Research On Load Probability Modeling And Orderly Charging Strategy Of Electric Vehicles

In recent years,with the gradual reduction of fossil energy and the increasing requirements of environmental protection,electric vehicle(EV),as environmentally friendly vehicle,has received strong support for its development and the number has grown rapidly.Due to the uncertainty of EV owners' travel and traffic conditions,the EV charging load has a strong randomness.The probabilistic modeling of EV charging load helps to study its changing characteristics,and then analyze its impact on the operation of the distribution network.A large number of EV disorder charging will adversely affect the load characteristics,power quality and power grid operation control,which brings new challenges to the distribution network operation.Therefore,this paper establishes a probabilistic model that takes the EV charging station load as the research object,and studies the EV orderly charging guidance strategy based on the load scenarios.A load probabilistic modeling method for EV charging station considering time correlation is proposed.Taking the load of each period in daily load curve of EV charging station as a random variable,based on historical data,the probability distribution of each single period load is established with versatile distribution which has the highest fitting accuracy.Because of the continuity of EVs' charging behaviors,the charging station's loads in adjacent periods are correlated.Firstly,96 periods of a day are divided into several continual periods sets according to the correlation analysis between loads of different periods.In each set of continual periods,the correlation between the loads of several adjacent periods is relatively large.Then,the joint probability distribution of the loads of several adjacent periods in each set of continual periods is established by using Pair-copula method with D-vine structure.Furthermore,the Pair-copula joint probability distribution model is used to sample and generate load scenarios considering time correlation for all continual periods sets in a day.The fluctuation trend and fluctuation size are used to represent the fluctuation index of the generated load scenarios to measure the rationality.Finally,taking the actual historical data of an EV charging station in Shenzhen city as an example,the effectiveness of the proposed method is verified.An orderly charging guidance strategy for EVs based on the time-of-use(TOU)price of charging stations is proposed to achieve friendly access to EV loads in the distribution network.The orderly charging model aims at the smallest sum of the distribution network loss and the charging station power purchase cost,taking into account the interests of the grid side and the charging station.Based on the EV user price response curve and the TOU price of the distribution network,the orderly EV charging guidance can be realized by optimizing the peak?flat and valley time periods division and electricity prices of the charging station.In order to avoid that the price signal obtained by single load scenario optimization can not be applied to other scenarios at the same time,error scenario constraints and scenario transfer constraints are added to the model to obtain a more general charging station TOU electricity price strategy.Finally,the actual 19-node distribution network system and 265-node distribution network system are taken as examples to verify the effectiveness of the proposed model.