寇凌峰, 刘自发, 周 欢. 区域电动汽车充电站规划的模型与算法[J]. 现代电力, 2010, 27(4): 44-48.
引用本文: 寇凌峰, 刘自发, 周 欢. 区域电动汽车充电站规划的模型与算法[J]. 现代电力, 2010, 27(4): 44-48.
Kou Lingfeng, Liu Zifa, Zhou Huan. Modeling Algorithm of Charging Station Planning for Regional Electric Vehicle[J]. Modern Electric Power, 2010, 27(4): 44-48.
Citation: Kou Lingfeng, Liu Zifa, Zhou Huan. Modeling Algorithm of Charging Station Planning for Regional Electric Vehicle[J]. Modern Electric Power, 2010, 27(4): 44-48.

区域电动汽车充电站规划的模型与算法

Modeling Algorithm of Charging Station Planning for Regional Electric Vehicle

  • 摘要: 合理确定电动汽车充电站的规模及位置, 建立了一种电动汽车充电站选址定容的最优费用模型。模型以居民负荷的分布情况模拟电动汽车的数量, 用层次分析法给出候选站址的权系数, 在候选站址与变电站的距离、电动汽车充电站的安装费用、电动汽车数量等条件的约束下, 目标函数还加入了充电站的运行费用、网损费用和充电站配电变压器的投资。模型中电动汽车充电电价采用实时电价。为验证模型的有效性, 采用粒子群算法对一假设算例进行优化求解, 结果表明该模型具有一定的可行性。

     

    Abstract: In order to determinate reasonable scale and location of charging station for electric vehicle, the optimization cost model of locating and sizing of charging station for electric vehicle is built. The model simulates the number of electric vehicle based on the distribution of residents and the weight of candidate address is determined by using of Analytic Hierarchy Process (AHP). This proposed model includes constraints such as the distance between the substation and candidate address, installed cost of charging station for electric vehicle, the number of electric vehicle, and so on. Such variables as running cost of charging station, network loss cost and transformers investment, etc., are introduced in objective function. Charging price of electric car is real time electricity pricing. The simulation is carried out on a test example by using particle swarm optimization algorithm, and the results show that the model is effective and feasible.

     

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