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Researcher On The Electric Vehicles Charging Load Forecasting Method And The Strategy Of Charging Control

Posted on:2016-08-16Degree:MasterType:Thesis
Country:ChinaCandidate:J W YangFull Text:PDF
GTID:2322330473465726Subject:Electrical engineering
Abstract/Summary:PDF Full Text Request
With the development of technology and the progress of economy, traffic is more and more convenient. But at the same time carbon emissions caused by transportation increase much, then many problems followed, such as energy shortage and the worsening ecological environment. As a new energy traffic mean, electric vehicles(EVS) have incomparable advantages over traditional cars in saving energy, protecting environment and other aspects. Therefore, many countries in the world are promoting electric vehicles. Charging load of large scale electric vehicles connected to the grid have the characteristics of strong randomness in terms of time and space, which will bring great challenges for stable operation and control of the power grid. In order to cope with the impact caused by large-scale electric vehicle connected to the grid and promote the development of electric vehicles, it is essential to study the charging load forecasting theory. Therefore, How to build charging model of electric vehicles is focused on in this paper, and then control the electric vehicles to charge or discharge under the smart grid environment to eliminate negative impact when electric vehicles connected to the grid disorderly. The main contents include the following aspects:The development of electric vehicles at home and abroad is discussed, and then the characteristics and the influencing factors of electric vehicle charging load are analyzed. Some important factors such as drive habits, the battery characteristics, charging mode, different types of electric vehicles and development scale of EVS are analyzed and studied, which is the basis of.building charging load model.Private cars was taken for example in this paper take, then their driving behavior, charging mode, charging characteristics are analyzed. The probability distribution functions of mileage in one day and the start time of charging are established according to statistics data of conventional cars, the number of electric vehicles in Beijing is predicted, then the Monte Carlo is used to simulate and calculate charging load, predict future charging load curve, and analyze the impact of charging load on the grid according to the predicted curve.A method of forecasting charging load based on fuzzy inference system is proposed in the paper then. The travel characteristics of electric vehicles is analyzed, and the fuzzy inference system is used to emulate the process of drives deciding to charge their cars, the charging probability is attained in the given location. Finally, the daily profile of charging load can be predicted according to the numbers of electric vehicles forecasted in Beijing. This method can better simulate actual electric vehicle charging process, and the load forecasting curve is more realistic to design an electric car and operate the power grid.The contradiction between electric vehicles and the traditional grid are analyzed finally, and the ways to solve these contradictions is to control electric vehicles charging or discharging under smart grid environment. Then the coordinated charging strategy and the technology of vehicles to grid(V2G) are analyzed. Finally the coordinated charging model and the V2 G model are built and simulated, and the influence of charging load on the origin load curve is analyzed based on the simulation results.
Keywords/Search Tags:electric vehicle, charging load forecasting, Monte Carlo, fuzzy inference, smart grid, coordinated charging, V2G
PDF Full Text Request
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