| Under the environment of "Emission Peak,Carbon Neutrality" and "New Infrastructure" strategy vigorously promoting the development of new energy vehicle infrastructure,largescale access of electric vehicles has led to significant changes in the operation characteristics of urban power grid.As a bridge between electric power system and traffic system,the charging demand of electric vehicles is affected by user behavior and road traffic factors,and has significant spatial and temporal distribution characteristics.In this context,studying the impact of the temporal and spatial distribution of EV charging load on the carrying capacity of the distribution network can not only effectively analyze the weak links in the operation of the distribution network,but also provide an analysis basis for the planning,construction,optimization,regulation and operation of the distribution network under the future large-scale EV parallel network.Based on the coupling relationship between urban power grid and traffic network,this paper studies the spatial-temporal hosting capacity and optimization of distribution network for large-scale electric vehicles.Firstly,the spatial and temporal distribution characteristics of EV charging load are studied.On this basis,the carrying capacity of distribution network to EV is studied,and the actual carrying capacity of distribution network to EV is quantitatively evaluated.Then the comprehensive evaluation and optimization method of distribution network carrying capacity considering the spatial and temporal distribution of electric vehicles are studied.The main research work of this paper is as follows:(1)The temporal and spatial distribution probability model of EV charging load is established.Firstly,based on the concept of user travel chain,the characteristics of the time and space features covered by the complete travel chain were modeled,and the corresponding probability and statistics model was established to describe the spatial-temporal rules of electric vehicle users’ travel.At the same time,the urban road traffic network and road traffic delay factors are modeled and analyzed,and the improved prior path algorithm based on Dijkstra is proposed to plan the travel path with the minimum delay for EV users,and the Monte Carlo simulation method is used to simulate the spatial and temporal distribution of EV charging demand in the road network.The validity of the probabilistic model was verified by an example,and the temporal and spatial distribution characteristics of EV charging load in the road network were analyzed.(2)Based on the road-electric coupling network,a multi-objective optimization evaluation model for EV load acceptance potential of distribution network is established,and a quantitative evaluation method for carrying capacity of distribution network is proposed.Firstly,the cooperative operation mechanism of road-electric coupling system is described,and the power supply region division model of coupled distribution network is established.On this basis,considering the safety and economy of distributed new energy grid connection and power grid operation,an optimization evaluation model of EV load potential was established to analyze the temporal and spatial distribution characteristics of EV charging load power accepted by distribution network in various scenarios.Then,the influence of charging load on the distribution network under different EV permeability was analyzed from the perspectives of node voltage,branch power flow and line loss.The maximum offset of node voltage was taken as the discriminant index to evaluate the carrying capacity of the distribution network,and the carrying capacity of the distribution network to EV charging load was quantitatively evaluated.(3)A comprehensive evaluation index system for hosting capacity of distribution network and an optimization model for hosting capacity are established considering the spatial and temporal distribution characteristics of electric vehicles.Firstly,a multi-layer evaluation index system for the comprehensive carrying capacity of distribution network is proposed,which considers the spatial-temporal distribution characteristics of EV load.Criterion layer and index layer are established respectively to evaluate the operation and carrying capacity of distribution network,charging facility network and EV charging users.Entropy weight and comprehensive fuzzy score of each level were obtained by fuzzy comprehensive evaluation method combining information entropy and fuzzy theory.Then,aiming at the vulnerability index in the evaluation of the carrying capacity criterion layer of the distribution network,a method to improve the carrying capacity of the distribution network based on the optimal scheduling of V2 G cluster was proposed.Finally,a comprehensive score is given for the carrying capacity of the distribution network in multiple scenarios with different EV penetration levels and whether V2 G optimal scheduling strategy is adopted through an example,so as to analyze the comprehensive carrying capacity and integration efficiency of the distribution network for EV. |
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