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Influence Of Electric Vehicle Charging Load On Distribution Network And Orderly Charging And Discharging Strategy

Posted on:2021-01-21Degree:MasterType:Thesis
Country:ChinaCandidate:S Y ZhouFull Text:PDF
GTID:2392330620478900Subject:Electrical engineering
Abstract/Summary:PDF Full Text Request
With the continuous development of economy,people's demand for energy is increasing.In this context,the problem of resource shortage and environmental pollution caused by the excessive use of fossil energy is increasingly apparent.In order to deal with these problems,various countries have invested in the research of new clean energy.In the transportation industry,electric vehicles are favored by various countries because of their advantages of small pollution,low energy consumption and low noise.In recent years,the number of electric vehicles is increasing day by day.The vigorous development of electric vehicles has relieved the pressure of the world's energy crisis and contributed to the cause of environmental protection.However,disordered charging of large-scale electric vehicles will cause serious harm to the stable operation of the power system.Therefore,how to guide the electric vehicle to charge and discharge in order has become a research hotspot in today's era.Firstly,the number of electric vehicles is predicted.The least square method is used to establish the number prediction model of electric vehicles,and the grey correlation theory and expert evaluation method are used to deal with economic indicators and policy indicators respectively,so as to predict the number of electric vehicles in China,and then get the number prediction values of electric vehicles in Jiangsu Province and Xuzhou city respectively.It can be seen from the predicted value that in recent years,the number of electric vehicles is growing rapidly,and its charging load scale cannot be ignored.Then,the influencing factors of the disordered charging load of the electric vehicle are studied,and the load of the electric vehicle is predicted.This paper analyzes the factors that affect the load of a single electric vehicle,including the travel characteristics of users,charging mode and battery charging characteristics,and obtains the probability distribution of each parameter.On the basis of several basic hypotheses,Monte Carlo simulation method is used to establish a load forecasting model of disordered charging and to analyze a load forecasting example in a certain area.After that,the influence of disordered charging of electric vehicle on distribution network is studied.Select electricity method to analyze the calculation process of network loss,and point out the harm of network loss to power grid.From the point of view of battery and reactive power,the causes of voltage deviation are analyzed,and the harm of voltage deviation to power system is pointed out.A regional distribution network model is established to analyze the disordered charging behavior of electric vehicles under different permeability and the influence of network loss and voltage deviation.This paper studies the relationship between load standard deviation and voltage quality,network loss,and concludes that optimizing load standard deviation can improve voltage quality and reduce network loss.Finally,the orderly charging and discharging strategy of EV considering user response is studied.Under the background of TOU price,this paper introduces the traditional process of using membership function and elasticity matrix of electricity price in fuzzy mathematics to divide peak period,flat period and valley period and to make the electricity price in each period.Combined with V2 G technology,the discharge price based on cost-benefit is analyzed.Based on the concept of peak price coefficient and valley price coefficient,an orderly charging and discharging model considering the response degree and satisfaction degree of users is established,and the types of electric vehicles are divided according to the different response modes.This paper introduces the traditional multi-objective particle swarm optimization algorithm and analyzes its limitations,and proposes a Pareto based multi-objective particle swarm optimization algorithm which can overcome its limitations.In the case analysis,this algorithm is used to solve the objective function under the constraint conditions in a certain region to obtain the optimization solution set,analyze the optimization solution set and select the actual optimal solution.Monte Carlo simulation method is used to calculate the optimized load.The optimization effect of the load is discussed,and the charging cost before and after the user optimization is calculated.The results show that the optimization effect of orderly charging and discharging strategy is significant.
Keywords/Search Tags:electric vehicle, load forecasting, Monte Carlo, orderly charging and discharging, particle swarm optimization algorithm
PDF Full Text Request
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