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电动汽车充电站选址优化研究
引用本文:杨现青,刘法胜,杨玲玲.电动汽车充电站选址优化研究[J].交通科技与经济,2016(3):14-18.
作者姓名:杨现青  刘法胜  杨玲玲
作者单位:山东科技大学 交通学院,山东 青岛,266590
摘    要:电动汽车充电站是影响电动汽车发展的一个重要因素,对电动车的推广具有重要意义。当前充电站配套设施建设的滞后阻碍电动汽车的发展。充电站建设前期选址是否合理影响着充电站的运营效益、服务质量以及安全性。针对当前电动汽车充电站选址布局的研究现状,总结影响充电站选址布局的因素和充电站选址布局原则。在满足选址原则的基础上,考虑充电需求点分布,建立以充电服务半径和充电站最大服务数量为约束的充电站收益最大化的非线性目标函数。为求解目标函数,利用遗传算法对目标函数进行寻优处理。最后通过仿真算得充电站的位置和服务充电需求点的范围。算例仿真表明,该模型能够实现较优的选址方案,为充电站的选址工作提供参考。

关 键 词:电动汽车  充电站选址  最大收益  遗传算法

Study on the Site Selection Optimization of Electric Vehicle Charging Station
Abstract:Electric vehicle charging station is an important factor affecting the development of electric vehicles ,the promotion of electric vehicles is of great significance .At present ,the construction of the supporting facilities of the charging station lags behind the development of the electric vehicle ,w hich has already hindered the development of the electric vehicle .And for the charging station construction site is reasonable to affect the charging station operating efficiency ,quality of service and security .Firstly ,this paper analyzed the current situation of the research on the location and layout of the charging station of the electric vehicle ,and summarized the factors that affect the location and layout of the charging station and the principle of the location and layout of the charging station . On the basis of meeting the location principle ,a nonlinear objective function was established ,which was based on the charge demand point distribution ,and establishes the maximum service radius of the charging station and the maximum service quantity of the charging station .In order to solve the objective function ,genetic algorithm was used to optimize the objective function .At last ,the location of the charging station and the range of the charging demand point were calculated by the simulation .Simulation results show that the proposed model can achieve a better site selection ,in reality ,it can provide some reference for the site selection of the charging station .
Keywords:electric vehicle  charging station location  maximum benefit  genetic algorithm
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