Research On Evaluation Of Electric Vehicle Acceptance Capacity In Local Distribution Network

In recent years,people have paid more and more attention to environmental pollution.Electric vehicles(EVs)are regarded as an effective means to reduce air pollution and carbon emissions in various countries and have been greatly developed in technology and market.However,as a new type of power load,the charging behavior of EVs has the characteristics of randomness of space-time distribution.The charging of large-scale EVs will pose a serious threat to the safe and stable operation of the distribution network.Under the condition of safe and economical operation,the current distribution network is limited to the acceptance capacity of EVs.Therefore,it is necessary to study the quantitative evaluation of the acceptance capacity of the EVs.In this thesis,for the local distribution network,the maximum load capacity of the transformer and the voltage deviation of the node are used as evaluation indicators to evaluate the acceptance of EVs under multiple scenarios.The main research contents are as follows:Firstly,the travel behavior and charging load characteristics of EVs are analyzed.Based on the statistical data of the National Highway Traffic Safety Administration(NHTS)in 2009,the entry and exit rules of EVs in residential area,office area and commercial area are analyzed.The charging behavior of EVs is simulated by Monte Carlo random sampling,including initial charging time,expected departure time and starting charge SOC.The charging power curve of the electric vehicle in residential area,office area and commercial area is calculated.Secondly,it quantitatively evaluates the ability of local distribution networks to accept EVs.The impact of EV access on the distribution network was analyzed,and the maximum load capacity of the transformer and the node voltage deviation were determined as the evaluation indicators of the acceptance capacity.According to the topology of distribution network,different functional areas are divided,the correlation of EV charging location and function area is considered,and the maximum acceptance ability of local distribution network under safe and stable operating conditions is calculated.The 33 node distribution system is taken as an example to analyze the acceptance of EVs in different functional areas.Thirdly,considering the optimization of charging strategy,the evaluation of the acceptance capacity of the EVs is carried out.Two kinds of charging strategies of variable power charging and time-controlled charging are formulated respectively with the charging power and charging state of EVs at each time period respectively.The two charging strategies are solved by the particle swarm optimization algorithm,with the goalof minimum load curve peak valley difference,minimum system load fluctuation and minimum charging cost of users.In evaluating and accepting capabilities,the number of EVs is continuously increased to speed up the simulation.The distribution network of an office area is taken as an example to analyze the results.The results show that the acceptance ability of the optimized charging strategy is obviously improved,and the acceptance capability of the variable power charging strategy is the largest.Finally,evaluation of electric vehicle acceptance capability considering PV configuration is carried out.The photovoltaic output characteristics of sunny,cloudy and rainy are analyzed,and the number of the most acceptable EVs can be calculated by the particle swarm optimization(PSO)algorithm,and evaluate the electric vehicle acceptance capacity when the user's response rate to the charging strategy is different.The capacity of the power distribution network to the EV is evaluated by an example of an office area equipped with a photovoltaic power generation system.