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Research On Charging Service Pricing Policies Of Electric Vehicle Charging Stations With Photovoltaic Power

Posted on:2016-02-28Degree:MasterType:Thesis
Country:ChinaCandidate:W J GeFull Text:PDF
GTID:2272330467979147Subject:Electrical engineering
Abstract/Summary:PDF Full Text Request
ABSTRACT:Electric vehicles’charging has great randomness in time and space, and would cause great impact on the power system. Electric vehicle charging stations with photovoltaic power can not only improve the problem but also increase the energy-saving emission reduction efforts. Based on this background, by establishing the mathematical model of the electric vehicles’load and electric vehicle users’price response, the research proposed the charging pricing policies to charge electric vehicles orderly. On one hand, the charging load would be improved to use more solar power, on the other hand, there’s an economic benefit to reduce users’expenses and increase operator’s revenues.This research studied mathematical models of the electric vehicles’load and the electric vehicle users’price response. According to the load characteristics of electric vehicles, the research analyzed the characteristics and effects of main factors. Based on the probability distribution of start point of charging, establishing a typical day’s load curve; by assuming that users won’t change their trip characteristic, based on access data of the commuting fuel vehicles, the paper establishing a typical month’s load curve. Based on the principle of consumer psychology, the paper established the model of electric vehicle users’price response and obtained parameters through questionnaire surveys.Based on the above, from the perspective of charging station operators, the paper developed a strategy for charging electric vehicles orderly.(1) For the case of continuous charging time, the paper proposed an optimization method of charging service price. The objective is to maximize the utilization of photovoltaic power. A modified particle swarm optimization (MPSO) algorithm is employed to optimize the problem. Through the enumeration method, the validity of the optimize result is proved. A case analysis verifies the effectiveness of the method. By comparing three kinds of application effect of charging service price, the paper suggests using monthly charging service price separately for weekdays and weekends.(2) For the case of discrete charging time, the paper proposed an optimization method of charging service price. The objective is to maximize the utilization of photovoltaic power and to minimize payment from the grid. A linear programming algorithm is employed to optimize the best charging load curve. To fitting the best charging load curve, a particle swarm optimization (PSO) algorithm is employed to optimize the problem. The results show the effectiveness of the method of charging service price. Furthermore, two common methods were analyzed.
Keywords/Search Tags:Electric vehicle, Charging station, Charging service price, User priceresponse model
PDF Full Text Request
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