Study Of The Temporal-Spatial Stochastic Model Of EVs And Aggregator's Scheduling Strategy With Consideration Of DR

Electric Vehicle(EV),based on its low pollution,smaller energy consumption,is gradually occupying the automotive market.EV's special needs for electricity energy,will make load configuration,line margin,power capacity face new challenges.With the development of the EV industry,technology of V2G(Vehicle to Grid)and aggregator management mode(Aggregator),EV is being considered as one of the most complicated loads/power sources.It also gradually be realized that the demand response(DR)function of EV with practicality and operability.Although an EV can participate in DR based on price or other incentives,under the capacity constraints,an EV is not competitive in more market services.As a proxy for a large number of EVs,Aggregator can gain more benefits with the purposeful,planned,and controllable strategies by participating in more markets.The multi-stakeholder interests are also taken into consideration in the strategies.Therefore,Aggregator is worthier to research,which involves different subjects and complex.According to above analysis,this paper will do the research based on some research fields,such as economy,social investigation,geography,transportation,and electric.Research on EV load management and Aggregator profitability scheduling will be conducted as the following sides:1.This paper will propose an EV state transition diagram between driving,charging,V2 G and idle.The temporal-spatial stochastic models of EV load will be established.Based on Logistic regression model,the paper will establish a selection factor model for EV users to Aggregator.The influence of the Aggregator number on EV load's temporal-spatial distribution will be simulated in IEEE 123 Node Test Feeder system.2.From EV user's point,this paper will integrate user's willingness index with the battery charge-discharge aging taken into consideration.The EV charging/discharging economic models will be established.This paper also will propose the expected charge/discharge SOC(State of Charge)capacity model during EV seeking for Aggregator service..3.According to the relationship between Aggregator,EV users and distribution network,this paper will present Aggregator revenue models,EV user satisfaction models and Aggregator inspection models.The Aggregator optimal scheduling model with maximized DR revenue will be established under the constraints of electrical power,user satisfaction and other restraint indexes.The optimal dispatch strategies of Aggregator will be investigated by V2 V and technology and EV scheduling models.This research will simulate the correlation between different DR and revenue caused by EV user driving habits and charging/discharging behaviors in distribution network.The effects of V2 V Aggregator facilities to customer satisfaction,Aggregator revenue and the distribution network's assessment index will be analyzed.This paper also will discuss the win-win combination between two kinds of Aggregators.According to the simulation,the models in the paper are applicable,which will provide an important reference for reality management of EV loads and Aggregator.The models and research will be conducive to mobilize various factors to improve EV.