Data menu The default load corresponds to the average monthly values for an AC low load house ME Load and Selling Purchasing Energy El Data source o Monthly Average Load Profile Import hourly data file data in w and kg Import Export AC LOAD W DC LOAD W H2LOAD kg WATER m3 day FROM WATER TANK PREVIOUSLY PUMPED PURCHASE SELL ENERGY Month Oih 12h 23h 34h 45h 56h Em 7en es sion 10119 11 12 1213h 13 140 14 15h 15 161 M Scale factor for Monday Friday 1 Scale factor for the weekend 1 AVERAGE LOAD IN DECEMBER MIA H2 en PCS 3 AC load power factor cos fi 1 AC max load in the year Active 308 W Aparent 308 VA ES Draw AC average load Active 151 24 W Aparent 151 24 VA DC max load in the year 0 DC average load O w Average daily load 3 63 kwh day Average hourly value of Energy DC hourly Eneragy Total hourly DC Factor 0 N B All data on demand levels must be referred to OFFICIAL times NOT SOLAR TIMES FROM PREVIOUS VERSIONS In many European countries official summer time is 2 hours ahead of solar time whilst official winter time is I hour ahead 3 options are available for introduction of data sources on load MONTHLY AVERAGE LOAD PROFILE
137. een and components hydrogen fuel cell and electrolyzer hydrogen tank 30 of the fixed on their screens R Dufo Lopez HOGA User Manual 3 18 Probability Analysis Only in PRO version 130 Once the data of resources and components have been set you can access the data for the study of probability analysis using the Probability Analysis WK Probabilistic analysis of variability of load irradiation wind speed and or water flow o DO NOT PERFORM PROBABILITY ANALYSIS O PERFORM PROBABILITY ANALYSIS By default there is no probability analysis To do this you must click on PERFORM PROBABILITY ANALYSIS appearing the following screen EA Probabilistic analysis of variability of load irradiation wind speed and or water flow DO NOT PERFORM PROBABILITY ANALYSIS o PERFORM PROBABILITY ANALYSIS Number of series to analyze each combination of components and control strategy 500 Y Analyze variability of load V Analyze variability of irradiation DAILY LOAD AVERAGE VALUE IRRADIATION AVERAGE VALUE Mean 3 63 kwh day Mean 4 65 kiwh m2 day Standard Deviation 0 3 kwh day Mean 3 636 Std Dev 0 305 kWh day Probability TRE gt Average Load kWh da Aer a s Hourly variability in the series O a y Hourly variability in the series 9 Y Analyze variability of wind speed Analyze variability of water flow WIND SPEED AVERAGE VALUE Mean 3 32 m s Standard Deviation 0 5 m s
138. ents Data Base it shows the data bases for the different components 1n tables x Databases of components e 9 a ho e PY Panels Wind Turbines Batteries AC Generators Inverters Hydro Turbines Electrolyzers Fuel Cells His t a Name Nom Voltage shortcut 4 P nominal Wp Acq Cost Temp Coef 2C Emisions kgCO02 k4p 2 0 0 0 1 0 1 SimM1Z Atersa A10 0 68 0 45 SiM12 Atersa 420 1 32 0 45 SiP12 Atersa ABBP 4 06 0 43 SiP12 Atersa A95P 5 51 0 43 SiP12 Atersa A135P 8 23 0 43 SiP24 Atersa A180P 5 4 SiP24 Atersa A2B0P E Sik412 Isofoton 1s10 0 82 _ SiM12 Isofoton 1s22 1 64 SiM12 Isofoton 1s60 3 73 _ SiM24 Isofoton 1s150 SiP12 Suntech STP SiP12 Suntech ST 1 SiP12 TAV PY 135 SiP24 Schott Mono1 DI SiP24 Schott 451100 Multiply costs of PY Panels and O amp M by factor 1 800 800 600 800 800 Add components from the project PY Panels table There are 8 tabs each tab includes a table for a component type panels wind turbines In each table there is a component Zero to take into account the absence of this component R Dufo L pez HOGA User Manual 8 1 You can edit add and remove components of the database using the browser buttons table at the top a a NR RN ca To access the table at a certain box of a panel click on 1t with your mouse Once inside the table we
139. er not only to meet the demand but also trying to charge the batteries to SOCsetpoint gen or SOCsetpoint_FC in the case of fuel cell If the option continue up to SOCstp is selected it will continue the next hours until SOCstp is reached R Dufo L pez HOGA User Manual 40 SOCstp_gen and SOCstp_FC by default are 95 However these variables can be optimized as well as other variables In case of optimizing these variables for example if the software in a particular case chooses Pcritical_gen 1000 W and SOCstp_gen 75 this means For each hour if the generator has to supply a power greater than O but less than 1000 W it will run at its rated power trying to charge batteries with surplus power to 75 of SOC try to reach this value of SOC only during that hour if the continue up to SOCstp is not selected while if this option is on the generator will run the following hours to reach 75 of SOC That is for that time the strategy will be cycle charging with or without continue up to SOCstp For each hour if the generator has to supply a power exceeding 1000 W it will run at a power strictly necessary to supply the demand without trying to charge the batteries That is for that hour the strategy will really be load following Try both If you select Try both the software will consider the two strategies However in this case Poritical gen and Peritica FC May not be optimized It i
140. erest rate I per year and overall inflation in the price of the components for when you have to replace them and costs of operation and maintenance g per year Sensitivity of the inflation rate of the fuel consumed by the AC generator Inf F x In the 5th tab we accede to cases of sensitivity analysis of inflation in the cost of fuel of the AC generator The base case Inf F 1 uses the values in the table of the generators of the window where they are defined not specified here as there may be several cases as there may be several generators that use different fuels diesel gasoline etc The cases we add we set a specific value in annual increase for different fuels all the same For example if 15 Inf F 2 means in this case all fuels increase their price by 15 every year Sensitivity of acquisition cost of the most relevant components Pr x In the 6th tab we accede to cases of sensitivity analysis of the acquisition price of photovoltaic panels wind turbines batteries and hydrogen components For each case of the sensitivity analysis we will set a scale factor for each type of component that will multiply the purchase price of each component acquisition cost at their screens For example in the case Pr 2 we can considered the costs of the PV panels to be the 50 of what R Dufo L pez HOGA User Manual 129 we have set on their screen the same in wind turbines batteries to 70 on the set on their scr
141. even when the modified project is not saved To save a project with a different name use the Save As button The tables mentioned above are shown in the figure below They include data for Load Wind PV panels Wind Turbines Hydraulic Turbines Batteries Inverters AC Generators H Fuel Cell and Electrolyzer and results once the system has been calculated AC LOAD W DC LOAD w H2 LOAD kg Monn Oth 12 23h 34h El 600 600 600 600 60 600 600 600 600 60 600 600 600 600 60 600 600 600 600 60 600 600 600 600 60 600 600 600 600 60 600 600 600 600 60 600 600 600 600 60 600 600 600 600 60 600 600 600 600 60 600 600 600 600 60 600 600 600 600 60 Details will be provided below for the screens on consumption resources and components The structure of the Component screens may vary depending on the type of optimization to be applied Optimization of Components and Strategy or Optimization of Strategy Only Fixed Components All details will relate to the first type full optimization For strategy only optimization the differences refer to the options available for the system components only the type may be selected as components are fixed and the number of components in parallel in terms of PV panels Wind Turbines and Batteries R Dufo L pez HOGA R Dufo L pez User Manual 45 HOGA User Manual 46 3 2 Expected Load The expect
142. f solution when all combinations have been evaluated correspond to Total Cost NPC in red Annual equivalent CO2 Emissions in green and Unmet Energy in blue Also in blue it is shown the unmet load in kWh year and in Days range for the average daily load of the year the value of the division between the rated capacity of the battery bank and shortcut current of the photovoltaic generator Cn Ah Isc Idc A the renewable fraction covering the demand and the levelized cost of energy of kWh k Wh On the right are the boxes SIMULATE REPORT and COSTS that when pierced you access the simulation screens report or costs screens Right there are also the results of human development index HDI and jobs created during the life of the system Also columns showing the characteristics of the system number of PV panels in parallel power of PV panels are shown Simulate Report__ Costs HDI ios NoPYpanpfP PV pan wp Slope 8 No Bat p Ch Bat 4h P Gen 4 P inv vA SIMULATE REPORT COSTS EEN 0 0547 ER E ET aL SIMULATE REPORT COSTS 0 5138 0 0608 io 135 350 1500 al SIMULATE REPORT COSTS 0 5130 0 0487 a 135 E0 1 330 1300 si SIMULATE REPORT COSTS 0 5138 0 0547 a 135 E0 1 465 1300 BL SIMULATE REPORT COSTS 0 5130 0 0607 10 135 BU 1 946 1300 aL SIMULATE REPORT COSTS 0 5139 0 0668 11 135 E0 1 330 1300 aL SIMULATE REPORT COSTS 0 5138 0 054 3 135
143. f you have defined individual panels and not PV generators the proportional cost of the inverter must be included in the PV panels cost Note that the number of PV panels in serial will be calculated taking into account the DC bus voltage The cost of the PY inverter must be included in the cost of the PY generator or panels Rated power of the inverter 1 s Peak power of the FV generator Inverter efficiency output power of rated Da ar a de oe 10 ala 30 0 30 50 FO od Ja de 30 You must indicate the rated power of the inverter times the peak power of the PV generator default x1 Also you must define the efficiency vs the output power of rated PV panels price inflation Prices for PV panels may be expected to increase at a rate different from that of generic inflation figures the same is true of wind turbines batteries and H2 components Therefore an estimation must be made of specific price increases for PV panels including an upper limit for those IHOGA will then use this data to calculate the number of years required to reach the price limit Once this value has been reached PV panels will be assumed to see their prices increased in line with general inflation Annual Inflation Rate for PA Panels Cost 4 a Max Variation of PY Panels Cost e g for an expected 20 reduction on current PY panels cost introduce 20 20 Dt The limit is reached in 5 5 years Cases of very high load When ver
144. fault currency was defined the first time you created a project However you can change the currency used in each project to dollar or another to define In any case the change of currency must always establish the equivalence with the previous currency Eequivalence between currencies 1 13 sZ Multiply costs by conversion factor Cumulative Conversion Factor 1 1 3 D If you check Multiply costs by conversion factor all costs used by the program including databases will be multiplied by this factor changing the currency In results costs also will be changed if the project has already been calculated except if the sensitivity analysis has been done which in that case it is mandatory to make the changeover before the calculations If not checked numeric values will remain changing only the currency The databases also change If you later want to change back to the default currency the conversion factor calculated by the program appears we can not change it because it 1s necessary to obtain the initial values in the default currency When you close the program 1t undoes the change in the database so that original database values are stored for subsequent projects in euros Warning If you have changed the currency in a project when you finish your project please close the program before you open another project or before you create another new project Loan In the right panel we can indicate th
145. for the components optimization af the evaluation time were enough to evaluate all see section 4 5 For example in this case 1 minute has been indicated as maximum execution time and the software must use genetic algorithms to optimize the combination of components in this time R Dufo L pez HOGA User Manual Maximum execution time O h 1 min MAIN ALG SEC ALG NUMBER OF CASES ES OPTION 1 EVAL ALL EVAL ALL 348460 100 1h 5 OPTION 2 EVAL ALL GEN ALG 14267680 A100 days zh OPTION 3 GEN ALG EVAL ALL 2969 0 56 h 0 60 OPTION 4 GEN ALG GEN ALG 122545 Je EB Oh 40 50 TIME EXPECTED 142 Click on Calculate to start the optimization The results are displayed after each generation is completed by the main algorithm Solutions evaluated are numbered in yellow and sorted on the number of solutions by which they are dominated Dom By The Pareto is displayed for each generation Please note that if the number of solutions to be shown is high the programme screen may be halted for a few minutes after each generation is completed 1HOGA must sort all solutions in order to determine the number of solutions dominating them This process may take some time for large populations The figure below shows the last generation in a multi objective example where cost is displayed versus emissions No best solution is available here as such so a range of non dominated solutions is
146. ged Language for non unicode programs must be changed to English Windows XP Go to Control panel gt Regional and Language Options gt Advanced gt and change the Language for non unicode programs to English and restart the computer Windows 7 or 8 Click the Start orb and in the search type regional You will see Change the date time or number format Open it and click the Administrative tab Next click Change System Locale and change it to English Windows XP screen Windows 7 and screen Regional and Language Options Ax i O EE ETE Regional Options Languages Advanced Formats Location Keyboards and Languages Administrative Language for non Unicode programs Welcome screen and new user accounts This system setting enables non Unicode programs to display menus and dialogs in their native language It does not affect Unicode View and copy your international settings to the welcome screen system programs but it does apply to all users of this computer accounts and new user accounts Select a language to match the language version of the non Unicode programs you want to use Py Copy settings English United States v Tell me more about these accounts Language for non Unicode programs Code page conversion tables This setting system locale controls the language used when displaying i text in programs that do not support Unicode A 10001 MAC Japanese Current language for non Unicode
147. generator 1350 wp 60 4C Generator 4000 VA Batteries bank of 11232 Wh Batt charge reg 54 Inverter 500 VA Rectif 1060 w By clicking on the Report button on the screen of sensitivity analysis summary it displays a report that can be printed or saved as pdf 1f we have a virtual pdf printer installed on the computer In this case the report occupies l page R Dufo L pez HOGA User Manual 181 E Print Preview SA A TT OC OS A a sale i 5 ee NM SB Be coel Project 1 Optimal solution found for each sensitivity analysis TOTAL COST NPC CO2 EMISSIONS m ae 8 CO2 emissions kg yr 3 co o 1 2 3 4 5 6 1 2 3 4 5 6 Sensitivity analysis Sensitivity analysis SENSIT ANALY SIS 1 Rad 1 4 65kWh m2 Load 3 63kWh dia I g 1 4 2 Inf F 1 Base Pr 1 x1 x1 x1 x1 NPC 16483 CO2 Emissions 180 kg yr Unmet load O kWh yr 0 Days range INF Renew able fraction 96 8 of demand Levelized cost of energy 0 5 kWh Components PV generator 2160 Wp 60 AC Generator 4000 VA Batteries bank of 11232 Wh Batt charge reg 86 A Inverter 500 VA Rectif 1060 W SENSIT ANALY SIS 2 Rad 1 4 65kWh m2 Load2 2 18kWh day L g 1 4 2 Inf F 1 Base Pr 1 x1 x1 x1 x1 NPC 12409 CO2 Emissions 104 kg yr Unmet load 0 kWh yr 0 Days range INF Renew able fraction 98 of demand Levelized cost of energy 0 62 kWh Components PV generator 1350 Wp 6
148. genetic algorithms to any given problem are thus presented as individuals within a certain species Each individual is actually a combination of the variables genes to be optimized in our case the variables or genes correspond to the hybrid system components and to the variables utilized for the system control strategy Our variables or genes are integers number of PV panels codes for panel types The structure of the variables or genes is called genotype whereas any concrete combination of variables or genes in the genotype is called individual or phenotype The first generation includes a random set of individuals which we call population These individuals breed that is they mix with each other with a higher probability of reproduction for the best individuals those with the lowest NPC 1 e best fitness New individuals are generated by reproduction children thus replacing the worst parents and creating a new generation Some individuals mutate values for variables or genes are randomly altered The process repeats itself with more and more new generations and better solutions provided as the algorithm progresses IHOGA makes use of two genetic algorithms the main algorithm and the secondary algorithm The main algorithm provides an optimum configuration for the PV panels the wind turbines the hydraulic turbine the batteries the AC generator th
149. gy If you choose the strategy Load following Pcrtical_gen and Pcritcal_FC variables are set to 0 W That is the generator or fuel cell never work at rated power to try to charge the batteries When it must operate the power required to operate is the one to strictly meet the demand This strategy implies that SOCstp_gen and SOCstp_FC are equal to SOCmin However these variables can be optimized as well as other variables In case of optimizing these variables for example if the software in a particular case chooses Pcritical_gen 1000 W and SOCstp_gen 75 this means For each hour if the generator has to supply a power greater than O but less than 1000 W it runs at its rated power charging batteries with surplus power to 75 of SOC try to reach this value of SOC alone during that time the following will not That is for that time the strategy really will be cycle charging without continue up to SOCstp For each hour if the generator has to supply a power exceeding 1000 W it will run at the power needed to supply the demand without trying to charge the batteries That 1s for that time the strategy will be load following Cycle charging strategy If you choose the strategy cycle charging Pcritica_gen and Pcritica_FC variables are set at a very high value 10 W thus ensuring that no load will exceed this value That is the generator or fuel cell will run when batteries can not meet the load at rated pow
150. h Worth Month Method PY bat 4 R Dufo L pez HOGA User Manual 36 3 1 2 OPTIMIZATION tab The type of optimization to be applied is selected in the screen shown below Only costs are optimized for mono objective mode whereas levels of CO or unmet load or both are also included for multi objective mode From 2 0 version two more objectives can be added maximization of HDI and jobs creation GENERAL DATA OPTIMIZATION CONTROLSTRATEGIES FINANCIAL DATA RESULTS CHART OPTIMIZATION TYPE MONO MULTI OBJECTIVE a MOMO DEBJECTIVE MULTI OBJECTIVE Display Mon dom only Cost CO2 Emis E i Cost Unmet load 300 Triple 50 Another A Export Paretos Display Parameters Optimization is Mono Objective by default Therefore the programme will obtain the most cost efficient solution that with the lowest total costs for the useful lifecycle or NPC Solutions are sorted by the application according to their costs for each generation Solutions with lower costs are more likely to breed therefore moving over to the next generation In fact the best solution is carried over unmodified elitism As the execution of mono objective optimization progresses a chart will be shown with the costs for the best solution in each generation as well as a table with the characteristics of that solution Multi objective optimization Please select MULTI OBJECTIVE for Multi Objective optimization where two three or fi
151. harges SOClimit 0 9 SOC to reset Number of Bad Recharges 9 999 End of batteries lifetime will be considered when Max Capacity is 80 of nominal Capacity Corrosin speed during floating life Corrosion speed for folating life data 2 Calculate The first is to choose at the top the battery type OPZS tubular optimized for photovoltaic applications long life or Ogi flat plate open use in uninterrumped power systems emergency lighting telecommunications etc can also be used in machines boot and in photovoltaic systems are similar to the so called modified SLI Batteries data OPZS 4 The software loads the data from the batteries used in the article Schiffer et al 2007 27 however it should be noted that these data are for a certain family of OPZS and Ogi batteries which may not coincide the batteries you are using We should update the data with those of the family of batteries we re using we should know our batteries data or test them to get them On the right side of the curve we must select the curve of corrosion rate vs the positive R Dufo L pez HOGA User Manual 103 electrode potential the Ruetschi 2004 model 33 or the Lander 1956 model 35 It should be noted that the actual curve for each battery family is different so we should define the curve for the family of batteries under consideration either from the manufacturer or by testing and modifying the values of the cur
152. he Higher Heating Value HHV for Hp is 39 400 Wh kg Systems which include Electrolyzer but do not include Fuel Cell Uncheck the Fuel Cell check box when no fuel cell is required e g when an electrolyzer is present but only H is used for external use with no consumption of electric energy from fuel cell mw FUEL CELL 3 15 2 Electrolyzer Data must be introduced on Name Nominal Power kW Acquisition Cost Operation R Dufo L pez HOGA User Manual 122 and Maintenance Cost Expected Lifetime Consumption Parameters A kW kg h and B kW kg h and Minimum Operating Power as a percentage of nominal power Please select the most appropriate units bottom centre for Expected Lifespan and Operation and Maintenance Costs yrs and yr or hours and yr Graph represents the consumption and efficiency of the electrolyzer that is selected in the table Below the graph it shows the nominal H2 mass flow kg h and the minimum electrical power needed to start generating hydrogen In the case of the figure the electrolyzer needs at least an electric power of 0 6 kW to begin generating hydrogen In the simulation if during a given time no more than 0 6 kW of power is available to operate the electrolyzer 1t can not generate hydrogen during that time and therefore it will not work during that time 3 H2 COMPONENTS E Fuel Cells Electrolyzers H2 Tank Generation of H2 by electrical energy
153. he desired column Right click to display the context menu and select Save Column or Save Table AC LOAD W DCLOAD w H2 LOAD Monn oh tm 2 34 JANUARY 600 600 600 600 FEBRUARY 600 600 600 600 El MARCH 600 600 600 600 E APRIL 600 600 600 600 El H T 600 600 600 600 JUNE 5 Save Column JO 600 E JULY b Save Table 10 600 AUGUST bourse evo 600 E SEPTEMBER 600 600 600 600 El OCTOBER 600 600 600 600 E NOVEMBER 600 600 600 600 p DECEMBER 600 600 600 600 To save the consumption chart right click to display Copy to the clipboard or Save Image This is possible for all iHOGA charts R Dufo L pez HOGA User Manual 60 AVERAGE LOAD MONTH JANUARY MO A E DC MIA HZ HH load 2 2 Fe bch eet eS dd dd do 3 500 _ 3 000 E E E MN 2500 E 2 000 o 51 500 1 000 500 Save Image Ctrl 5 j E 12 18 hour Once all consumption indicators are defined click on OK to return to the main screen R Dufo L pez HOGA User Manual 61 3 3 Solar resouce Irradiation Data on solar irradiation may be introduced by clicking on the Solar button Resources or selecting Solar within the Data menu Irradiation data is used for calculation of the energy produced by PV panels HE SOLAR RESOURCE IRRADIATION Latitude 7 1 5 41 66 Slope of PY panels 2 60 Azmuth PY panels 2 from South 0 Ground Reflectance 0 2
154. her Institute For worldwide data 1 In http www windygrid org software page pagel the software WINDFREEDOM by Dr Joaquin Mur can be downloaded It is a free softwaer that gets data from any meteorological station in the world To save data you need the Wolfram Mathematica software Following the Windfreedom user s manual you must download the data of 1 full year from January 1 at Oh to December 31 at 23 h to obtain a txt file that 1HOGA can open directly 2 In http www eere energy gov buildings energyplus ctm weather_data cfm Zip compressed EPW metheorological data files can be downloaded for many places in the World One of the files UNZIPPED should have the extension epw for example climatezone9 epw Change the extension from epw to csv for example climatezone9 epw to climatezone9 csv In Microsoft Excel open the file that ends with csv the one you have just changed 1t should open in a new file The hourly wind speed data will be displayed in the column V 8760 hourly values in m s You must copy these 8760 values to a txt file R Dufo L pez HOGA User Manual 184 3 For all the world http eosweb larc nasa gov cgi bin sse grid cgi email na http eosweb larc nasa gov sse RETScreen Other sites www weatherbase com http www winddata com www windatlas dk Www epa gov 7 What about data for solar irradiation You may get this from the following web sites Worldwide dat
155. ie Pa Pe Pe e Pe Pe P2 P2 Fo WINTER periods distribution O 1h 1 2h 2 ah 34h 4 5 5 6h B Hi Bh a 9h 9 10h 1011h 11 12h Pl Pl Pl Fl Pl Pl Pl Pl Pe P2 e Pe r P2 e 1213 1314h 1415h 15 16h 16 17h 1718h 1819h 15 20h 20 41h 122h 223h Ih Pi Pe e Pe Pl Pr Pl Po Poe Pao PS Pl Pl Click OK to return to the tab It should also be entered the expected annual inflation to the price of electricity CO2 emissions due to energy purchased from the grid depend on the country s energy mix and the maximum power Pmax kW that can be purchased from AC grid and the annual fixed cost of the Power year All the unmet load will be covered by the AC grid 1f 1t 1s possible We must take into account that if unmet load during some hours exceeds the maximum power Pmax kW that can be R Dufo L pez HOGA User Manual 55 purchased from AC grid fixed in this tab in that case the AC grid will not cover all the unmet load Also we must take into account that if there 1s H2 load and the electrolyzer maximum power cannot serve the H2 load in some hours 1t will not be covered Access toll You can define an access toll by a fixed price or by hourly price as explained for the price of the energy purchased The access toll is applicable to the electricity purchased to the AC grid and this cost will be added to the cost of purchasing electricity to the AC grid Access Toll P
156. ift m recommended Dm for Bda Friction Losses 10 A Total pump efficiency 30 ES Pump voltage PE User must select daily water consumtion m day for every month hourly water consumption in of daily sum must be 100 water tank maximum capacity m water tank capacity at the beginning of the simulation pumping data elevation suction m friction losses electrical pump data pump electrical rated power W pump minimum power of rated total pump efficiency and pump voltage DC or AC At the right of the text box of the daily water consumption it is shown in brackets the energy needed in kWh day to pump the daily water consumption Button Generate AC DC and H hourly consumption 8760 hourly values for each load type are then generated by clicking on Generate The application will show the values for maximum and average AC and DC power as well as the DC Factor average value of the ratio between DC hourly load and total hourly load Once the hourly values for the year are generated the tables may be saved as a new profile by clicking on Add Load Profile The new profile will be saved within the perfiles txt along with all other existing profiles Data from hourly file Data source Monthly Average Load Profile Import hourly data file data im w and kg Import The third option for data sources on consumption Import hourly data file may be use
157. ind speed Wind x In the first tab the base case the wind in the wind screen if wind is used in the system is called Vto 1 and it is shown the average speed of the year Clicking on the Add button you can add another series of 8760 values 1HOGA wind to consider them as the case Wind 2 You can choose as the series Wind 2 the base case Wind 1 multiplied by a scaling factor or import a series of 8760 values in m s from file If you import from file if the file is vto it incorporates the measurement height If another type of file we put in the height field m the value of the height above ground at which the measurement was made At the right of the case Wind 2 the annual average wind speed is reported R Dufo L pez HOGA User Manual 27 6 SENSITIVITY ANALYSIS o Aa La E ES Wind Solar Load Interest and inflation AC Gen Fuel Inflation Components costs SENSITIVITY ANALYSIS OF WIND SPEED Vind1 Case base Average Wind Speed 3 32 m s Wind2 O Case Base x Scale Factor J kel Wind E EA mis From file hou values in m s Height tm 10 You can add up to a total of 5 cases of wind for sensitivity analysis base case and four others Can also be deleted by clicking Remove Last one By clicking on the button on the bottom right Draw the different series are plotted Each case will be considered in a different optimization ie 1HOGA perform system optimization for each case Wind x If we have 3 cases
158. ing external Hz No electrolyzer or tank are required unless H loads are present Fuel Cells Electrolyzers Generation of Electrical Energy by Hydrogen H a Mame Power kW Acq cost E Pmin 0 0 0 100000 1E 7 1E 7 1 7000 0 2 15000 0 05 0 004 2 12000 0 12 15000 0 05 0 004 Equivalent CO emissions manufacturing fuel cells and electrolyzer 330 ka CO equiv k rated power IF output power F i lower than Proam ef E Pak H2 consumption kg h B Prifk 4 P k IF output power F is higher than Pmax_et 7 Phi HZ consumption kg h B Pn 4 P 1 Feb PP Pmax_ef 1 001 FC2 Consumo kg h y Eficiencia WPCI Electricity DC ee O Ha FCI H2 33 3k 4h kg Em 2 a Eficiencia de PCI Fuel from En zZ O kE L 5 ua FEE 5 O 3 CH I ou POWER kW o He produced by electrolyzer gt External Rated Power 2 kM his needed at least 0 008 kgH2 h to generate electrical power i 4 FUEL CELL ELECTROLYZER H2 TANK Annual Inflation Fate for Fuel Cells Electrolyzers and yy Max Variation of Fuel Cells Electrolyzers and H2 Tanks Cost e g for an H2 Tank Cost expected 90 reduction on current cost introduce 903 Limit Iz reached in 21 9 pears 30 Fuel Cell and Electrolyzer are connected to AC bus by means of their inverter and rectifier respectivelly Inverter and rectifier data Click on the check boxes under
159. l solutions dominated by 1 solution etc As the multi objective optimization progresses a chart and a table are shown by the application The chart includes the individuals for every generation the emissions or unmet load versus NPC for each individual this 1s known as a Pareto diagram The table provides a list of individuals sorted from best to worst Every time a new generation 1s obtained a new chart and table are shown A check box 1s available to Display Non Dominated Solutions only The Multi Objective algorithm 1s based on SPEA Strength Pareto Evolutionary Algorithm and on SPEA 2 The user must introduce the maximum percentage difference of NPC that may be achieved by any non dominated solution as referred to the non dominated solution with the lowest NPC The maximum number allowed for non dominated solutions must also be introduced This prevents the number of non dominated solutions from being too close to the population number which would result in a saturation of non dominated solutions In this case they would be too similar without a reasonable degree of variability As a practical example let us assume that a non dominated solution has the lowest NPC value of all at 100 000 If the percentage specified by the user is 60 all non dominated solutions with NPCs above 160 000 will be eliminated provided the total number of non dominated solutions is larger than the maximum number allowed for non d
160. le This percentage must be input for daily and hourly periods and for each type of load These values will be used by HOGA to calculate randomized hourly consumption levels Noise AC DC Hz Daly Do x fo gb x Hourly D xb z O AC load power factor The user must also introduce a value for the expected AC load power factor AC load Power factor cos fi 1 WATER m3 day FROM WATER TANK PREVIOUSLY PUMPED This tab displays the following R Dufo L pez HOGA User Manual 50 AC LOAD w pc LOAD 4 H2 LOAD kg J WATER m3 day FROM WATER TANK PREVIOUSLY PUMPED PURCHASE Z SELL ENERGY heL bE E ea Ae iz e HOURLY WATER CONSUMPTION IN OF DAILY CONSUMPTION January O kM hiday July 0 O kw h day Oh ih 2h Sh 4h Ah Eh kh Bh Yh Wh 11h February O 0 kwh day August JO 0 kw h day 2 2 Je e JJ io Js JE Gii March O 0 kiwh day September O kiwhidav 12h 13h 14h 15h 16h 17h 18h 19h 0h Ah 22h 23h Gm 5 a E 5 3 2 5 Fi Fi 4 2 El April D O kwh dap October D O kwthday e May 0 0 kwh day November 0 O kwh day l HOURLY WATER CONSUMPTION OF DAILY June 0 O kM h day December O Earth day 5 Scale factor for Monday Friday 1 For the Weekend 1 WATER TANK 2 E 12 18 Water tank capcadity 40 ma hour Capacity at the begining of the simulation 40 m3 ELECTRICAL PUMP PUMPING DATA Pump electrical rated power O Ww Purp minimum power 0 2 of rated Elevation head suction l
161. lected will then be Combinations_main_alg No _Pv_Panel_Types 1 No _max_Pv_Panels_parallel No _min_Panels_parallel No _Wind_T_types 1 No max_Wind_T_parallel No min_ Wind T parallel No _battery_tpes 1 No max_batteries _parallel No min_batteries_parallel No _AC_gen_types No Hyd_T_types No _electroliz_types No _Fuel_Cell_types Combinations_secondary_alg A criterion may be specified to halt the genetic algorithm Once a certain number of generations has been produced e g 20 the algorithm will stop 1f no improvements are made on the objectives In the example shown above the algorithm continues provided system costs for generation 25 are less than 99 of those for generation 20 mono objective optimization as this implies that results may be further refined If the value is over 99 the algorithm will stop an optimum state has been reached or near it R Dufo L pez HOGA User Manual 196 Check boxes related to the genetic algorithm are disabled when EVALUATE ALL COMB 1s selected In this case a check box 1s enabled to select the number of best possible solutions to be shown If a very large number of solutions is possible the application may use a large proportion of memory or it may even block Solutions to be shown are the best ones available including the optimum fit so the number of solutions selected should not be too large unless many combinations are required In the message box sho
162. ll as provided by manufacturers However AC generators usually show a high specific consumption for low powers Higher power values may contribute to lower the system s NPC Fuel cells have a more constant consumption though this may increase for low powers SOC min represents the minimum state of charge allowed for the batteries Though this is provided by the manufacturer higher values may be better Peritical gens Peritical FC SOC stp gen SOCstp Fc and HyTANKsp are control variables for the AC generator and the fuel cell Since AC generators have a higher specific consumption for low powers under the critical value Peritical gen It may be interesting to make them deliver higher power values The rest may then be used to charge batteries until a certain state of charge SOC is reached called SOC generator setpoint and represented by SOCgip sen H2 could also be produced in the electrolyzer until a certain level of charge is reached within the H tank called HoTANKegip in kg of H2 The order in which the excess energy is used charging batteries to reach SOC gp gen or generating Hz to reach H gt TANKsp will depend on the amount of excess energy itself If this is less than Prim charge batteries will be charged first and any remaining energy would be used to generate H2 If the excess energy is more than Phim charge the process order will be inverted The same holds for the fuel cell so the paragraph above applies here
163. llowing variables must be estimated the current generated by renewable sources as a function of solar irradiation wind speed and hydraulic flow the electric energy used up by the loads both AC and DC and the consumption of external H2 which depends on the loads expected for that hour the charge level of the batteries and the amount of H available in the tank Hourly values for solar irradiation may be imported from a file with the 8 760 hourly values or calculated from monthly published data using Graham s method 1990 17 with statistical variability or through the method provided by Liu and Jordan 1960 18 and Hay and Davis 1978 19 and Rietveld 1978 20 with different correlations Liu and Jordan 1960 18 Collares Pereira 1979 21 and Erbs et al 1982 22 The charge level for the batteries as well as the maximum acceptable batery charge may be calculated using any of two methods the Ah Model proposed by Schuhmacher in 1993 23 or the KiBaM Model Manwell and McGowan 1993 24 Coppeti model Copetti et al 1993 y 1994 25 26 or Schiffer aging model Schiffer et al 2007 27 Calculating an estimated lifespan for the batteries 15 very important as this has an influence on battery replacement costs and hence on total system costs In earlier programme versions a simplified method was applied Equivalent Cycles also used by other applications such as R Dufo L pez HOGA User Manual 16
164. load and energy bought and sold to the AC grid in thin columns not stacked R Dufo L pez HOGA User Manual 154 Hourly simulation Hourly values separately Monthly and annual Average Power Monthly values Annual values Hydrogen detailed AC Generator detailed Water load MONTHLY AND ANNUAL AVERAGE POWER kW Ss ii ns ee i i i i i i i i i i 0 2 4 1 4 ii Ile gt Ann A AT AA 0 18 t 1 A A 0 141 0 12 0 1 0 08 Average Power k 0 06 1 2 3 4 5 6 7 8 9 10 11 12 YEAR O PV Generator E Wind Turbines EJ Hydro Turbine MM AC Generator EB Fuel Cell O Total Load E Unmet Load HE E bought to AC grid MW E sold to AC grid Monthly values tab This tab displays for each month 1 12 monthly energy values kWh Hourly simulation Hourly values separately Monthly and annual Average Power Monthly values Annual values Hydrogen detailed AC Generator detailed Water load MONTHLY ENERGY kWh Total Load PV Generator Wind Turbines 100 100 50 50 0 0 2 6 8 10 12 2 6 8 10 12 2 6 8 10 12 Hydro Turbine Excess Energy Electrolyzer Energy HHV of H2 in H2 tank end ofthe month DR E O DR RD Batteries Charge Batteries Discharge ria Energy at the end of the month 40 6 20 4 0 2 2 6 8 10 12 2 6 8 10 12 Ae ae
165. lrc P2 Pmin gen Pmin FC SOC min Poritical_gen Poritical_FC SOC sip gen SOC stip Fc H TANK ip The total cost may thus be calculated referred to the initial installation time NPC for each possible solution obtained from both algorithms Main algorithm optimization of components On the MAIN ALGORITHM OPTIMIZATION OF COMPONENTS box the user must decide if the optimization method is GENETIC ALGORITHM or EVALUATE ALL COMB In the first case numeric values must be provided for a number of system parameters For each given genetic algorithm to be used for optimizing the physical system components the numeric values to be provided include the number of generations the population mutation and crossover breeding rates and uniformity in mutation For uniform mutation the value for each mutated gen or variable is selected at random For non uniform mutation the value is also selected at random but there is a higher degree of probability that this mutated value 1s close to the original one MAIN ALGORITHM OPTIMIZATION OF COMPONENTS OPTIMIAZ4 TION METHOD f GENETIC ALG RITHH f EVALUATE ALL COMB GENETIC ALGORITHM Generations 1 5 Population 1480 Crossover Rate S0 3 Mutation Rate Z Mutation Uniform STOPPING CRITERION Stop execution of secondary algorithm if after 0 generations it cannot improve 1 Ze IM 5 generations The solutions obtained will be more representative for larger populatio
166. lutions with low NPCs as well as low CO emissions or unmet load The genotype for the main algorithm includes 11 genes all of them integers Number of PV panels in parallel Type of PV panels Number of Wind Turbines in parallel Type of Wind Turbines Type of Hydraulic Turbine Type of Fuel Cell Type of Electrolyzer Number of Batteries in parallel Type of Batteries Type of Inverter Type of AC Generator Code types for all different elements are integers e g solar panel 0 solar panel 1 solar panel PURO It is not possible to optimize the number of PV panels and batteries connected in serial These variables are fixed and depend on the DC bus voltage and on the nominal voltage of the panel and the battery The user decides whether the inverter may be optimized or it has a fixed value with its rated power higher than the maximum AC load power All remaining elements battery charge regulator rectifier hydrogen tank are optimized by HOGA with respect to each other and to the control variables in use The secondary algorithm obtains the most appropriate control strategy combination of control variables for minimum costs and for any given component setup provided by the main algorithm more profitable system R Dufo L pez HOGA User Manual 194 The secondary algorithm genotype includes 12 genes all of them being system control variables and integers Pim charge Pl gen P
167. lyzer and an H gt tank In this case the fuel used by the fuel cell Hz or otherwise is purchased externally and additional data must be estimated as shown below bottom right Fuel Price 1 0 Ekg Fuel Price Inflation Aate 2 ES Fuel CO 2 emissions 0 kglO2 kgF uel Fuel Price kg note that fuel is estimated in kg even for a gas as weight does not vary with pressure and temperature Expected Fuel Price Inflation Rate for the fuel to be used by the cell and CO emissions from the fuel used by the fuel cell kgCO kgFuel The R Dufo L pez HOGA User Manual 121 SOCgp rc and Pertica rc control variables are not relevant now so they are disabled in the main screen Fuel cells data Data must be introduced for the fuel cell table including Name Nominal Power kW Acquisition Cost Operation and Maintenance Cost h Expected Useful Lifespan h Consumption Parameters A kg kWh and B kg kWh Pmax_ef and Fef and Minimum Operating Charge as a percentage of the nominal power If P Pw_ Fc lt P max ef 70 ConsSzc Bec P re Asc P If P Pn rc gt P max ef 90 Cons Ban P A Pil F Pax er 70 2 C CfN FC cH ef y e Pe 100 The chart shows the consumption for the fuel cell selected Additional data is provided under the chart on the efficiency of the fuel cell for the nominal power as a percentage of the Lower Heating Value LHV for Hz 33 000 Wh kg T
168. m R Dufo L pez HOGA User Manual 70 Scale by The user can select a Scale by lower left corner in the screen for hourly wind speed default 1 This 1s the value by which hourly wind data will be multiplied Not to be confused with the scale factor of the Weibull distribution Scale by 1 Import hourly data file Data source Monthly Average o Import hourly data file 860 values in m s Import Click on Import to use wind related readings in m s when this data is available in a file A folder called Viento is available within i1HOGA application folder including a file with data on wind readings for Saragossa and some others Data sources may be files with any of the following formats e Files with extension txt Text files with data on hourly windspeed readings expressed in m s Each reading occupies one line 8760 rows total In http www eere energy gov buildings energyplus cfm weather_data cfm Zip compressed EPW metheorological data files can be downloaded for many places in the World One of the files UNZIPPED should have the extension epw for example climatezone9 epw Change the extension from epw to csv for example climatezone9 epw to climatezone9 csv In Microsoft Excel open the file that ends with csv the one you have just changed it should open in a new file The hourly wind speed data will be displayed in the column V 8760 hourly values in m s
169. m 12h 23h am 45h 56h 67h ren es son 1011h 1112h 12 13h 1344n 1415h 15 16 gt E pe Le E e a mm m z D D O S amp S O O O O oa D GS O O O O D O O S amp S O O O O O See cgeegegaeccmcerEcreexs s D D D Dl DD a D a DO O D D D D O O S amp S O O O O a D O O O O O O D O O O O O O O SeegcgeeuceerBEiueereek ie E E a D a a DO O D D amp D D O S amp S O O O D fof D O a O O O O O En Scale factor for Monday Friday 1 Scale factor for the weekend 1 Load Profile data Data source o Monthly Average C Load Profile Import hourly data file data in 4 and kg For loads corresponding to profiles predetermined by the system or created by the user the R Dufo L pez HOGA User Manual 49 adequate option for data sources is Load Profile When this option is selected the default profile is charged the AC Farm see above Additional preloaded profiles are available by clicking on the pop up Profile menu which is displayed under the tables Profile Balada AL STANDAARD Randomness A percentage of randomness noise must be introduced for the expected consumption when data sources are either Monthly Average or Load Profi
170. mperature of the batteries is the same of the temperature at floating lifetime so the floating lifetime will be the same as the one indicated by the manufacturer Data for the calculation of life cycle emissions must be set equivalent CO2 emissions in the manufacturing of the batteries kg CO2 per kWh of storage capacity Equivalent CO emissions 55 kg COZ equiv kWh capacity We can add batteries from the data base R Dufo L pez HOGA User Manual 98 The State of Charge SOC expected at the start of the simulation as a percentage must be introduced Once all battery units are defined click on Accept to return to the main screen As mentioned above for solar panels and wind turbines when very high loads are present for the hybrid system e g for a town or a city 1t may be best to introduce data for battery sets on each row 1 e sets of batteries in series and in parallel Thus each table row would correspond to one battery set e g one group with 120 V and 500 Ah another group with 120 V and 1 000 Ah etc for this example DC voltage would be 120 V In this case the following values would be introduced on the main screen Batteries parallel Min 1 Max 1 3 10 2 Models of batteries Battery models available include the Ah Model Schuhmacher 1993 23 the KiBaM Model a kinetic model Manwell McGowan 1993 24 Copetti Model Copetti et al 1993 y 1994 25 26 or Schiffer Model Schiffer et al
171. n Gen Prnin FC H2 TANK setpoint HH H2 Days displ BATTERIES ENERGY wh soc SOC limits Cap Max SOC setpoint Gen SOC setpoint FC Save Simulation Data Save Prob Data ae LOAD FOLLOWING P1 gen INF Pmin_gen 57044 SOC stp gen 20 SOC min 20 The whole load is covered all the hours of the year The default value for Days displ is 1 day on each screen Use the scroll bar to move within the year Additional information is displayed under the chart on all variables shown with different colours and a check box for each one Variables disabled correspond to those not used by the system e g if no Wind Turbines are used the Wind Turbines curve will be disabled Energy is shown on the left axis for all system elements except for the batteries The State of Charge SOC for the batteries 1s displayed along the right axis R Dufo L pez HOGA User Manual 150 All energy values are shown in Wh this is equivalent to power in W since 1 hour steps are considered Some values have been converted into energy from kg of Ho including H2 consumption energy of the H tank and the value of the H2TANKg variable and have been converted into energy by multiplying the initial units by 39 400 Wh kg the HHP for H5 Values are provided for every variable and every hour A practical example the AC generator supplies O Wh on January 1 at 00 00 hours and 2 000
172. n cost year 0 replacement costs years when the component must be replaced and incomes of selling the component at tl _7 YEAR Costs PV Gen O amp M PV Gen Costs Wind T O amp M Wind T Costs Hydro T O amp M Hydro T Costs AC Gen O amp M AC Gen Costs 8 cash year NPC cash year NPC cash year NPC cash year NPC cash year NPC cash year NPC cash year NPC cash year NPC cash ye Si o 8642 4 8642 4 o o 1241 5 1241 5 o o o o 0 0 1040 1040 o o 10 1 o o 141 2 135 8 o o 66 3 63 8 o o o o 0 o 16 7 16 1 pan 2 o 0 144 133 2 o o 67 6 62 5 o o 0 o o o 17 15 8 3 o o 146 9 130 6 o o 69 61 3 o o o o 0 o 17 4 15 5 13 o 0 149 8 128 1 o o 70 4 60 1 o o 0 o o o lr or 15 2 14 5 o o 152 8 125 6 o o 71 8 59 o o o o o o 18 1 149 ES 6 0 o 155 9 123 2 o o 73 2 57 9 o o 0 0 o o 18 4 146 16 7 0 o 159 120 8 o o 74 7 56 7 o o o o o o 18 8 143 Eli 8 0 o 162 2 118 5 o o 76 2 55 6 o o 0 o o o 19 2 14 18 9 o 0 165 4 116 2 o o 777 546 o o o o 0 o 19 6 13 8 19 10 o o 168 7 114 740 7 500 4 79 2 53 5 o o 0 0 o o 20 135 6 20 11 o o 172 1 111 8 o o 80 8 52 5 o o o o 0 o 20 4 13 2 21 12 o o 175 6 109 7 o o 82 4 515 o o o o o o 20 8 13 22 13 0 0 179 1 107 5 o o 84 1 50 5 o o o o o o 212 12 7 J 23 14 o o 182 6 105 5 o o 85 8 49 5 o o o 0 o o 21 6 125 24 15 0 0 186 3 103 4 o o 87 5 48 6 o o o 0 0 o 22 12 2 Es 16 o o 190 101 5 o o 89 2 47 6 o o o o o o 22 5 12 26 17 0 0 193 8 99 5 o o 91 46 7 o o 0 o 0 o 22 9 11 8 Ezd 18 o o 197 7 97 6 o o 92 8 45 8 o o 0 o o o 23 4 115
173. n in DECEMBER fixed PV panels is 62 Optimal slope taking into account the ratio load irradiation over tilted surface fixed PY panels is 60 Month of worst ratio load irradiation for that optimal slope of 607 is DECEMBER with equivalent DC load of 4 4 kWh day and irradiation over tilted surface 60 is 2 63 kWh m2 day Back Irradiation for slope O 15 30 45 60 75 and 90 and for the optimal slope is shown for every month and for the whole year 1HOGA calculates the optimum angle for each month reporting the optimum tilt to maximize production in the month of lower irradiance in Spain December It also calculates the optimum inclination considering not only the irradiation but also the load consumption of each month giving the ratio load irradiation for each tilt angle between O and 90 The optimum tilt angle will be the value will so that the annual minimum ratio load irradiation is maximized This only makes sense if the slope of the panels will be fixed or tracking system is only using vertical axis If the tracking system is by using horizontal or both axes the tilt of the panels is changing to throughout the day If the azimuth we have indicated in the screen is not optimal 0 for northern hemisphere and 180 for the southern hemisphere a text appears in the top of the screen showing the warning If load is about the same throughout the year 1t will choose the optimum angle for the month R Dufo L
174. n of the first 10 years The first change of batteries is Year no 10 April 23 Batteries lifetime 9 31 years E 3 January year 1 December year 10 gt 3649 By clicking on the buttons on the right of the screen simulation different variables appears in R Dufo L pez HOGA User Manual 164 a new simulation screen BATTERIES ENERGY Ph m soc SOC limits ee SOC setpomt Gen SOC setpoint FC SOC O 1 SOC of the battery bank in per unit in Figure 10 years displyed 3649 days xom O S A i ee X fein E E January year 1 December year 10 BACK Days displ T full charge Time and equivalent cycles since the last full charge January year 1 December year 10 U Days since last full charge Full equivalent cycles since last full charge 3649 Days displ R Dufo L pez HOGA User Manual 165 V Battery Battery voltage and cutting limits in Figure 1 days display Battery voltage and cut limits 4 January year 1 Battery votag Lower cut im Higher cut im BACK Days displ Capacity Is displayed in Figure 10 years displayed 3649 days Battery max capacity capacity loss by corrosion and loss by degradation January year 1 December year 10 Maximum capacity Capacity loss by corrosion Capacity loss by degradation EE Ccorr limit 0 674 Days
175. n the last replacement of the component and the end of the study period Equivalent CO emissions including emissions from fuel consumed in AC generator emissions in the manufacturing process of the components of the system and emissions of the electrical energy bought to the electrical grid if this 1s the case are also obtained R Dufo Lopez HOGA User Manual 15 1 2 System Simulation Each and every year in the useful lifecycle of the system is assumed to be equivalent to any other year within the study period Thus the system is simulated for one full year for each combination of control variables and components The results obtained for a 1 year simulation will then be the same for the whole of the useful lifecycle of our facility Throughout this 1 year period all variables are collected to define system behaviour This is based on the features of all system components on control variables on levels of energy demand and on weather reports The system 1s assumed to be semi stationary so that all system variables remain unchanged through any given 1 hour period If the battery model is the aging model Schiffer et al 2007 27 which takes into account the aging model batteries degradation and corrosion not all years are the same but the simulation is performed continuously until the end battery life From that time the cycle is repeated For the most generic case where all system components are present the fo
176. n the wind 1s less Also interesting 1s the option to optimize the slope along with the system in cases where consumption is distributed throughout the year and during the day so unusual for example consumption of irrigation pumps that operate only in summer only during morning or afternoon hours in the day In such cases a priori it 1s difficult to know the optimal slope for the photovoltaic panels that feed these pumps so we can let the software try different slopes and seek optimal The possible slopes to consider in the optimization are between O and 90 in 10 intervals Official hour change User must select right of the screen the official hour change winter summer R Dufo L pez HOGA User Manual 67 Summer Official hour advances EN h to solar Hour From day 30 of month 3 Until day 26 of month i Winker Official hour advances 1 h to solar hour Force some consecutive cloudy days only diffuse irradiation Several consecutive cloudy days can be forced in a given month so that in those days there will only be diffuse irradiation Force cloudy consecutive days only difuze irradiation in month Enero Calculate button Once all data are introduced click on Calculate The application will generate hourly irradiation values on the plane of the PV panels Calculated data will be displayed under the chart referring to daily average hourly irradiation and yearly total values
177. n this button to start optimizing A confirmation screen appears so we can see the 5 constraints which will be taken into account by 1HOGA see section 3 1 3 Any combination of components and control strategy that does not match the 5 constraints will be discarded If you agree with this constraints click OK and the software starts the optimization If you do not agree click Cancel and in the main screen General Data tab change the constraints explained in section 3 1 3 Con e me The constraints 5 to be considered are 1 Maximum Unmet Load allowed 1 of total annual load There ts no AC grid or it is not allowed to buy Unmet load to AC grid 2 Minimum number of days range 3 days If there is AC generator or fuel cell using external fuel or purchasing Unmet load from AC grid ts allowed the number of days range will be considered as infinite 3 Nominal Capacity of Batteries bank Ah lt 20 x Isc PV gen Ide wind turbines group at 14 m s Do not consider this constraint if there 15 AC generator or a fuel cell using external fuel or purchasing Unmet load from AC grid is allowed 4 Minimum Renewable Fraction 0 5 Maximum levelized cost of energy 1305 kWh To change these constraints press Cancel Do you watn to continue with the optimization of the system After clicking on OK if the system was previously calculated the following window appears asking to confirm 1f we want to re calculate b
178. nalysis the optimal system found For example the following figure shows the summary of the sensitivity analysis of a project in which the number of sensitivity analyzes is 9 A graph that represents the NPC red based on the left vertical axis and emission green based on the right vertical axis for each number of sensitivity analysis is shown Below the chart there is a box where you can choose other representation Below there 1s the summary text of the best solution found for each sensitivity analysis Scrolling with the vertical scroll you can see all 9 results in text AAA A A an d ee HK Summary of Sensitivity Analysis o E NPC and CO2 Emissions of the best solution found for each sensitivity analysis 180 1 170 160 150 2 40 30 q S 20 w u a F110 O n 100 90 180 70 Sensitivity analysis Display in graph Back o NPC and CO2 emissions NPC CO2 emissions D CO2 emissions NPC Unmet Load NPC Report Best solution found for each sensitivity analysis il SENSIT ANALYSIS H 1 Rad 1 4 65kwW h m2 Load1 3 63kw hed a I g l 4 2 Inf F 1 Base Pr 1 x1 x1 x1 x1 NPC 16483 CO2 Emissions 180 ka yr Unmet load O kWh yr 0 Days range INF E renewable 96 8 of demand Levelized cost of energy 0 5 k Wh Components PV generator 2160 wp 60 AC Generator 4000 VA Batteries bank of 11232 Wh Batt charge reg 86 A lnverter 500 VA Rectif 1060 Ww SENSIT ANALYSIS 2 Rad 1
179. nd discharging the batteries 1f the charge regulator and the rectifier are PWM or ON OFF the two devices charge regulator and rectifier are supposed to perform same control After choosing the type of control PWM or ON OFF we must select the controller parameters those of the manufacturer of regulators or rectifiers that we will use they have to be suitable for the batteries that we will use In the case of PWM control we must enter data of charge in several stages typically three stages bulk absorption and flotation and also data for equalization charge If the model is Copetti also we must indicate the coefficient of variation of the voltage with temperature mV C Controller to switch Diesel genset to charge batteries If there is a controller charge discharge batteries controller that can automatically start the diesel generator some types allow the generator to charge the battery to 95 SOC default can be modified only in PRO version every few days or every number of complete cycles equivalents In that case check the box lower part of the window of the battery charger in PRO version in the rest of the versions in lower part of the window of the battery lf there is an AC Generator every 14 days or 8 equivalent full cycles generator charges batteries atleast upto 95 E R Dufo L pez HOGA User Manual 111 Rectifier battery charger conv AC DC Once simulated each combination of compone
180. ndicate the Factor rainflow 0 1 R Dufo L pez HOGA User Manual 104 Factor rainflow 0 1 05 The modified method takes into account the average SOC during each cycle of the batteries The original cycling curve of the following figure is provided by the manufacturer discharge cycles versus depth of discharge CF and 1s assumed to begin each cycle with the battery being fully charged However if a battery during a given cycle begins with an SOC lt 100 the wearing will be greater This approach seeks to address the most wearing fewer life cycles if every cycle does not start with fully charged batteries With the rainflow factor F a lower limit curve is obtained which would be for the cycles that begin and end in the shortest possible SOC for these cycles The lower limit curve is calculated by Cr F c CFR Crr where Crr is the lower reference of the figure 140 Cycles A Original curve 1200 1000 800 600 400 0 0 0 2 0 4 0 6 0 8 1 0 Depth Of Discharge DOD per unit To calculate the battery life for each cycle this method takes into account the average SOC for each cycle and get the number of cycles of life from the curve fot that SOC which will be between the original curve and the lower limit curve If selected model is Schiffer Schiffer et al 2007 27 the aging model used by Schiffer can be selected Only in PRO version R Dufo L pez HOGA R Dufo L pe
181. nerator diesel gasoline when energy from renewable sources is not enough to meet the whole load the rest energy 1s covered by the battery bank If the batteries can not cope with the demand the generator will run to cover the rest of the load The same applies for the fuel cell 1f present in the system instead of the generator e CYCLE CHARGING with or without the option continue up to SOCstp The difference with the previous strategy 1s that when the generator must run because load can not be met by the batteries it will run at its rated power so that the extra power will be used to charge the batteries If Continue up tp SOCstp is activated the generator will run at rated power until the State Of Charge SOC of the batteries reach the value of the variable SOC setpoint generator which by default is 95 R Dufo L pez HOGA User Manual 39 For both strategies we have the possibility to optimize the control variables while some do not make sense depending on the global strategy chosen The variables to be optimized must be selected here with a maximum number of 12 see Annex 2 The exact number of variables will depend upon the system elements selected For the case shown in the figure below no fuel cell has been selected no electrolyzer so the following variables are disabled Prim charge Plrc P2 Pmin sc Peritical gen SOCstp cen and H TANK sip as they are no longer required Load following strate
182. ng the general report the probability analysis report 15 automatically opened Data and results more relevant appear in graphical probability distributions This report has multiple pages bottom left of the page informs where we are Clicking on the top left MI we move through the different pages of the report On the first page there are the most important results with their probability distribution graphs On page 2 it is reported the mean and standard deviation of the other results and the report of the most important results of probability typical cases combinations 5 umber of probability variables combinations of average average Std Dev average 3Std Dev average Std Dev average 3Std Dev of different variables taken into account in the probability anaylsis consumption solar irradiation wind speed and or water flow 1f applicable This report can be printed a printer or PDF in the same way as explained for the general R Dufo L pez HOGA report Print Preview User Manual 171 _ S gt ars OE BSB lt gt n 3 B Project 1 hoga Solution 0 Probabilistic Analysis Report Random data Load mean 7 04 KWh day Std Dev 0 28 AVERAGE DAILY LOAD kWh day 7 Wind speed mean 3 32 m s Std Dev 0 AVERAGE WIND SPEED Ms Results Total Cost NPC mean 29351 Std Dev 1799 3 TOTAL COST NPC currency ni 30 000 Unmet load mean 0 Std Dev 0 UNME
183. nother one for weekend AC LOAD GYI DE LOAD w H2 LOAD kg WATER m3 day FROM WATER TANK PREYIOUSLY PUMPED PURCHASE SELL ENERGY Month Oih 12h 23h 34h 45h 56h Brh zeh es stos 101th 11 12 12 13h 1314h 1415h 15 164 pe e oe a lt MI E D gt gt D D gt gt D GS O D O O O O O Ss D Se O a O O D O O D D Ge O O D O O O Ss D D O a O D O O O SO D eS O D O O D O O SO D D Ge O O D O O O Ss D GS O D O O O O O Ss D GS O D O D O O So D GS Ge O O O O O Ss D GS O D O O D O O Ss D GS O D O O D O O D e 0 D D szem O o JS e DR Id N 8 08 D Sea O O O O 4 din Scale factor for Monday Friday 1 Scale factor for the weekend 1 H2 LOAD W tab In this table you must enter the H2 load kg 1 e external H2 consumption It is not the H2 consumption of the fuel cell Here you must enter the H2 consumption which will be used externally for example H2 to be used in a hydrogen car Scale factor must be entered one for weekdays and another one for weekend AC LOAD WwW DC LOAD 4 HZ LOAD kg WATER m3 day FROM WATER TANK PREVIOUSLY PUMPED PURCHASE SELL ENERGY E Moh o
184. ns and larger numbers of generations where the genetic algorithm will provide an optimum solution more easily However when both values are high a longer time will be necessary for the simulation this R Dufo L pez HOGA User Manual 195 time 1s proportional to the population and the number of generations included for both the principal and the secondary algorithm A balance must be reached between the required accuracy and the time available for execution For large differences in maximum and minimum values for batteries PV panels and wind turbines in parallel many combinations will be available for the sizes of solar and wind turbines as well as batteries For very low maximum values problems may arise when catering for energy demand unless additional sources are available such as a diesel generator a fuel cell etc The number of cases to evaluate in order to optimize component combinations using genetic algorithms will be given by Combinations_main_alg Population_main Generations_main 1 Population_main Crossover_Rate_main 100 Mutation_Rate_main long 100 Combinations_secondary_alg For all possible component combinations select EVALUATE ALL COMB This will apply forced optimization evaluating all the combinations with no genetic algorithms For a large number of combinations execution times may increase enormously The number of possible combinations when all components are se
185. nsiderations As an example we may modify the minimum value of the SOC for the batteries in order to check for changes on the results shown in the same table row For example the number of system elements in parallel may also be changed on the table PV panels batteries and wind turbines Any changes to the power of these elements will however produce no effect as powers are only displayed not manipulated 1HOGA uses the values of power introduced into each component screen Changes on these screens will produce changes on the results table 4 4 5 Report Click on the REPORT column in the results table to display a report for each solution Details are provided in the report on System Components with a power chart Control Strategy Energy Balance and NPC values with charts for all of them The menu at the top provides the following options Zoom Printer Setup Print Report Save Report to a File Open an Existing Report Reports may be saved in pdf format using Adobe Acrobat and the Print option If you have installed in your computer Adobe Acrobat or a PDF virtual printer fo example Free Pdf Creator http pdfcreator softonic com the printer can be configured as a virtual printer of PDF and when clicking on the print button it generates the report as a pdf file which can be saved R Dufo L pez HOGA User Manual 170 ODE gt S8 B l ms Project 1 Solution 1 DC Voltag
186. nsume all the energy from AC grid Draw button A Draw button 1s available bottom left Once the yearly loads are generated or imported a screen 1s displayed with a chart for the hourly consumption during one full year expressed in watts all intervals are hour long so W or Wh may be used for the units AC consumption is displayed in blue with DC consumption in green and Hz consumption in red Data for H consumption is introduced in kg but must be translated into energy Wh in order to compare this with electricity consumption the HHV for H 1s used ca 39 000 Wh kg Data for water consumption is introduced in m day and converted to m h but must be translated into energy Wh to be displayed this energy displayed is the energy needed to pump previously from the river to the tank the water consumption for that hour The number of days to be displayed may be changed bottom right By clicking on the rightmost button in the chart a menu 1s shown to select Copy to the clipboard or to Save Image R Dufo L pez HOGA User Manual 59 Graph dl dl td td te t AS AE A A AROS APS APA AAA CA a le AS BACK Hourly values generated or imported may be exported by clicking on the Export button top right Data from consumption tables may also be saved for AC DC and H2 The user may save only the column selected or the whole table To save data left click on any cell within t
187. nts and strategy for each case IHOGA determines the maximum power required by the rectifier thereby 1t calculates its cost The cost of AC DC converters rectifiers may be modelled to be linearly dependent on power within certain limits Their efficiency is usually very high around 90 with little dependence upon power If the rectifier battery charger is included in the AC Generator you must set here its costs in O If the rectifier is included in the bi di converter see next section the cost of the rectifier will be set to O automatically R Dufo L pez HOGA User Manual 112 3 13 Inverters The Inverters screen may be accessed by clicking on Inverters Components area or selecting Inverters in the Data menu Inverters are DC AC converters Unlike other auxiliary equipment inverters are a very important component with a large influence on the operation and total cost of the system Inverter performance is heavily dependent upon power at any time apparent power Inverter costs are equally important so details must be introduced on all features available Inverters data Generic data on inverters includes Name Apparent rated Power VA Useful Lifespan yrs Acquisition Cost If the inverter includes the battery charger bi directional inverter select OK in the column Batt Charger In that case you must set the value of the maximum current to charge the batte
188. of AC Generator fuel Cost Fuel and cost of external fuel for Fuel Cell C fuel ext FC and incomes of selling E and costs of buying E to the AC grid Inc Sell and Cost Buy are expressed in 8 Load of Hydrogen H2_kg load H2 used by fuel cell from H2 tank Fuel FC or externally purchased Fuel ext_FC hydrogen generated by the electrolyzer Prod H2 and hydrogen stored in H2 Tank HZ 9 Date Hour Load AC load DC load H2 load H2_kg load Water PV Wind Hydro Gener Fuel Gen Cost Fuel F C Fuel 10 01 ene 0 00 69 96 22 0 0 0 47 96 0 61 63 0 0 0 0 0 aai 01 ene 1 00 69 96 22 0 0 0 47 96 0 35 93 0 0 0 0 0 EM 01 ene 2 00 69 96 22 0 0 0 47 96 0 18 33 0 0 0 0 0 13 01 ene 3 00 69 96 22 0 0 0 47 96 0 9 2 0 0 0 0 0 14 Ol ene 4 00 69 96 22 0 0 0 47 96 0 19 72 0 o 0 0 0 15 01 ene 5 00 69 96 22 0 0 0 47 96 0 10 92 0 0 0 0 0 16 01 ene 6 00 349 8 110 0 0 0 239 8 0 7 04 0 0 0 0 0 17 01 ene 7 00 293 9 176 0 0 0 119 9 0 24 61 0 0 0 0 0 18 01 ene 8 00 251 9 132 0 0 0 119 9 56 87 12 23 0 0 0 0 0 a 01 ene 9 00 181 94 110 0 0 0 71 94 309 42 8 59 0 0 0 0 0 20 01 ene 10 00 181 94 110 0 0 0 71 94 571 72 5 77 0 0 0 0 0 21 01 ene 11 00 403 92 308 0 0 0 95 92 787 64 Zu 0 0 0 0 0 22 01 ene 12 00 427 9 308 0 0 0 119 9 909 31 0 26 0 0 0 0 0 23 01 ene 13 00 411 84 220 0 0 0 191 84 909 31 0 0 0 0 0 0 24 Ol ene 14 00 367 84 176 0 0 0 191 84 787 64 0 0 0 0 0 0 25 01 ene 15 00 273 9 154 0 0 0 119 9 571 72 0 3 0 0 0 0 0 26 01 ene 16 00 203 94 132 0 0 0 71 94 309 42 0 0 0 0 0 0
189. offered The user must select the most convenient solution based on cost and emissions and or unmet energy R Dufo L pez HE Proyecto CAiHOGA2 0 PRO Proyectos 1 HOGA _ gt baba Project Data Calculate DataBase Report Help LOAD 7 AC GRID GENERAL DATA OPTIMIZATION CONTROL STRATEGIES FINANCIAL DATA RESULTS CHART RESOURCES A SEA A Multi objective optimization Non dominated Pareto of Gen 15 Total cases evaluated 2993 Y SOLAR o 133 A A e 0 ls is apa o a o pp es AOS SS o 131 RN O tettes 1294 COMPONENTS A A E E E E E E E E E E E E A E E mass eses ais odc esco meli sas dates doce sau 8 127 i i i i Y PV PANELS 2126 i i Das ae E 124 A r go ata pa a SR e alka E a A 1224 121 vf BATTERIES uti gt gt gt gt gt gt 21 000 22 000 23 000 24 000 25 000 26 000 27 000 28 000 29 000 30 000 31 000 Y INVERTERS Total Cost NPC Y AC GENERATOR Show Sketch af H2 F C Elyzer Total Cost NPC Emission kg002 yr Unmet kWh yr Unmet D range Cr h Isc de 4 Ren Cost E kw h Simulate OTHERS AUX 0 20829 134 0 0 INF 53 988 0 63 SIMULATE 0 21206 119 0 0 INF 47 99 7 0 64 SIMULATE DC Voltage 24 V 0 31584 119 0 0 INF 47 997 0 95 SIMULATE AC Voltage 230 Y PRE SIZING Energy Storage 4 days range Max bat parallel gt Cn min Max PY pan parallel gt P min Max wind t parallel gt P min H
190. ojects of very high daily consumption you should choose a higher currency for example a fictitious currency called k equivalent to 1000 so we avoid economic results to have oversized numbers 2 Can iHOGA only be used to simulate and optimize off grid systems No you can also simulate and optimize grid connected systems with or without energy storage If AC grid is available and the option to purchase to AC grid unmet load unmet by the standalone system energy not served by the system is purchased from the grid If you check the option to sell excess energy not used by the standalone system to AC all power not able to be consumed or stored is sold to the grid Both options are independent may be marked only one of them or both It can also take into account the consumption of Net Mettering annually or monthly so that the system will only sell to the AC grid the energy bought from the grid annual or monthly There are up to 8 options of Net Mettering depending on the energetic laws In systems where there is no load energy consumption of the system is 0 kWh in the constraints you must change the maximum levelized cost of energy because it does not make sense and should put a very high value for example 10 you can write 1E10 3 What components should be selected when optimizing everything This choice will depend on consumption design available renewable resources and the commercial models to be used of ea
191. oltaic Idc wind turbines renewable fraction or maximum levelized cost of energy In this case 1HOGA assigns an infinite cost to the solution All rows showing R Dufo L pez HOGA User Manual 139 this value INF under the C total column NPC correspond to a generation where no solution is available within the constraints This happens often when loads are high and system elements are small The graphical representation is C total NPC 0 Once the simulation is completed a description is provided of the best solution found the best solution for the last generation Show Sketch Click on the check box in the right to show the layout of the selected components Sketch or the results table MK Proyecto C iHOGA2 0 PRO Proyectos LHOGA a E Project Data Calculate DataBase Report Help LOAD AC GRID _ LOAD 7 Ac GRID GENERAL DATA OPTIMIZATION CONTROLSTRATEGIES FINANCIAL DATA RESULTS CHART RESOURCES Y SOLAR o __Hyoro_ COMPONENTS A PvPANELs wip URB HYDRO rure Y BATTERIES Y INVERTERS Y AC GENERATOR Show Sketch wf H2 F C Elyzer _Y OTHERS aux ee 0 0 63 REPO 0 E f Multi objective optimization Total No of cases evaluated 3600 Time 1 12 0 63 SIMULATE REPO 0 63 SIMULATE REPO 0 63 SIMULATE REPO 0 63 SIMULATE REPO 0 63 SIMULATE REPO 0 63 SIMULATE REPO _ 0 63 SIMULATE REPOI 0 63 SIMULATE
192. ominated solutions After all non dominated solutions above the specified percentage are eliminated the number of the remaining non dominated solutions is checked If this number is still larger R Dufo L pez HOGA User Manual 38 than the maximum number allowed truncation is applied For each pair of adjacent non dominated solutions on the Pareto diagram a check is carried out of the modulus of the distance between them The solution is eliminated for the closest pair where the solution is nearer from its adjacent solution on the other side The user must also decide on the number of generations between successive storage of the Pareto diagram 1 e NPC and emission values for the individuals in that generation The first and the last generations are stored by default Once the simulation is over the different Pareto values stored may be exported as an ASCII file by clicking on Export Paretos 3 1 3 CONTROL STRATEGIES tab GENERAL DATA OPTIMIZATION CONTROL STRATEGIES FINANCIAL DATA RESULTS CHART CONTROL STRATEGIES VARISBLES TO OPTIMIZE Load Following Cycle Charging Continue up to SOC stp Try both Pmir gen Pin FC H2TANKstp Figen HIRE P2 O SOCstp_gen SOCstp_ FC SOCmir Peritical gen Pentical FC Plim charge FixWariables Wariables accuracy 9 100 There are two possible global control strategies e LOAD FOLLOWING STRATEGY In this strategy in systems that include batteries and ge
193. on Draw to display wind speed values for all hours within the year WIND SPEED 8 January BACK R Dufo L pez HOGA User Manual Info time of calm wind Click Info time of calm wind to see the information about calmness for each month E Calm winds time lt 3m s el jp JANUARY 296 Hours of calm winds during the whole month 39 of time 12 3 days Masimum number of consecutive hours with calm winds is 44 hours 1 8 consecutive days FEBRUARY 258 hours of calm winds during the whole month 38 of time 10 8 days Masimum number of consecutive hours with calm winds z 45 hours 1 9 consecutive days MARCH 357 hours of calm winds during the whole month 49 of time 14 9 days Maximum number of consecutive Hours with calm winds is 55 hours 2 3 consecutive days Into Info APRIL 321 Hours of calm winds during the whole month 43 of time 13 4 days Masimum number of consecutive hours with calm winds is 84 hours 3 5 consecutive days Di M r 409 hours of calm winds during the whole month 6 of time 17 days Maximum number of consecutive hours with calm winds 12 80 hours 3 5 consecutive days pato JUNE 431 hours of calm winds during the whole month 59 of time 18 days Maximum number of consecutive hours with calm winds i 57 hours 2 4 consecutive days Into JULY 407 hours of calm winds during the whole month 54 of time 17 days Maximum number of consecutive hours with
194. on does not meet constraints an infinite value is assigned to them by 1HOGA For display purposes the NPC is here considered to be equal to zero When EVALUATE ALL COMB is selected for the secondary genetic algorithm in a project with Optimization of Strategy Only all possible control variable combinations are R Dufo L pez HOGA User Manual 145 tried by HOGA Once all possible strategy combinations are evaluated HOGA displays the N best results sorted on costs lowest cost first Click on Cancel to stop the display at any point R Dufo Lopez HOGA User Manual 146 4 4 Result Table The table below shows all the features and parameters for the best solution within each generation Use the scroll bar at the bottom to move from left to right within the table 8 Total Cost NPC Emission kaC02 yn Unmet bet Coiote A er Cost E kwh Simulate Reporl j 20824 133 INF gt 0 63 SIMULATE REPOI 1 21152 119 0 IMF 7 dal 0 64 SIMULATE REPO E 21222 176 O 0 IMF adi 3643 0 64 SIMULATE REPOI 3 21422 133 O 0 IMF Bb 0 65 SIMULATE REPOI 4 21554 122 O 0 IMF BE 100 0 65 SIMULATE REPOI 5 21561 122 0 IMF dal 100 0 65 SIMULATE REPO E 21701 135 0 IMF r4 391 0 66 SIMULATE REPOI T 21762 173 0 INF EA SA 0 56 SIMULATE REPOI a 21773 120 O 0 INF 57 333 0 56 SIMULATE REPO 4 b The first columns after the first for Generations or for Dominated Solutions or for o
195. on or a very closely solution In short 1HOGA is a software tool for optimum sizing of hybrid energy facilities with the possibility to include renewable energy sources solar wind and hydraulic together with accumulator based support systems batteries and electrolyzer with H tank generating sets AC generators and fuel cells The tool uses genetic algorithms for studying costs and pollutant emissions in order to determine an optimum ratio for the number and type of PV panels wind turbines batteries AC generators electrolyzers fuel cells H2 tanks and inverters the power for the rectifier the current for the battery charge regulator and the overall control strategy for the system see Annex 2 for details of the control strategy All elements would be present for a generic case However the user has the choice to exclude any components at will R Dufo Lopez HOGA User Manual 13 1 1 System optimization In Annex 1 more information about Genetic Algorithms is shown IHOGA makes use of two genetic algorithms the main algorithm and the secondary algorithm The main algorithm provides an optimum configuration for the PV panels the wind turbines the hydraulic turbine the batteries the AC generator the fuel cell the electrolyzer and the inverter in order to minimize total system costs These are calculated for the total system lifespan and updated with respect to the initial time i e to the Net Present Cost
196. onal copyright treaty Conditions to use this software 1 This software is provided as 1s and without any warranties expressed or implied including but not limited to implied warranties of fitness for a particular purpose and non infringement 2 You expressly acknowledge and agree that use of the Software is at your sole risk 3 Calculations involving metheorological variables irradiation temperature wind etc and financial variables interest rate inflation rate etc are estimates that may differ significantly from the actual values the system models may differ significantly from actual performance and results of the simulations and optimizations could differ significantly from actual operation and actual costs of equipment and systems 4 Data of commercial components of the databases have been obtained on the manufacturers websites and costs have been obtained from online shops at a certain date Current costs can be different from costs shown on database Some data have been estimated and may differ from actual data 5 You give up the ability to require the author any responsibility for any defects errors or omissions or malfunctions or data from the software or from the databases If you agree with the conditions of this license for this sofware you can install it If you do not agree do not install this software or uninstall it Additional conditions for EDU version 6 You agree to use this software only in
197. oonnnnnnnnnnnnnnnnnnnnnnnnananoos 43 SA A AMAS A 46 Ss SONAL PC SOUC SLC AC Esla ON y OO sas asd cess ous aca A 61 SA Wind RESQUICOS oerien er EEEE E EEEE EENS 69 Hydrant TRC SOU CCS eee e o CU E A 78 CE DAL DOSES E E E CUE E bra oe sos a dare natandiiadaanas 80 IITA D e e UU E Asus deantioese 82 A A IS PUE PI saias ansiosa E conde sa aos panda n Gana renetand 89 Ja ALY dra APOIOS asaaneaainsoo gde aa asno aii des So gs ca ca a Sra a 94 sO Batteries aC CU MUN ALORS solas Cas anasaD 96 3101 General dala e e EE DE CRER CRER RRRRRRA ERR R 96 Del Models ODA sia 98 MEE Sl ModE OP ou ADS 100 3 10 4 Schiffer Model Only in PRO version 102 So Dalteres Me models a a S 103 O PRE SIZIN 6 PR apa e DR RR S SKEGEE 106 3 12 Auxiliary Equipment for Charging the Batteries 109 ANA ER EE DR 112 INCAS joio O do RR a RR o A 115 Force the generator to run all the Umie isses 116 R Dufo L pez HOGA User Manual Time availability AC generator in the hybrid system ccccooononnnnccnnnnnonononocnnnnnnnnnos 116 3 14 Fuel Cells and ECCI ONY ZO Sidor aa iios ari 118 AAA o RAR E ye ale SES KESDSE 119 SA Sl 0 110 8 ZS PAPI PON A e RN SR coe ocesiaeasceoes 121 E Be RS EG a oral a 123 DMO TAD WAG TOD C0 CANO tcs 125 3 17 Sensitivity Analysis Only in PRO version 3 18 Probability Analysis Only in PRO version 130 4 CALCULATING THE HYBRID SYSTEM occcccccccccccconcconcccncncnc
198. optimization screen EVALUATE ALL COMB 1HOGA will try all possible combinations Enumerative Method This option may be selected for both the principal and the secondary algorithms When this option 1s enabled no genetic algorithms will be applied Once the calculation is completed the N best combinations will be displayed N representing the figure introduced in the dialogue box below See Best see end of section 3 1 3 EVALUATE ALL COMBINATIONS See best 10 When EVALUATE ALL COMB is selected for the main genetic algorithm in a project R Dufo L pez HOGA User Manual 144 with Optimization of Components and Strategies all possible element combinations are tried by HOGA The application then seeks the best strategy for every combination of components Here the secondary genetic algorithm 1s the best method if EVAL ALL is not checked in the secondary algorithm and it 1s also possible to try all possible control strategy combinations if EVAL ALL is checked in the secondary algorithm In any case once all combinations are calculated the best ones are displayed in a table and a chart The N best combinations are shown here sorted by cost lowest values first and including the best strategy found for each combination The time required to display may be long for very high values of N The display may be interrupted by the user at any point An example is shown in the figure belo
199. or Fuel Prices 90 CO2 emissions kgCO fuel unit and Consumption Parameters A fuel unit kWh and B fuel unit kWh Default values for A and B are referred to a Diesel generator as shown by Skarstein and Ullen 1989 35 The chart above shows fuel consumption for the generator selected R Dufo L pez HOGA User Manual 116 Consumption fuel unit h P kW B P kW A where P is the nominal power in kVA although active power is used for consumption P is the output power Data for the calculation of life cycle emissions must be set equivalent CO2 emissions in the manufacturing of the generator recycling etc kg CO2 per kVA of rated power Equivalent CO2 emissions geneartor manutactunna 215 kg CO equi 4 RMA rated power The annual inflation rate for fuel prices Inff e is an important parameter and must be clearly identified with respect to the general expected inflation rate Inf shown in the main screen Most fuels are affected by much higher inflation rates than those affecting components and labour costs Fuel inflation rates must therefore be dealt with separately Force the generator to run all the time You can force the generator to run all the time to create the AC grid in this case you should select the checkbox Generator runs all the time AC grid reference Time availability AC generator in the hybrid system You can set the time availability of the AC generator both during the
200. ot improve 1 im 5 generations R Dufo L pez HOGA User Manual 197 For optimization of the control strategy using genetic algorithms the number of combinations will be given by Combinations_secondary_alg Population sec Generations sec 1 Population sec CrosoOver rate sec 100 Mutation rate sec long 100 As explained above for the main algorithm for all possible component combinations EVALUATE ALL COMB must be selected This will apply forced optimization with no genetic algorithms In this case the number of possible combinations is given by N jables_to_optimi Combinations secondary alg Variable_accuracy 1 me For large numbers of variables to optimize an extremely high value may result This will render the optimization process unfeasible Check boxes related to the genetic algorithm are disabled when all possible combinations are evaluated In this case a check box is enabled to select the number of best possible solutions to be shown This holds only for Strategy Only Optimization R Dufo Lopez HOGA User Manual 198 ANNEX 2 Control Strategies Control strategies utilized by earlier versions of HOGA 1 2 made use of the strategies described by Barley and Winn 28 in 1996 and of those developed by the HOMER application The current version of the programme uses a more complex and accurate global strategy 3 developed by the authors and optimized by means of genetic algorithm
201. otal Annual Irradiation Plane of PY 1696 7 kM heme Export tilted Exportar horiz Il Scale factor 1 If there is no sun tracking system or the sun tracking system is done only by horizontal axis the azimuth of the photovoltaic panels must be set orientation with respect to the south optimal is 0 for North Hemisphere and 180 for South Hemisphere azimuth west azimuth east If there is no sun tracking system or the sun tracking system is done only by vertical axis the slope of the photovoltaic panels must be set R Dufo L pez HOGA User Manual 62 Data sources for irradiation may be used in different formats such as monthly average daily readings Monthly Average Daily Irradiation or hourly readings on a horizontal surface expressed in kWh m From a File It is always best to use hourly data but this is not always easy Data source f Monthly Average C Import Hourly Data File in kim home Monthly Average data The default data source allows the user to select a data format from the monthly average data pop up menu Data Source for Monthly Average Daily Radiation Cleamess Index Irradiation Radiation Horizontal Surface kw hmmz Tracking System Peak Sun Hours The default format is Radiation Horizontal Surface kWh m2 with additional choices for Clearness Index and Peak Sun Hours Once the format is selected values will be intro
202. oughout the year be it caused by unusual consumption peaks or to longer than usual periods with low solar irradiation levels or wind speeds Additional auxiliary generation systems may be convenient in some cases in order to compensate for the above An acceptable charge level and a longer lifespan may thus be achieved for the batteries Generating sets are often used to ensure uninterrupted energy supply these are referred to as AC generators in the programme and are commonly diesel operated These generating sets are the most widely used alternative for auxiliary systems or as a method to provide additional energy supplies for certain high power consumption levels AC generators however do have major drawbacks emission of toxic gases with greenhouse effect An alternative technology is currently available in order to replace or complement AC generators fuel cells combined with electrolyzers Electrolyzers produce H gt from renewable sources with surplus energy This hydrogen is stored in an H3 tank When the demand for energy is higher than the energy supplied from renewable sources additional energy may be supplied by the fuel cell using the stored H in combination with O from the air in order to produce electricity and water through inverse electrolysis No harmful emissions are produced and H gt is obtained free of any charges as it is obtained in the electrolyzer with R Dufo L pez HOGA User Manual 11 ob
203. ourly Periods Hourly price all days the same O 1h 1 2h 2 3h 3 4h 4 5h B Bh E 7h F 8h gh 3 1 h 1011 11 12h 0 150000 0150000 0 150000 0150000 0 15000 075000 0150000 0150000 0150000 075000 0 150000 0 15000 1213 13914h 1415h 1516h 1617h 1718h TEA 19 40 20 2 1h Alho 0 2223h 324h 0 15000 0150000 0 75000 0150000 0480000 045000 0 15000 0 15000 0150000 0450000 0 15000 0 150000 OF R Dufo L pez HOGA User Manual 54 If you select Hourly periods the window shown is the following where you can define up to 6 hourly periods default 3 periods and you must indicate the price for each period You must enter the summer time from day to day the rest will be winter and you can define the distribution of the hourly periods in the day in summer and in winter HOURLY PRICE OF THE ELECTRICITY PURCHASED FROM THE AC GRID Hourly Price Data Eta Hourly all days the same From file 8760 hourly values Import f Draw Hourly Periods Hourly Periods Number of Hourly Periods 3 easel Sac Period P1 price 0 0799999982 From dap 30 month 3 j Period P2 price 0 119939939973 To day 26 month 10 Period P3 price O 1500000053 SUMMER perods distribution 01h 1 2h 2 36 3 4h 4 5h 5 6h B A Ah 8 9h 9 10h 1011h 11 12h Pl Pl Pl Pl Pl Pl Pl Fo Pe r P2 e Pe r P2 1314h 14 15k 15 176 16 17h 17 18h 1819h 19 20h ARO NH 2 223h 23 24h Pl P2 12 13h P P
204. ow in the table The parameters displayed include the Name Nominal Voltage V Shortcut current A Nominal Power Wp Acquisition Cost Operation and Maintenance O amp M Costs per Unit the cost for each one of the panels comprising the PV generator apart from the fixed cost for the panel set expressed in yr Expected Life yrs TONC C Maximum Power Temperature coefficient C and COZ emissions in manufacturing recycling etc kgCO2 equivalent per kWp of nominal power The nominal voltage may be selected from a pop up menu or directly introduced by the user Nominal voltage is the nominal DC bus value for the PV panel so that the panel can correctly charge the batteries If nominal voltage is 12 V the Open circuit Voltage is about 21 V so R Dufo L pez HOGA User Manual 83 that the panels can always charge batteries In some cases the manufacturer do not give the nominal power In these cases you must look for the Open circuit voltage and knowing this value the Nominal voltage can be selected as follows o For Open circuit Voltage between 20 and 40 V gt Nominal voltaje 12 V o For Open circuit Voltage between 40 and 60 V gt Nominal voltaje 24 V Nominal voltage Navigation toolbar The user may click on any table cell to edit the contents move through the table using the arrow keys on the keyboard and the table navigation toolbar see figure below or use this bar to Add or
205. pez HOGA User Manual 66 of lower irradiance on a horizontal surface in Spain in December whose value is about 60 However 1f the system 1s only used in one time of year for example in summer we will have to choose the optimum inclination for this period for example in the case of the figure 1f load consumption was only in summer choose the angle of about 23 or 30 slope Optimize PV panels slope during the optimization of the system If the checkbox Optimize PV panels slope during the optimization of the system is checked the slope of the panels will be a variable to be optimized as the number of panels panel type etc Optimize PY panels slope during the optimization of the system This option is interesting for the systems which include PV array and also available wind turbines or water turbines which electrical production is not stable throughout the year as usual In many of these cases the optimum slope will not be the same as if it were a photovoltaic only system and a priori it is difficult to know For example in a photovoltaic wind power installed in Spain if wind production is higher in winter it 1s possible that the optimum inclination of the panels is not the usual slope for photovoltaic systems where production is maximized in the month of lower irradiance December with optimum inclination 60 but it is possible that the PV slope will be the value to maximize production in another month whe
206. programs 10002 MAC Traditional Chinese Big5 English United States 10003 MAC Korean 10004 MAC Arabic 10005 MAC Hebrew What is system locale Ay Change system locale Default user account settings Apply all settings to the current user account and to the default user profile R Dufo L pez HOGA User Manual 20 All versions need internet connection to verify that the license is active If no internet connection is available HOGA will not run The internet connection is required only to get the current date from the internet and check the validity of the license R Dufo L pez HOGA R Dufo L pez User Manual 21 HOGA User Manual 22 3 INTRODUCING DATA A welcome screen is shown when the programme is open On the Project Menu there is a choice to create a new project open an existing one or quit the application PRO version The first time HOGA asks for a user name and a keys These fields must be filled with the data that the author will send by e mail to the user after the user purchases the license J LICENSE Lo x Username Key 1 Key 2 VALIDATE L Z thse pogam After entering the user name and the two keys clicking on VALIDATE a text field appears where you must specify the email address where you want to receive the activation key R Dufo L pez HE LIC
207. ptimization is available as it is in 1HOGA Other advantage of iHOGA is that the models components financial calculations are more accurate than in HOMER as well as features such as presizing optimization of the slope of the photovoltaic panels etc IHOGA makes use of Genetic Algorithms more information in annex 1 and references 2 5 6 8 9 14 for optimization both for the system components main genetic algorithm and for the control strategy secondary genetic algorithm Genetic algorithms may produce adequate solutions when applied to highly complex problems with very short calculation times These techniques have been applied to a large number of problems in industry often achieving better solutions with shorter times than those for alternative optimization methods IHOGA offers the choice to perform an evaluation of all possible combinations both for components and for control variable strategies This is called the Enumerative Method which does not use genetic algorithms However this approach is usually not feasible since the number of components and strategies may be huge thus resulting in calculation times of the R Dufo L pez HOGA User Manual 12 order of months or even years Genetic algorithms allow for near optimum solutions with relatively short calculation times 8 9 Using Genetic algorithms the computation time can be reduced to less than 0 1 with high probability of obtaining the optimum soluti
208. r values will force the user to use scroll bars in order to view full application screens A ioprowe Double click on the self executable file called iHOGA plus version number The following screen will be shown Setup T WARNING Thit pogam te protected by copprght law ard irhemationa maes Unauthoszed reproduction or distatution of this program or any poron of map end in severe cid and crmnal penalties and wil be prosecuted to the manman extent possible under lew Click on Next A licencing screen will pop up where we must click on Accept A second screen is then shown to select the installation path Click on Continue and the programme will be installed A folder called Projects is available in the installation directory with several examples of hybrid systems Warning The tables of the databases used by iHOGA are stored in folder Tablas in the installation directory It is recommended to copy the directory Tablas and rename it eg Original tables because in the future it is possible we need the original tables R Dufo L pez HOGA User Manual 19 2 2 Running the Application The application may be started e From the Start button Select All Programmes select HOGA e From the Desktop double click on 1HOGA INUGARRESPROS For Greek Chinese Russian and other users whose language uses characters different from English Windows settings must be chan
209. rice Annual Inflation 2 Emizsion Kolosh 3 0 4 Frnax k Fired Cost P Eyr 1000 O Access Toll Price Em hi J Fixed Access T price Eh 01 Hourly Price Price Support Toll applied in Spain Eh Fixed Support T price B E wh O Hourly Price The cost of the support toll vall be added to the E purchased When you select this option an information dialog appears showing the percentage of the whole load which is the maximum allowed value for Unmet load maximum energy which can be purchased from the AC grid This percentage can be changed in the main window in Constraints section R Dufo L pez HOGA User Manual 53 IHOGA E Maximum allowed value for Unmet load maximum energy which can be bought from the AC grid 151 of the whole load You can modify this value in the main window of the software section Constraints You can choose a fixed price for all hours of the year the same price checking the Fixed price kWh checked by default or set a price for each hour or time slots if not check that box Hourly Price button is enabled puncturing a window from which you can enter the price for each hour of the day every day the same or import from file prices for 8760 hours a year or consider hourly periods HOURLY PRICE OF THE ELECTRICITY PURCHASED FROM THE AC GRID Hourly Price Data Eta Hourly all days the same From file 5760 hourly values Import f Draw H
210. rice Et ht J Fixed Access T price Eh 01 Hourly Price Support toll You can define a support toll by a fixed price or by hourly price as explained before The support toll is applicable in Spain this toll 1s applied to the electricity that is generated by the own system and is consumed in the own system for example electricity produced by the PV panels which is consumed by our loads and is not injected to the AC grid This cost will be added to the cost of purchasing energy from the AC grid Price Support Toll applied in Spain ek hp Fixed Support T price EXE O Hourly Price The cost of the support toll will be added to the E purchased Sell excess energy to AC grid excess energy produced by the system components ell Excess Energy to AC grid J Fised Price Eh 10 12 Hourly Price Pr sell pr purchase s 1 Annual Inflation 42 3 Max Power kM 100 Energy Transfer Toll Ek Fixed Transfer T price Ek 0 05 Hourly Price Self consumplion and Met Mettenng No Met Mettering sd Surplus DC energy must be transferred to the AC side using the inverter with a certain energy loss due to the limited efficiency of this device Therefore any energy available for sale to the R Dufo L pez HOGA User Manual 56 AC grid shall be smaller than the original DC surplus energy If the surplus is larger than the maximum inverter capacity it will not be possible to sell this excess energy by transferring i
211. ries in the next column Imax charg DC A and the efficiency of the charger into the next column Minimum and Maximum DC voltage operation The nominal DC system voltage set on the main screen should be between these two values If the bi directional inverter includes the PV battery charge controller the bi di inverters may include management of renewable photovoltaic and or wind energy in that case you must choose OK in the column PV Batt Controller if the controller is MPPT you must choose MPPT In that case in the next column Pmax_ren W you must set the maximum input power of whole renewable system PV array and wind turbines Additional data must be provided on efficiency or performance as regards output power as a percentage of nominal power These values are displayed in the performance chart Inverters can be added individually from the database using the Add from database button Also by clicking on Include only VDC suitable from family button 1t can be forced to show up at the table just the inverters of a family which are suitable for the nominal DC voltage of R Dufo L pez HOGA User Manual 113 the system The inverters shown will be the ones of that family suitable for the VDC voltage of the system but only the ones which are included in the selection of the groupbox on the right without rectifier charger or with rectifier without PV controller or with rectifier and P
212. rom the AC Grid Charge and Discharge Battery Energy Electric Energy Used by the Electrolyzer Energy Generated by the AC Generator and Energy Generated by the Fuel Cell As mentioned above all of these energy values are annual values Etotal k hiy JErenks yr Epp ur Ek PER EW yr E excess kWh yr E sell khur E buy kW tr E ch bat kW h yr he 1324 dala 2913 0 O 303 0 O T 1324 2732 2732 0 O 1171 D 0 Al 1324 2234 234 0 e50 0 7 7 1324 2513 RE 0 302 0 T 1324 Cide arde 0 0 1171 0 T 1324 3072 3072 0 0 1443 0 T 1324 2913 2913 0 0 302 0 0 T 1324 2234 2234 0 0 G45 0 T 1324 2792 2732 0 1171 0 0 T aan n Additional columns in black provide data in hr yr for battery charge discharge operation of the AC generator the electrolyzer and the fuel cell as well as battery useful lifespan Life Bat years Hours disch Bat Hours Electrol C Fuel Gen 8 0 C Fuel FC t yr JE Buy tyr JE Sell tyr or 18 36 26 6 gro 0 0 13 46 0 D 0 E 13 2604 5280 0 0 239 0 0 O 74 18 63 erdl 9320 0 0 36 99 0 0 al 23 13 56 2673 5273 0 0 11 47 0 0 0 20 2538 5286 0 0 0 0 0 0 0 18 06 2564 dera 0 0 0 0 0 0 O aU 6x0 dede 0 0 gar 0 0 0 bs 13 45 ofa T326 0 0 FER 0 0 E 20 2601 5203 0 0 1 5 0 0 0 E Ed 4 4 1 System Simulation Screen Click on SIMULATE in the row of the results table corresponding to the solution you want to see the simulation The simulation screen opens All 1 ho
213. s There are 12 control variables Once the values have been estimated for all variables for each hour the system control is subject to certain conditions in order to minimize total system cost for the case of mono objective optimization or to minimize both costs and levels of CO or unmet load for multi objective optimization As a fundamental premise for control the energy produced from renewable sources photovoltaic wind based and or hydraulic will be used to feed the loads as this energy is free once the components have been purchased Besides preference will be given for every energy source renewable or otherwise to feed the loads on their voltage bus DC or AC External consumption of Hz will be covered by the H tank Should this not be enough additional energy may be generated with the electrolyzer Should more energy be produced from the renewable sources than that which is needed for consumption the remaining energy will be used to pump water to the water tank as much as possible if water consumption from water tank previously pumped is modelled in the project Once the remaining energy has been used in pumping water if there is remaining energy this energy which we will call Ponarse would be used to charge the batteries or to generate Hp in the electrolyzer This process will be called CHARGE The choice will depend on the cycling costs of the energy in the batteries and on the electrolyzer The
214. s bus de Wmax_p_ panel grid connected systems Data Vmax p panel Vnominalpanel 1 475 Consider effect of Temperature Data of ambient temperature C E Fiz M18 420 M25 J30 J 32 430 528 Do Nile ODS Monthly average sunny hours From file 8760 Hourly values E Draw Efect of ambient temperature The effect of ambient temperature Tamb C can be taken into account by checking the box Consider effect of Temperature and entering monthly average data or by importing data from file 8760 values including files generated with Windfreedom software Considering the effect of temperature the internal cell temperature Tc is calculated by Tc Tamb G TONC 20 800 After calculating the internal temperature of the cell the power generated by the PV generator 1s calculated by P Pn G 1 Ct 100 Tc 25 Npaneles_serie Npaneles_paralelo FS Where Ct is the Maximum Power Temperature coefficient C PV generator connected to AC bus You can define that the PV generator is connected to the AC bus by checking the chekbox PV generator is connected to AC bus it has a own inverter PY inverter data In this case the PV generator will have its own inverter The data of this inverter is shown by R Dufo L pez HOGA User Manual 87 clicking PV inverter data button There is shown that the cost of the inverter must be included in the cost of the PV generator if you have defined whole PV generators I
215. s a percentage of the maximum size of the H tank The larger the tank the less precise this variable will be In this case the value of the HyTANK setpoint may be larger than the tank size calculated by 1HOGA Additional estimations must be made of the tank load in kg as well as of the expected lifespan and the operation and maintenance costs for the tank R Dufo Lopez HOGA User Manual 124 3E H2 COMPONENTS DN a gt gt o e 7 Fuel Cells Electrolyzers HZ Tank Acquisition cost 1000 7 kg of max capacity Max size allowed 10 kg kg at the beginning of the simulation O Lifetime 25 years Operation and Maintenance Cost 10 E year 4 FUEL CELL ELECTROLYZER H2 TANK Annual Inflation Rate for Fuel Cells Electrolyzers and 20 Max Variation of Fuel Cells Electrolyzers and HZ Tanks Cost e g foran eg HZ Tank Cost expected 60 reduction on current cost introduce EDS 72 Limit ls reached in 4 1 years R Dufo L pez HOGA User Manual 125 3 16 HDI and Job creation Pressing the button on the main screen HDI and Jobs the following screen appears HE HDI and Job Creation HUMAN DEVELOPMENT INDEX JOB CREATION OF DIFFERENT TECHNOLOGIES Number of persons NP E Number of jobs created per GWh HDI 0 0978 x LN Eperson 0 0319 Rojas 2012 Photovoltaic 0 87 AC Generator 0 14 Eperonjkw hyr Total load per person and year Wind 0 17 Fuel Cell 0 12 Eperson k4 hep
216. s must be from the same family voltage data refered to 2 Y cells Curve of Corrosion speed vs potential of positive electrode vs Hg Ha2504 ref eed ys potential of positive electrode vs Ha Ha2504 ref Open circuit voltage at full charge UO 2 1 Y A ee Ruestschi 2004 Ks in micraA em2 0 6 4 Gradient of change in OCY with state of charge g 0 1 Y 15 0 8 45 14 Initial effective internal resistance charge ro_c_0 0 43 ohm Ah 035 5 E SS 124 Initial effective internal resistance discharge ro_d_0 0 38 ohmAh 1 6 11 DU Resistance representing charge transfer process which depends on SOC Me 0 36 11 85 8 10 b D 9 Resistance representing discharge transfer process which depends on SOCC Md 0 29 112 5 S 8 f g 7 Normalized capacity of battery charge Ce 1 001 114 25 el Normalized capacity of battery discharge Cd0 1 642 118 gt Sf Normalized reference current for current factor ref 0 1 A amp h 1 25 25 i Height of battery z 20 cm 7 2 7 06 07 08 09 1 11 12 ES 14 Corrosion voltage of fully charged battery without current flow Ucor0 1 75 Y F T Potential of positive electrode V vs ref Hg Hg2504 Nominal Voltage for Gassing Ugas0 2 23 Y Normalized Gassing Current Igas0 20 m4 1004 SOC for considering full charge in order to set fsoc 1 and obtain current for factor fl 0 99 When Max Capacity lt Nominal Capacity use this SOC in terms of Max Capacity Minimum state of charge for bad c
217. s possible to select only some of all available variables Variables not selected here will not be optimized In the example shown in the figure below all available variables will be optimized except for SOC sip sen Which was not selected The value will be set to SOC pin or any other value as shown on the screen when clicking on Fix Variables The Accuracy for Variables parameter plus one is the number of possible values that can be taken by a variable Larger values for this parameter will ensure higher accuracy but also many possible combinations for variable values Optimization may thus take longer Important If there are many possible combinations of components and control strategies LHOGA will need a lot of time to do the optimization Combinations of components are more important than control strategies in the Net Present Cost Clicking on the Fix Variables button will open a new screen This will allow the user to select variables not checked in the previous screen i e variables not to be optimized A choice is provided here between a value calculated by the programme or one assigned by the user R Dufo L pez HOGA User Manual 41 Non Optimizable Control Variables fixed value Pmin_gen Pmin_FC H2TANKstp_gen o Pl gen Pisce P2 C SOCstp_gen SOCstp_FC SOCmin s Manufacturer s SOCmin s s C Set value SOCmax 50 E a Peritical gen Peritical FC Plimit charge f O
218. s range battenest hidrogen 40 generator 3 days 14 if there is AC generator or fuel cell using external fuel or purchasing unmet load from AC grid te allowed number of days range infinitum Nominal capacity of batteries bank Ah lt 0 y shortcut current of PY generator current from Wind Turbines gruop at 14 s 4 e if there is AC generator or fuel cell using external fuel or purchasing unmet load from AC grid iz allowed do not take into account this constraint Minimum renewable fraction d Maximum Levelized Cost of Energy 130 kwh Maximum Unmet allowed value described above Minimum number of days range sum of autonomy that give the batteries if any plus autonomy gives storage of hydrogen if any plus autonomy gives the AC generator 1f any If AC generator eg Diesel exists 1t is considered by default that autonomy is infinite unless you uncheck the 1f there is AC generator or purchasing unmet load from AC grid is allowed number of days range infinitum The same is seen 1f fuel cell is used and H2 is externally purchased It is also considered infinite autonomy if purchased to AC unmet load this is specified in the load AC grid screen see section 3 2 If a combination of components and control strategy does not meet minimum autonomy this combination is discarded To calculate the days range the energy consumed during one day concerns of average consumption energy consumed during the year divided
219. s reaches very high values this may be the case with Pl E H tank and Hz TANK setpoint Uncheck the parameter with the high value for easier visual analysis The hourly data on display may be exported to an ASCII file by clicking on Save Data Additional information is provided under the chart for components and strategies used for each simulated system Also information of the months and the concrete days in which the system does not cover the whole load is shown R Dufo L pez HOGA User Manual 151 You can change the number of days to be visualized in the screen for example in the next figure there are 30 Days displ this example of simulation corresponds to a system different from the simulation shown before 3 SIMULATION B 0 AS E O Lo jas Hourly simulation Hydrogen detailed AC Generator detailed Water load Hourly values separately Monthly and annual Average Power Monthly values Annual values Simulation of 1 year All the years are the same 12 13 14 15 16 17 18 January lt r e 4 al COMPONENTS ENERGY Wh BATTERIES ENERGY Wh a 19 20 21 22 23 24 25 26 27 28 29 30 Days displ Unmet Load Water tank Wh from pumpling Water pump E Pmax input Inverter Discharge Batteries 7 E to supply batt 7 E max disch batt Charge Batteries Wind Turbines Hydro Turbine AC Generator P max Gen F E m
220. screens once defined as discussed below can be added to the database tables pressing the button Add components from the project Add components from the project PY Panels table R Dufo L pez HOGA User Manual 82 3 7 PV panels The photovoltaic panels screen may be accessed by clicking on PV panels Components area or by selecting PV panels in the Data menu The software allows the user to modify eliminate or add PV panels ik PV PANELS Lo E amt So Add PY panel Zero Add PY panels family SiM12 Atersa X CO2 emissions Nominal Shortcut Nominal Acquistion O amp M Cost ieee Sie a ER PEA Voltage current power Cost unit 1 1 25 49 0 2 gt aSi12 Schott ASI100 12 6 79 100 Name Fixed cost of Operation and Maintenance 40 yr The Loss Factor is defined as the increase in power required for the PV generator to compensate for any loss from shadows orientation ditt in panels etc The Loss Factor usually has a value of between 1 1 and 1 3 Loss Factor selected 1 2 PY battery charge regulator includes Maximum Power Point Tracking MPPT Pv generator is connected to AC bus it has a own inverter Annual Inflation Rate for PY Panels Cost Max Variation of Pt Panels Cost e g for an expected 70 reduction on current PY panels cost introduce 0 The limit is reached in 59 6 years mra PV panels data Each PV panel corresponds to a r
221. sed by clicking on AC Gen Components area or selecting AC Gen in the Data menu AC Generators include all sorts of generating sets operated with diesel petrol biomass hydrogen and other fuel types Generators can be added from database Ye AC GENERATORS Sn lt e An a mm A a el n s Add from Database Cero Rated Acquisition Fuel co2 power Pn Cost O amp M Cost Lifespam P min infl rate Emissions A B Name wa E of Pr E ud kg CO2 ud ud kWh ud kwh 0 0 30 Diesel litro 0 0 0 0 246 0 08145 Diesel 1 9kVA 1 9 800 30 Diesel litro 13 10 3 5 0 246 0 08145 Fuel curve coefficients Equivalent CO2 emissions geneartor manufacturing 215 kg CO2 equiv 7 kVA rated power Generator runs all the time AC grid reference Consumption litro h Pn kW B P kw A Diesel 1 9kVA fuel Diesel co AC Generator Availability o a o ha o ba Fuel consumption ud h o 1 Output power KW AC Generators data Data must be introduced for each generator on Name Rated Apparent Power kVA Acquisition Cost Operation and Maintenance Cost h Expected Lifespan h Minimum Recommended Power by manufacturer as a percentage of nominal power Fuel Type choices provided include Diesel Petrol Ethanol Methanol Natural Gas Propane Biogas or H2 Fuel Units litre kg m Normal Fuel Price unit Annual Inflation Rate f
222. sizes and number of generations at the expense of longer calculation times In general terms the best choice is a large population rather than a large number of generations For populations of a small size 1t will be difficult to find an optimum system with breeding or mutation regardless of the number of generations used For the principal algorithm these values must depend on the degree of variability and on the maximum number of system components allowed PV panels batteries and wind turbines For larger component variability large populations are necessary For the secondary algorithm this depends on the control variables to be optimized and on the degree of accuracy required for the optimization process For a large number of variables a larger population will be required For higher accuracy a larger population will also be required since many values will be available for each variable as an example for a value of 50 in accuracy variables will take 50 discrete values in 2 steps Number of generations must be 15 or 20 Population must be greater than 0 003 of all the combinations Mutation rates are usually within 0 5 1 Breeding rate is usually 70 90 10 NCP is displayed with a value of infinite INF and a screen is shown at the end saying No solution fulfills system requirements In this case the system cannot find any solution which meet all constraints If the unmet load constraint is not achieved
223. solated hybrid systems minimizing costs and pollutant emissions Renewable Energy 31 14 pp 2227 2244 3 Dufo L pez R Bernal Agustin JL Contreras J 2007 Optimization of Control Strategies for Stand Alone Renewable Energy Systems with Hydrogen Storage Renewable Energy 32 7 pp 1102 1126 4 Dufo L pez R Bernal Agustin JL 2008 Influence of mathematical models in design of PV Diesel systems Energy Conversion and Management Volume 49 Issue 4 April 2008 Pages 820 831 5 Dufo L pez R Bernal Agustin JL 2008 Multi objective design of PV wind diesel hydrogen battery systems Renewable Energy Volume 33 Issue 12 December 2008 Pages 2559 2572 6 Bernal Agustin JL Dufo L pez R 2009 Multi objective design and control of hybrid systems minimizing costs and unmet load Electric Power Systems Research Volume 79 Issue 1 January 2009 Pages 170 180 7 Bernal Agustin JL Dufo L pez R 2009 Simulation and optimization of stand alone hybrid renewable energy systems Renewable and Sustainable Energy Reviews Volume 13 Issue 8 October 2009 Pages 2111 2118 8 Bernal Agustin JL Dufo L pez R 2009 Efficient design of hybrid renewable energy systems using evolutionary algorithms Energy Conversion and Management Volume 50 Issue 3 March 2009 Pages 479 489 9 Dufo L pez R 2007 Dimensionado y control ptimos de sistemas h bridos aplicando algoritmos evolutivos
224. t to the AC bus In this case the amount of energy sold may be much smaller than the excess energy produced You can select for the energy sold to the AC grid a fixed price checking Fixed Price kWh by default or a price proportional to the purchase price checking the Pr sell pr purchase x If you check this box the selling price will be set for purchase same for all hours or not multiplied by the factor of the box Max Power kW refers to the maximum power of the energy to be sold to the AC grid If the excess power during an hour is higher than this value the energy sold during this hour will be limited to this value Energy Transfer Toll You can define an energy transfer toll by a fixed price or by hourly price as explained before The energy transfer toll is applicable to the electricity injected to the AC grid and this cost will be substracted to the incomes of selling electricity to the AC grid Energy Generation Toll Transfer Toll kwh Fixed Transfer T price Ek 0 0005 Hourly Price Taxes We can define the total tax in for the costs involved in the energy bought to the AC grid including the cost of the energy transfer toll for the energy sold and the total tax in for the price of the energy sold to the AC grid Total tax for electricity costs bought tolls 2 0 Total tax for electricity sold Et 0 Net Mettering only in PRO version As default No Net Mettering is selecte
225. t be set default 500 If set to a very low value the distribution achieved may not seem like much to a Gaussian distribution The analysis can take into account the probability gaussian distribution of average annual values of Average consumption Irradiation only if you have selected that may have photovoltaic panels on the system Wind only if you have selected that may have wind turbines on your system Water flow only if you have selected that may have water turbine in the system Mean values are those who have fixed in their screens of load and resources Standard deviations are to be fixed in each case in this screen For each case it 1s shown in red the probability distribution curve taking into account the number of series N to be set default 500 and in green the ideal curve Gaussian probability distribution If a small value is set for the number of sets for example N 50 it appears that the actual distribution can be very different from the ideal figure below which is not recommended Analyze variability of load Analyze variability of irradiation DAILY LOAD AVERAGE VALUE IRRADIATION AVERAGE VALUE Mean 3 63 kWh day Mean 4 65 kWh m2 day E Standard Deviation 0 3 kwh day Standard Deviation 0 2 kwh m2 day Mean 3 578 Std Dev 0 313 kWh day Mean 4 688 Std Dev 0 216 kWh m2 day Maximum 4 25 Min 2 8 Kw h day 3 4 Maximum 5 26 Min 4 2 kwh m2 day Average Load kWh day Proba
226. the air density at this altitude Height avobe sea level 247 Mm Aur density at that height i 1 196 kgm R Dufo L pez HOGA User Manual 91 It also represents the power curve for this altitude green curve The density is calculated according to the International Standard Atmosphere ISA earth atmospheric model created by the International Civil Aviation Organization assuming that in an altitude up to 11 000 feet above sea level the temperature decreases linearly with altitude according to the equation T T LH where T is the temperature K at the altitude avobe sea leve H m To is the temperatura at height of sea level 288 15 K and Lis the variation rate of temperature vs height L 0 0065 K m Atmospheric pressure and air density are calculated as follows EM RL port T O P M P A SI 1000 R T where T Temperature K P Pressure Pa p Density kg m H Height above sea level m Pe Standard pressure at sea level 101325 Pa E Standard temperature at sea level 288 15 K g 9 80665 m s L the variation rate of temperature vs height 0 0065 K m R Ideal gas constant 8 31432 J mol K M Molecular weight of dry air 28 9644 g mol Considering the ideal gas law AS D 315 where po1s the air density at sea level 1 225 kg m R Dufo L pez HOGA User Manual 92 Is obtained by substituting the relationship between the density of the height H and the density at sea level gM
227. the field of education or training You agree not to use this software in any other field including any kind of professional business commercial or research fields for these fields must purchase the license PRO EDU version is not permitted in projects engineering work installation work and in general in any case in which there is derived economic transactions EDU version is not permitted in research fields If you agree with the conditions of this license for this sofware you can install it If you do not agree do not install this software or uninstall it R Dufo L pez HOGA User Manual R Dufo L pez HOGA User Manual CONTENTS 1 INTRODUCTION AND OVERVIEW ssssssss sss s s s s s s ss t s sss s z sss sse s sz z s s s esse s 8 SS AOpen A E ada aa Saddi anos So Kek ts i 13 IAN A NPR DURE e E A 15 2 INSTALLING AND RUNNING THE APPLICATION 18 A EE RR A egek 18 D2 UNS DE APD AMON oda 19 INTRODUCING DA TA cited 22 E AAA A A DARREN 29 JLL GENERAL DATA ab ssssscssssseacseasuvosaassseannpedsaseeassedsandsagseantsnaceanaseaaeaaessedeases 30 SEZ OOP A IVE DO AD e S E EEE EEE 36 3 13 CONTROLCSIRAITEGIES AD sapata n rni neie ene E ENE EE ea OESE 38 391 4 FINANCIAL DATA CD secarse EEA E A E 41 Die IM di A A baz ele s sz ares intsade sita ainsi 42 AA AGC spr cxe testes aber aimed Ei a qa 43 3 1 7 Buttons and Menus on the Main Screen ccccccccccnnnnnnnnn
228. thms to optimize the combination of components in this time Maximum execution time O h 1 min MAN ALG SEC ALG NUMBER OF CASES Ea TIME EXPECTED OPTION 1 Ev l ALL EVAL ALL 348480 100 1h 5 OPTION 2 EVAL ALL GEN ALG 14287680 400 Sdays 7h OPTION 3 GEN ALG EVAL ALL 2989 0 86 Oh 0 60 OPTION 4 GEN ALG GEN ALG 122549 ae Oh 40 50 When the optimization starts a progress bar 1s shown at the bottom of the screen with data on cases evaluated time elapsed and time left Click on Cancel to stop at any point R Dufo L pez HOGA User Manual 138 Project Data Calculate DataBase Report Help LOAD 7 AC GRID GENERAL DATA OPTIMIZATION CONTROL STRATEGIES FINANCIAL DATA RESULTS CHART RESOURCES SE ae F Multi objective optimization Total No of cases evaluated 1688 Time 33 COMPONENTS 1 2 3 4 5 6 7 GENERATIONS Show Sketch Total Cost NPC Emission kgC02 yr Unmet kwh yr Cn h Isc dc 8 Ren Cost E kwh Simulate Report _ OTHERS AUX 1 42391 275 0 0 67 95 100 1 28 SIMULATE REPOI 7 2 42391 275 0 0 6 7 95 100 1 28 SIMULATE REPOI DC Voltage 24 3 21701 135 0 0 INF ZA 991 0 65 SIMULATE REPO AC Voltage 230 Y 4 21701 135 0 0 INF 74 991 0 66 SIMULATE REPOI 5 21701 135 0 0 INF 74 991 0 65 SIMULATE REPOI 6 21222 176 0 0 INF 59 968 0 64 SIMULATE REPO Energy Storage 4 days range 7 20824 133 0 0 INF 5 3 988 0 63 SIM
229. total cost NPV emissions unmet load photovoltaic energy wind power etc For each result HOGA calculate the average of all these simulations and this is the value that will consider the program to compare with other combinations of components and strategies and to be displayed in the results table and in the reports After the optimization for each combination of components and control strategy in the simulation see section 4 6 1 1t will be shown the series of consumption radiation wind and water flow corresponding to the case that we have chosen here from the AVERAGE cases AVERAGE Std Dev AVERAGE 3 Std Dev AVERAGE Std Dev or AVERAGE 3 Std Dev In the simulation show the case obtained with the following data Irradiation Wind Speed Water Fow Average Average Average Average Std Dev ude hourly variability Average 3 Std Dev In Average Std Dev in the last two charts show the probability distribution of Average Std Dey The default is to simulate the average case but other cases can be set to simulate For example we can set for load consumption AVERAGE STD DEV and for irradiation data and for wind flow the AVERAGE STD DEV This combination would be rather pessimistic as we would consider that consumption is somewhat higher than average while resources are somewhat smaller and when viewing the simulation you can see if it meets the demand every day of the year etc
230. turing recycling etc kg X WIND TURBINES senmo SO ee ee ee Le E junta AddaWind Turbine Zero Wind Turbines connected to bus o Defined in Type D All to DC bus o All to AC bus Add a Wind Turbines family Southwest GENERAL DATA OUTPUT POWER 44 vs WIND SPEED Name Type Cost C Repl C O amp M Eyr Lifetime yr Height m Emis CO2 kg Im s 2m s 3m s 4m s Sms Emis Bmis 10m s 12m s D DC 955 630 50 10 9 300 0 32 126 281 505 1165 2137 380 5 Whisper DC 2065 2315 3000 0 2 25 55 150 204 600 839 Zero DC 0 0 0 0 0 0 0 0 0 0 0 0 Battery charger is included For a DC type wind turbine with voltage different from 48 Y DC losses at the DC AC converter will be included in the power curve Surface Roughness Class 1 5 P Length 0 03 m Agricultural open area without fences neither hedges and with very dispersed buildings Only smoothly rounded hills Height avobe sea level 247 m 012 3 4567 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 Air density at that height is 1 196 kg m3 WIND SPEED m s a E E P in standard conditions sea level P at height above sea level Annual Inflation Rate expected Max Variation of Wind Turbines Cost expected e g for an expected for Wind Turbine Costs 1 A 35 reduction on current Wind Turbines cost introduce 35 35 Limit is reached in 42 9 years Additional data must be introduce
231. uel cell and the simulation screen I see that in a certain time the fuel cell should be used but it is not used why The fuel cell needs a minimum hydrogen mass flow to start generating electrical power output If the amount of hydrogen available in the tank is not enough to cause the minimum mass flow during that time the fuel cell is not used ie it does not work See section 3 15 1 13 How to optimize systems selling electricity to the grid without load consumption In the window of load consumption LOAD AC GRID choose for data source Load profile and select the profile NO LOAD On the same window tab PURCHASE SELL ENERGY check the Sell excess energy to AC grid On the main screen of the software General data tab More Constraints button set O days for Minimum Number of Days Range and 1E10 for Maximum Levelized Cost of Energy After optimizing the solution with lowest Total Cost NPC will be the best If the total cost NPC is negative it implies that the system 1s profitable 14 How can I update HOGA In www unizar es rdufo R Dufo L pez HOGA User Manual 187 R Dufo L pez HOGA User Manual 188 REFERENCES 1 Dufo L pez R Bernal Agust n J L 2005 Design and control strategies of PV Diesel systems using genetic algorithms Solar Energy Volume 79 Issue 1 July 2005 pp 33 46 2 Bernal Agustin JL Dufo L pez R Rivas Ascaso DM 2006 Design of i
232. ur intervals in the year are included here ientze Cost Ef kwh Simulate Report Costs HDI fiobs Mo 2 JEM 0 45 SIMULATE REPORT COSTS 0 5705 0 0735 3 365 1 46 SIMULATE REPORT COSTS 0 5705 0 0735 3 986 0 46 SIMULATE REPORT COSTS 0 5789 0 0735 Hourly Simulation tab In the simulation screen there are 8 tabs to see the results of the simulation R Dufo L pez HOGA User Manual 149 A o Eso TE TAO TE SES Hourly simulation Hourly values separately Monthly and annual Average Power Monthly values Hydrogen detailed AC Generator detailed Water load Simulation of 1 year All the years are the same By default the Hourly Simulation tab is shown however you can click the another tabs to see the results in other formats monthly annual 3 SIMULATION Hourly simulation COMPONENTS ENERGY Wh 4 January BATTERIES ENERGY Wh C COMPONENTS ENERGY W h E FJ A Excess Energy Unmet Load Water tank fuh from pumpling Water pump 7 Pmax input Inverter Discharge Batteries Ir E to supply batt 7 E max disch batt Charge Batteries F E max charge batt Wind Turbines Hydro Turbine AC Generator P max Gen PY panels Electrolyzer E H2 tank HHY H2 Fuel Cell E to supply FC E max FC E Bought to AC grid E sold to AC grid Plimit Charge Fe E P1 P critical Gen P critical FC E Pmi
233. ve objectives will be optimized Multi Objective 2 5 6 11 15 16 may oppose Total Cost NPC to CO emissions or Total Cost NPC to Unmet Load In the latter case a maximum permitted value must be introduced You can also define Another type of optimization in which case it can be included as objectives the Human Development Index HDI and Jobs Creation maximize them If Another a panel appears on the right where you can define the multi objective optimization double triple or five objectives R Dufo L pez HOGA User Manual 37 In any of the two cases objectives to achieve may be mutually counterproductive in many situations Several solutions will be provided by the system some of them offering the lowest costs and some others providing the lowest level of emissions or unmet load Solutions or individuals are sorted by the application with the best ones at the top Solutions are better when they are dominated by fewer alternative solutions a particular solution is dominated by others when those provide better objectives in our case better solutions offer a lower NPC and lower levels of CO emissions or unmet load Thus the best solutions available will not be dominated by any others with the next best solutions dominated by 1 by 2 and so ON All non dominated solutions will have the same degree of probability to breed as none of them is better than any of the others The same argument applies to al
234. ves of Ruestschi or Lander At the bottom there must be set the speed parameter corrosion during flotation life in the units marked on the curve of the corrosion rate vs the potential of positive electrode Lorrosin speed during floating life Corrosion speed for folating life data 2 Calculate Or the corrosion rate during flotation life can be estimated Corrosin speed during floating life Obtain floating lite corrosion speed coefficient from Lander or Ruetschi curve using Corrosion speed for folating life data 2 ai Polarization of positive electrode mm 80 a Calculate Floating voltage 1 2 21 Potential of positive electrode 1 637 Y 1 215 ve Hg Hg2504 ref electrode Corrosion speed coefficient 2 242 micrad cme If the calculation is using Polarization of positive electrode mV the parameter of floation corrosion rate 1s calculated based on curve of Ruetschi or Lander 3 10 5 Batteries life models The lifespan for the batteries can be estimated by the Equivalent Full Cycles or by the Cycle Count or Rainflow method according to Downing s Algorithm Downing and Socie 1982 25 Lifetime calculation using model Rambo cycle counting Modified Equivalent full cycles En el caso de Rainflow si se marca la casilla Modificado aparece al lado una casilla donde debe indicarse el Factor rainflow 0 1 For Rainflow if you tick the Modified checkbox it appears a box where you should i
235. vious environmental benefits However this technology is currently rather costly so no massive facilities have been deployed though the situation may be expected to change in the future Fuel cells may alternatively use fuel not produced by electrolysis H2 methane etc but acquired from other sources The advantages of hybrid over single source systems are clear but optimized calculations for the former are highly complex This complexity is due to the extremely variable degree of availability of renewable resources solar irradiation wind hydraulic as well as to the variability of energy demand Besides there is a large number of variables which may have an influence on system optimization and some system components show non linear behaviour A great many different solutions are feasible for any given hybrid system PV panels wind turbines hydraulic turbines batteries AC generators fuel cells electrolyzers inverters and variables for control strategy Optimization methods based on classical mathematical techniques are therefore particularly hard to apply e g as with mixed integer programming There exist software 7 9 10 such as HOMER 10 developed by the NREL National Renewable Energy Laboratory in the U S carry out optimization by trying out all possible combinations For a significant number of feasible solutions however calculation times may be enormous Control strategies are too simple and no in depth o
236. w Project Data Calculate DataBase Report Help LOAD 7 AC GRID j _ LOAD AC GRID GENERAL DATA OPTIMIZATION CONTROL STRATEGIES FINANCIAL DATA RESULTS CHART RESOURCES Multi objective optimization Total No of cases evaluated 312 Time 5 SOLAR r COMPONENTS Y PY PANELS BATTERIES Solution sorted from best to worst 7 INVERTERS Y AC GENERATOR E Show Sketch A t Total Cost NPC Emission kgC02 yr Unmet kwh yr Cn h Isc dcJ 4 Ren Cost E kwh Simulate Report _v OTHERS AUX 0 0 5 3 0 63 SIMULATE 0 64 SIMULATE 0 64 SIMULATE 0 65 SIMULATE 0 65 SIMULATE 0 65 SIMULATE 0 66 SIMULATE 0 66 SIMULATE 0 66 SIMULATE DC Voltage 24 V AC Voltage 230 Y PRE SIZING Energy Storage 4 days range Max bat parallel gt Cn min Max PY pan parallel gt P min Max wind t parallel gt P min on On ek wo NH Oo ooo ceo coc ec amp Slo ro ola o a a 4 HDI and JOBS Hybrid system Best solution Sensitibity Analysis COMPONENTS 2s x 9p PY panels of 135 W slope 60 77 12s x 1p batteries of 390 amp h 77 AC Generator of 1 9 kVA 22 Inv 500 VA 22 Rect 493 W 2 Unmet load 0 NPC 20824 0 63 k Wh Probability Analysis STRATEGY LOAD FOLLOWING P1gen INF Pmin_gen 570 W Peritical_gen OW SOC setpoint gen 20 SOC min 20 3 CALCULATE Save Table as Excel If a soluti
237. week and on weekends clicking the Availability of AC Generator By default availability 1s total If you want some hours to be not available you must deselect the checkboxes for the corresponding hours R Dufo L pez HOGA AC GENERATOR HOURLY AYAILABILITY Monday Friday 9 0 52 1 W 2 Y 3 Y 4 7 5 7 W 7 Y 8 fw 9 54 10 52 11 7 12 7 13 W 14 7 15 7 16 9 17 7 18 7 19 W 20 7 21 W 22 wf 23 Th 2h 3h 4h ah Eh Th ah 3h 10h 11h 12h 13h 14h 15h 16h 17h 18h 13h 20h elh 22h zah z4h R Dufo L pez Weekend 7 0 2 1 W 2 7 3 W 4 7 5 9 6 o 7 4 8 7 3 4 10 52 11 17 12 7 13 114 7 15 W 16 W 17 7 18 7 19 7 20 E 21 Y 22 7 23 Th 2h 3h 4h oh Eh fh oh 3h 10h 1h 12h 13h 14h 15h 16h 17h 18h 13h 20h elh 22h 23h 24h User Manual 117 HOGA User Manual 118 3 14 Fuel Cells and Electrolyzers The Fuel Cell screen may be accessed by clicking on H2 F C Elyzer Components area or selecting H2 F C Elyzer in the Data menu Three tags are displayed providing access to Fuel Cells Electroloyzers and the H tank Two configurations are available e A Fuel Cell using Hz produced in the electrolyzer and stored in the H5 tank e A Fuel Cell us
238. wer required by the loads as well as all the inverters available for this value A warning message will be displayed when no inverters meet the power requirements R Dufo L pez HOGA User Manual 114 Additional data is provided on average hourly AC consumption power and on the percentage of this power as referred to the nominal power of the inverter selected This provides an indication of the average efficiency of the inverter 1HOGA will use this value to calculate some of the parameters required for the control strategy However it is the real efficiency of the inverter which will be used for hourly calculations of system energy balance The real efficiency depends upon the output power as shown in the efficiency chart When the default option is not checked the inverter will not be selected as the smallest device with enough capacity to supply maximum AC load In this case 1HOGA will try different inverter combinations in order to calculate the best solution for the hybrid system All inverters will then be considered to be equivalent although low power inverters will yield unacceptable solutions with a certain degree of unmet energy Efficiency is calculated for each inverter related to average AC consumption power This will in turn be used by HOGA to calculate the different parameters required by the control Strategy R Dufo Lopez HOGA User Manual 115 3 14 AC Generators The AC Gen screen may be acces
239. when very high loads are present for the hybrid system for a town or a city for example 1t may be best to introduce data for wind turbine sets on each row 1 e sets of wind turbines in parallel Thus each table row would correspond to one wind turbine set e g one 10 kW group at 14 m s another 20 kW group at 14 m s etc In this case the following values would be introduced on the main screen Wind Turb in parallel Min 1 Max 1 Press OK to return to the main screen R Dufo L pez HOGA User Manual 94 3 9 Hydraulic Turbines The Hydraulic Turbines screen may be accessed by clicking on Hydro Turbines Components area or selecting Hydro Turbines in the Data menu e Lo ES JE HYDRO TURBINES gt E Add from Database Zero v H a a HYDRO TURBINE GENERAL DATA EFF TURBINE vs FLOW of F nom Nome Type Power kw Flow max s Min height ml Max height m Cost Litespam yr C O amp M yn 0 10 20 30 40 50 60 70 80 80 100 7 12 18 D Turgo500 AC 0 5 1450 30 150 D 0 0 0 0 0 OD 46 48 48 485 Check that turbines are suitable for an available head of 13 m Available head must be between Min height and Max height of the turbine For DC Hydro Turbines with a DC AC converter available this will be E 2 included in Electrical Generator Efficiency Turgo500 Q 7 l s Pnom 0 5 kW P m x salto m x 18m 0
240. wn below information will be provided here on the number of cases to be evaluated This number depends on the user selection GENETIC ALGORITHM or EVAL ALL for both algorithms this message box is also displayed towards the central part of the main screen whenever the cursor 1s moved over the optimization parameters or maximum and minimum components or the control variables areas There are 4 possible combinations option 1 through option 4 with the option selected highlighted in red Figures are displayed for the number of cases to evaluate and the time estimated for the simulation provided the speed test has been carried out beforehand press CALCULATE and CANCEL after a few seconds Secondary algorithm optimization of control strategy On the SECONDARY ALGORITHM OPTIMIZATION OF CONTROL STRATEGY box numeric values must be provided for a number of system parameters For the genetic algorithm to be used for optimizing the system control variables the numeric values to be provided include number of generations population mutation and crossover breeding rates and uniformity of integers mutation SEC ALGORITHM OPTIMIZATION OF CONTROL STRATEGY OPTIMIZATION METHOD f GENETIC ALGORITHM f EVALUATE ALL COME GENETIC ALGORITHM Generations 15 o Population io Crossover Rate 90 Mutation Rate Zz z fw Mutation Uniform STOPPING CRITERION Stop execution of secondary algorithm if after 15 generations it cann
241. y Averages the user must introduce values for each month on the left side of the screen These values will be displayed in a chart with additional indicators for maximum and average flow and maximum power available from the waterfall calculated as follows Pmax kW 9 81 H m Qmax 1 8 Nmains Mturb gen 1 000 Data must also be introduced on daily and hourly flow variability as a percentage The chart and the information displayed will be updated whenever changes are introduced for any of the data described above Click on Draw to display a chart for hourly flow throughout the year Click on Export to save hourly flow values as calculated by 1HOGA Click on OK to return to the main screen R Dufo L pez HOGA User Manual 3 6 Data bases HOGA includes a comprehensive database of components that can be incorporated into the screens of the components The components contained in the databases can be used in the optimization or not the databases are just storages of commercial components Later when defining the different components used in the optimization it may incorporate some of the components of the database if the user wants it In the databases the user can edit add or remove components Access to databases At the top of the main screen you can access the menu Data Base Project Data Calculate Report Help wf LOAD Components Data Base E Then clicking on Compon
242. y high loads are present for supply to a town or a city for example it may be best to introduce data for photovoltaic generators on each row 1 e sets of PV panels in series and in parallel instead of data for discrete panels In this case each table row corresponds to R Dufo L pez HOGA User Manual 88 one photovoltaic generator An example could include one 1 kWp generator one 2 kWp generator etc The main screen would then display Panels in Parallel Minimum 1 Maximum 1 as this data would not apply unless several photovoltaic generators are required to be in parallel As usual press OK to return to the main screen R Dufo Lopez HOGA User Manual 89 3 8 Wind Turbines The Wind Turbines screen may be accessed by clicking on Wind Turbines Components area or selecting Wind Turbines in the Data menu Data are available in a table for each type of wind turbine The table may be accessed as explained in previous section 3 7 Wind turbines data Some of the data for wind turbines may be considered generic including Name Voltage Type DC or AC in a pop up menu Acquisition Cost Replacement Cost at the time of replacement at the end of its useful life but expressed in the currency referred to the time of the initial investment Operation and Maintenance Cost for each generator currency yr Useful Lifespan yrs Height of the Hub m and CO2 emissions in manufac
243. y the AC batteries provided Pick lt Pl gen Otherwise energy will be provided by the AC generator From a general standpoint the Discharge Strategy will be provided as follows For Paischarge lt P1 energy will be supplied by the batteries For Pl lt Paischarge lt P2 energy will be supplied by the element with lowest PI AC generator or fuel cell For Paischarge gt P2 energy will be supplied by the element with highest PI AC generator or fuel cell In case the system element selected can not supply all of the required Paischargeo AN additional element must be chosen to provide the rest Pick at the lowest possible cost When the 2 element cannot supply the rest of the ower a 3 element must be ppty P R Dufo L pez HOGA User Manual 201 selected Calculation may not be carried out accurately for Prim charge Plgen Plrc P2 as no data is available beforehand such as battery lifespan etc Therefore optimum values for the variables do not necessarily match those values provided by the calculation The final optimum values for all the variables in order to minimize the system s NPC will be found through the secondary genetic algorithm which optimizes correction factors for those variables Details are provided below about the remaining system variables used for the system s control Strategy Pmin gen and Prin rc represent the minimum operating power for the AC generator and the fuel ce
244. z User Manual Lifetime calculation using model Raintlow cycle counting Equivalent full cycles Aging model 5 hitter 105 HOGA User Manual 106 3 6 PRE SIZING PRE SIZING Energy Storage 4 daps range Max bat parallel gt Cr min Mas PY pan parallel P min Max wind E parallel gt P min Clicking on the blue button PRE SIZING of the main screen a message is shown with information of maximum recommended power for photovoltaic generator wing turbines group AC generator inverter Electroyzer and Fuel Cell HOGA eS RECOMMENDED MAXIMUM POWER PV Generator 3 2 kWp Wind turbines group 1 9 kW AC Generator 0 4 kVA Inveter 0 4 kVA Electrolyzer 3 2 kW Fuel Cell 0 4kW ELECTRICITY STORAGE FOR 4 DAYS RANGE EMAX DAY DC 1 2 5 4 kWh day Batteries bank capacity 1513 Ah 36 4 kWh H2 tank size 2 4 kg The data shown has the following meaning IHOGA knows the load and the irradiation so it calculates approximately the peak power of the Photovoltaic Generator which can meet the whole load by itself estimating an average value of the inverter efficiency of 80 losses of 20 in batteries assuming that all the energy passes through the battery and adding the safety factor of the photovoltaic panels This peak power in the example 2 5 kWp should be the maximum allowed power for the photovoltaic generator If for example the PV panels selected are 135 Wp 12 V panels

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