| The electric vehicle industry is an important carrier for China to achieve the "dual carbon"goal,which has attracted much attention and is developing rapidly.However,the development of the electric vehicle industry is to some extent constrained by the friendly interaction between electric vehicles and the power grid.The rapid growth of electric vehicle charging load and its electricity consumption characteristics affect the reliable and stable operation of the power grid,while the power supply capacity of the power grid also limits the development scale of electric vehicles.Based on studying the prediction method of electric vehicle charging power demand and the static voltage stability of the distribution network under a high proportion of electric vehicle charging loads,this article further studies the layout optimization problem of electric vehicle charging stations and the orderly charging and discharging strategy of electric vehicles.The studies can provide theoretical basis and technical support for the friendly interaction between electric vehicles and the power grid and the coordinated development of the two.A total of four aspects of the research have been carried out,with specific explanations as follows:(1)A spatiotemporal distribution prediction method for the charging power demand of electric vehicle users is proposed to address the impact of uncertainty in their charging behavior on their charging power demand,taking into account the anxiety factor of electric vehicle users’mileage.By analyzing the relationship between the psychological endurance of electric vehicle users towards mileage anxiety and their expected battery level,a charging decision model for electric vehicle users considering mileage anxiety factors was established.A time and spatial probability model for the charging power demand of electric vehicle users was established based on the non-stationary Markov chain and travel chain theory,respectively.Monte Carlo simulation was then used to predict the charging power demand of electric vehicle clusters.(2)A hybrid power flow model-based method for evaluating the static voltage stability of distribution networks under a high proportion of electric vehicle charging loads is proposed.Firstly,the static voltage stability indicators applicable to three different operating conditions,namely steady-state operation,small disturbance,and extreme operation,were elaborated.Then,an improved probabilistic power flow calculation method based on Latin hypercube sampling is used to simulate the impact of the uncertainty of electric vehicle charging load on the power flow of the distribution network.Finally,combining static power flow,continuous power flow,and probabilistic power flow models,a calculation method for the probability distribution of static voltage stability indicators in the distribution network after electric vehicles are connected is provided.Based on an example,the ultimate charging power of electric vehicles causing static voltage stability issues in the power grid was analyzed.(3)Considering the balance of interests among electric vehicle users,charging station investors,and power grid operators in the optimization of electric vehicle charging station layout,a multi-objective optimization method for electric vehicle charging station layout considering the balance of interests among multiple parties is proposed.A multi-objective optimization model was established by comprehensively considering the charge wait time for electric vehicle users,the selling and idle rate of charging facilities,the static voltage stability margin index of the power grid.The Pareto optimal solution set was obtained through an improved multi-objective cuckoo search algorithm,and then the dominant strength rule was used to obtain the optimal solution without subjective factors.(4)A strategy for orderly charging and discharging of electric vehicles based on V2G dynamic spatiotemporal electricity price guidance is proposed to address the increased risk of safe and stable operation of the power grid caused by disorderly charging and discharging of electric vehicles.Firstly,a V2G response probability model based on electricity price incentives and charging demand constraints was established.Then,considering the discharge cost of electric vehicles,as well as the peak valley difference and load fluctuation of the distribution network,a V2G electricity price optimization model was established.This model is based on the lowest cost of electric vehicle charging and discharging and the construction and operating cost of power grid.The proposed improved cuckoo search algorithm was used to solve the model.Finally,this article takes the distribution network in Dali County,Weinan City,Shaanxi Province as an example to verify the correctness and effectiveness of the proposed method.The research results indicate that the proposed charging power demand prediction method can obtain the node dimension of electric vehicle charging power demand,and the charging power demand of electric vehicle users is closely related to mileage anxiety factors.Based on the proposed static voltage stability evaluation method for the distribution network,the probability distribution of node static voltage stability indicators can be given;the high proportion of electric vehicle charging load connection may lead to system static voltage instability.Based on the proposed optimization method for charging station layout,it effectively balances the interests of electric vehicle users,charging station investors,and power grid operators.It shortens the waiting time of electric vehicle users,ensures stable static voltage of the power grid,and fully utilizes the charging facilities of the charging station.Based on the proposed V2G dynamic spatiotemporal electricity price guidance,the orderly charging and discharging strategy for electric vehicles can be reasonably arranged through electricity price guidance,significantly reducing the charging costs of electric vehicle users and the construction and operation costs of power grid companies. |
PDF Full Text Request