蒋怡静, 于艾清, 屠亚南. 基于IBQPSO算法的电动汽车时空双尺度有序充电引导策略[J]. 现代电力, 2019, 36(6): 1-8.
引用本文: 蒋怡静, 于艾清, 屠亚南. 基于IBQPSO算法的电动汽车时空双尺度有序充电引导策略[J]. 现代电力, 2019, 36(6): 1-8.
JIANG Yijing, YU Aiqing, TU Yanan. Coordinated Charging Strategy for Electric Vehicles in Temporal-spatial    Dimension Based on IBQPSO Algorithm[J]. Modern Electric Power, 2019, 36(6): 1-8.
Citation: JIANG Yijing, YU Aiqing, TU Yanan. Coordinated Charging Strategy for Electric Vehicles in Temporal-spatial    Dimension Based on IBQPSO Algorithm[J]. Modern Electric Power, 2019, 36(6): 1-8.

基于IBQPSO算法的电动汽车时空双尺度有序充电引导策略

Coordinated Charging Strategy for Electric Vehicles in Temporal-spatial    Dimension Based on IBQPSO Algorithm

  • 摘要: 大规模电动汽车的无序充电会影响电网的安全经济运行,以车联网系统为基础,提出电动汽车的充电行为引导策略。充电站运营商按用户在时间和空间上接受充电引导所起的作用对于整体调度作用的贡献程度,分别对用户进行费用补偿,在此基础上建立时空双尺度有序充电引导模型。其次,提出一种IBQPSO算法求解规划问题。最后,通过具体算例对模型进行仿真,结果能满足电网、充电站运营商和电动汽车用户三方的利益,表明了模型与算法的可行性与有效性。

     

    Abstract: The disorderly charging of large-scale electric vehicles will affect the safe and economic operation of the power grid. The charging behavior of electric vehicles needs to be guided by the cost compensated by the charging station operator according to contribution of user’s guided charging behavior in temporal and spatial levels to the grid scheduling. Based on this, a temporal-spatial charging guidance model is established. Then, an IBQPSO algorithm is proposed based on Bloch sphere to solve the model. Finally, the simulated results of a specific example show that the interests of the grid, charging station operators and electric vehicle users can be meet, and the feasibility and effectiveness of the model and algorithm are verified.

     

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