Vehicle to Grid Simulator: User Guide - ev2grid
Contents
1. 40 minGap 3 sigma 0 5 gt parking endPos 180 id parkingl lane 5532530 1 0 name SantaCaterina startPos 1 gt station availableSlots 1 Id stationl station availableSlots 1 Id station2 parking parking endPos 400 id parking 186 2017704330 0 name Carrefour startPos 10 gt station availableSlots 1 Id stationl station availableSlots 1 Id station2 gt lt parking gt parking endPos 420 id parking lane 22986452 1_0 name Ospedale startPos 1 gt station availableSlots 1 Id stationl station availableSlots 1 Id station2 gt lt parking gt parking endPos 110 id parking4 lane 22576119 0_0 name Pietrasentina startPos 1 gt station availableSlots 1 Id stationl station availableSlots 1 Id station2 gt lt parking gt parking endPos 400 id parking5 lane 25643295 0 name Stazione startPos 1 gt station availableSlots 1 Id stationl gt station availableSlots 1 Id station2 gt lt parking gt lt additional gt Figure 2 Description of the Parking areas lt xml version 1 0 encoding UTF 8 standalone no gt lt additional xmlns xsi http www w3 org 2001 XMLSchema instance xsi noNamespaceSchemaLocation http sumo sf net xsd add2. G G DxR 2 where D is the traveled distance and R is the average battery use given in per Km 2 2 Results Visualization After fixing all the parameters the user clicks on the Simulation button to be then redirected to a second page where he has to click on the button Launch simulation to confirm his choice Once done the user has to wait for the whole duration of the simulation to be then redirected to the Results page In the Results page two results can be displayed the rejection percentage and the distribution of the battery level at the beginning and at the end of the simulation By rejection percentage we mean the percentage of charging requests that were declined since no charging stations were available as the EV arrives at 12 the parking area In the Fig 8 we show the distribution of the battery level of individual EVs computed at the beginning and at the end of the simulation More precisely each point of the curve represents a couple x y where y is the percentage of vehicles that have x of residual charge Battery Residual Charge EV PercentageL 10 15 20 25 30 35 40 45 50 55 60 Residual ChargeL Z1 Initial Residual Figure 8 Battery Residual Charge 13 3 Contribution to Activity KPIs The implemented simulator contributed to the following KPIs e P1301 number of interconnected technical components in a testbed or lab physical computers servers network elements sens
3. Road Network Converter net version gt edge id function gt lane id index speed length gt lt edge gt Simulation Exporter SMS EV P exporter SUMO Traffic Control Simulator Interface modified Traci routes mute id edges gt Toute id edges gt vehicle id route departTime gt edge id function gt tane id index speed length gt ledge connection from to fromLane toLane dir state gt connection from to fromLane toLane dir state gt inet pisa netxmt Traffic Model Ts ORE vehicle id route departTimez init SUMO Components Modified Components Introduced Components Figure 1 Building blocks of the simulation environment work for modeling EVs movement from one parking to another in a cyclic way As a result additional information is introduced in SUMO simulator for the inclusion of EV characteristics and charging models i e pisa add xm1 This information includes the set of parking areas and the status of charging stations as shown in Fig 2 the battery level and the set of assigned parking areas for each EV such as presented in Fig B the possible routes from a parking to another parking and
4. to Y guia Vag y Area della Tetzanaia s gt x Ww 6 im e y S nuo fo 3 6 J Sim Marino 82 55 ey b l Mattino ha z j dolci coccohito et 0 Bocea h g Casa Betania ba 0 Paolo Ripa Dim 5 Dipartimento di Scienze Wed DE E Alimentari 8 n 5 i Giardina Scotto c 9 T Vi 5 Via Carlo Matteucci dm 0 i Polo Didattico hti 8 dele ale 8 delle Piagge hele Paes A Bonajy Hotel Terminus Plaza D Stazione Di isa Cle PO ay y fn Dipartimento di Wa oe E 1 Biene veterinarie a Meet Hostel pisa s n AC Hotel Pisa i 6 y ja BBlePlagge y i Figure 5 Positioning of the parkings on the city map The second variable parameter is the overall duration of the simulation i e the simulated time which varies between 100 seconds and 10000 sec onds These values represent the time for which the traffic flow is simulated The user has to wait for the end of the simulation to be able to get access to the results The higher is the simulated time the more accurate are the results If the user does not want to wait for the simulations he can directly click on the button Results to have access to the results of simulations car ried out offline An example of those results is shown in Fig 6 where the utilization percentage of all the available charging stations in a parking area are plotted The user can also set the number of electric vehicles that will be considered in the simulation This num
5. finally the specific routes followed by each EV including the stops at the charging stations The other main component of the simulation environment is the smart management system for electric vehicle recharge SMS EV simulator that based on the movements of the EVs generated by SUMO evaluates the per formance of different policies for EV recharging in an activity based traffic model scenario and for the generation and collection of correspondent per formance statistics The SMS EV consists of the following modules the Pol icy Decision Element which implements the charging strategies e g First Come First Served while enforcing the decision to the charging system and the Statistic Collector for generating and elaborating statistics related to the charging station utilization battery consumption and user satisfaction SMS EV leverages the Traffic Control Interface TraCT for interfacing with SUMO and exploiting real time information about vehicle mobility e g number of vehicles position of vehicles across the road network In this work IraCI has been extended to include additional EV status information regard lt xml version 1 0 encoding UTF 8 standalone no gt lt additional xmlns xsi http www w3 org 2001 XMLSchema instance xsi noNamespaceSchemaLocation http sumo sf net xsd additional file xsd lt vType accel 2 6 color 0 1 0 decel 4 5 id EV length 2 maxSpeed
6. map formats supported by SUMO including Open StreetMaps into a SUMO specific XML format describing the overall road network i e pisa net xml The Traffic Model specifies the traffic pattern of vehicles across the road network e g the random movement of vehicles The Road Network Converter along with the Traffic Model provide the main inputs for the Simulation Exporter to generate road traffic within SUMO simulator 4 In the Simulation Exporter the Road Network Exporter is responsible for generating and updating SUMO internal data structures re lated to the road map by exploiting the Road Network information provided by the Road Network Converter while the Traffic Generator generates the vehicular traffic based on the specified Traffic Model e g random activity based model and based on the detailed vehicle positions along each route of the map provided by the DuaRouter component As result a data structure is generated and updated detailing all the routes followed by vehicles during simulations i e pisa rou xml The considered SUMO components have been modified to take into ac count the activity based EV behavior First the Road Network Exporter has been modified for extending the existing data structures and including the description of the parking areas i e pisa add xml Secondly the Traffic Model has been extended to include the activity based model used in this Road network Importer OpenStreetMaps
7. ber can vary between 50 and 200 vehicles 40 3 o S 30 o o 0 a 20 9 S N 10 0 0 1 2 Number of Occupied Stations per Parking Figure 6 Charging Station Utilization 2 1 2 Fixed Parameters The fixed parameters cannot be modified by the users and are kept constant for all the simulations In this version of the simulator we have fixed the number of charging stations available at each parking which is equal to 10 10 We have also set the minimum and maximum initial battery level to respectively 10 and 40 Each electric vehicle then starts the simulation with a battery level uniformly distributed in the interval 10 40 2 1 3 Evaluation Parameters Other parameters are not visible on the graphical interface but are necessary for running the simulations namely the map of the city the background traffic and the charging and consumption models At this stage the city of Pisa is the considered case study as shown in Fig 7 The road map of the city of Pisa has been extracted from Open StreetMap 3 with an overall extension of 375 km 19 78 km x 18 94 km One thousand conventional vehicles i e non EVs move in the area in a random way thus contributing as background traffic All the vehicles move following the Krauss based car following model 6 which makes the driver stay at a safe distance from the other vehicles and at safe speed allowing him to adapt his driving behaviour with respect
8. cR Pe ee BY wee dese OE A Battery Residual Charge 7 CON 2 WHR 1 EV2Grid Simulator Architecture The EV2Grid simulator is a Java based custom built simulator that has been developed to evaluate the performance of the Smart Energy Management Sys tem for Electic Vehicle recharge SMS EV To reproduce an urban traffic environment the simulator has been integrated with an extended version of the open source and widely used vehicular traffic simulator namely SUMO Simulation of Urban MObility 1 developed at the Institute of Trans portation Research at the German Aerospace Centre 2 SUMO simulates the movement of each vehicle in a city thus contributing to the overall travel demand in an urban area depending on a selected traffic model e g ran dom However SUMO does not consider the mobility of an heterogenous set of vehicles for example including both electric and conventional vehicles selecting their trips according to an activity based model For this reason we extended SUMO to include parameters and behaviors that are essential to model EV mobility as well as information related to the public charg ing infrastructure The resulting building blocks of the overall simulation environment are shown in Fig 1 and are described here below The Road Network Importer elaborates a graphic map into a Open StreetMaps 3 format while the Road Network Converter is responsible for converting a variety of
9. itional file xsd vType accel 2 6 color 0 1 0 decel 4 5 id EV length 2 maxSpeed 40 minGap 3 sigma 0 5 gt vehicle id evl type EV depart 0 0 route elecRoute0 battery 12 0 stop parking parkingl duration 1547 parking true gt stop parking parking2 duration 1247 parking true gt lt vehicle gt vehicle id ev2 type EV depart 0 0 route elecRoutel battery 23 07 stop parking parking3 duration 2067 parking true stop parking parking5 duration 1837 parking true gt lt vehicle gt lt additional gt Figure 3 Description of EV characteristics ing the initial battery capacity and EV departure time during the simulation The battery capacity is also updated during simulations based on the actual movement of EVs according to specific charging and consumption models EV Charging Simulator Parkings Number of EVs 050 gt 2 parkings lt 6 3 parkings parkings 5 5 5 Duration of the Simulation sec 100 1000 10000 Figure 4 Graphical User Interface 2 EV2Grid Simulator Environment 2 1 Graphical User Interface GUI The Graphical User Interface is displayed when the users get access to the SMS html page As shown in Fig 4 the user can directly interact with the simulator and choose the paramete
10. ng Infrastructure Deployed in City Parking Facilities IEEE ITST 2013 Nov 5 7 2013 Tampere Finland Presentations 1 L Valcarenghi R Bruno P Castoldi M Conti CROWD ReFUELING Bar Camp Festival dell Energia 2013 24 25 maggio 2013 Roma 15 References 1 6 7 C R D Krajzewicz G Hertkorn and P Wagner Sumo simulation of urban mobility an open source traffic simulation in Proceedings of the 4th Middle East Symposium on Simulation and Modelling 2002 pp 183 1877 2002 http sumo sourceforge net Sumo simulation of urban mobility Centre for Applied Informatics ZAIK Institute of Transport Research German Aerospace Centre Tech Rep January 2008 http www openstreetmap org L G Papaleontiou High level traffic modeling and generation Master of Science Thesis University of Cyprus Tech Rep March 2008 A Wegener M Piorkowski M Raya H Hellbruck S Fischer and J Hubaux High level traffic modeling and generation in Proceeding of 11th Communications and Networking Simulation Symposium CNS 08 April 2008 K S Microscopic modeling of traffic flow nvestigation of collision free vehicle dynamics in PhD thesis 1998 J Francfort Electric vehicle charging levels and requirements overview Clean Cities December 2010 Webinar December 2010 16
11. ors etc R2 9 e P1302 number of new products and services launched into the market B1 5 14 4 Task Outcome An outcome in terms of scientific publications has been also reached within this task The list of publications is the following International Journals 1 R Bruno L Valcarenghi M Gharbaoui B Martini Smart Manage ment of Renewable Energy for Green Transport ERCIM NEWS no 92 Jan 2013 International Peer reviewed Conferences 1 M Gharbaoui L Valcarenghi B Martini P Castoldi R Bruno M Conti Effective management of a public charging infrastructure through a smart management system for electric vehicles IEEE In ternational Energy Conference and Exhibition ENERGYCON pp 1095 1100 Sep 9 12 2012 Florence Italy 2 M Gharbaoui L Valcarenghi B Martini P Castoldi R Bruno M Conti Effective management of a public charging infrastructure through a smart management system for electric vehicles IEEE In ternational Energy Conference and Exhibition ENERGYCON pp 1095 1100 Sep 9 12 2012 Florence Italy 3 M Gharbaoui L Valcarenghi R Bruno B Martini M Conti P Castoldi An advanced smart management system for electric ve hicle recharge 2012 IEEE International Electric Vehicle Conference IEVC Mar 4 8 2012 Greenville SC USA 4 M Gharbaoui B Martini R Bruno L Valcarenghi M Conti and P Castoldi Policies for Efficient Usage of an EV Chargi
12. pedrada H Istituto di EAS Scuola Superior Informatica Sant Anna 1 m e Telematica Vehicle to Grid Simulator User Guide L Valcarenghi R Bruno M Gharbaoui B Martini P Castoldi and M Conti 1 Scuola Superiore SantAnna 2 CNIT 3 IIT CNR Pisa Italy About the manual This guide describes the features and functionalities of the EV2Grid simula tor It gives an overview of the architecture of the simulator and helps the user with the configuration of the parameters by detailing the instructions necessary to successfully launch a simulation and then get and interpret the results The simulator can accessed at the following webpage http 193 205 83 101 www ToolBox SMS html Contents 1 EV2Grid Simulator Architecture 2 EV2Grid Simulator Environment 2 1 Graphical User Interface GUI 0 2 1 1 Variable Parameters 2 1 2 Fixed Parameters 0 0008 2 1 3 Evaluation Parameters 2 2 Results Visualization 0 000084 3 Contribution to Activity KPIs 4 Task Outcome Ex El GEE List of Figures Building blocks of the simulation environment Description of the Parking areas Description of EV characteristics ln Graphical User Interface 24 2 x 99 9 o oos Positioning of the parkings on the city map Charging Station Utilization Thao PSA lt s ck
13. rs that will be considered during the simulation The GUI consists of variable parameters that are set by the user before launching each simulation and fixed parameters that are common to all the simulations and cannot be modified by the users 2 1 1 Variable Parameters The variable parameters are set by the user before launching each simulation For each parameter N possible values are available and the user has to check one of them The first variable parameter is the number of available parkings in the map By approaching the mouse the user can visualize the position of each parking on the city map La Coccinella Bed t Brenktast c V obo rt 8 T 1 4 ra N y n 0 n Arena Garibaldi sm B amp B PisaBelleville Campeggio Torre Pendente 3Parkings Alitalia Park Resort Stele Piazza del Duomo Abitilia Tower Plaza x Museo dele Sinopie s own ein Dipartimento SaiAfitacamere Dello A Ingegneria q Chiesa di Santa 4 0 T fes M Caterina d Alessandria i pedal Stazione Di Psa im S Rossore No b Sd Oel Nos ia Que D 1 Orto Botanico peat 1 f j cos Giovanni BOSCO moni Bed D lt via got loan And Breakfast hi A 4 y S 0 i Chiesa di San Frediano y s Museo degli Strumenti v peril Calcolo ymo Pacing k yino Pang 1 Camp Spot 0 k Comunale Abetone de 8 ag nm Fondazi ne Palazzo Blu 2 8 Mi 4 WP SN Bonsai
14. to the leader s deceleration The reaction time of the driver is assumed to be equal to one second Both EVs and non EVs are inserted at the beginning of the simulation at different random points on the map Non EVs follow pre determined trips that start from a random location on the map and finish at a random destination Once arrived to the destination the vehicles restart the same trip in a cyclic way in order to keep a constant traffic density of vehicles during the whole simulation The EVs on the other hand move continuously from one parking to the other in a cyclic way following a pre selected order The following charging and the electricity consumption models have been considered to set the actual level of battery electric charge Charging model For the sake of simplicity a linear charging model has been considered level 2 and level 3 charging 7 although more sophisticated models can be easily included C5 Ci te t x V 1 where C and C are the capacity percentage of the battery after and before recharging to t is the charging duration and V is the charging speed in per minute level 3 sockets fully recharge a battery in 30m while from 4 to 8 hours are needed for level 2 sockets Consumption model A linear model is also used for the electricity con sumption during the movement of the EVs which is function of the traveled 11 Figure 7 The city of Pisa distance and the battery efficiency
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