基于改进人工蜂群算法的电动汽车充电策略优化

Optimization of Electric Vehicle Charging Strategy Based on Improved Artificial Bee Colony Algorithm

由于大规模电动汽车接入电网的无序充电,导致电网安全稳定的运行状态受到冲击,提出了基于改进人工蜂群算法的电动汽车充电策略优化。以获取电动汽车出行时间概率密度与电池充电特性作为关键因素,计算电动汽车充电负荷需求,基于改进人工蜂群算法建立优化模型来实现电动汽车充电策略优化。仿真实验结果表明本文所提策略优化后的电动汽车充电负荷峰谷差降低449.2kW,电网负荷波动优化效果明显。

Due to the disordered charging of large-scale electric vehicles connected to the power grid,the safe and stable operation of the power grid has been impacted. An electric vehicle charging strategy optimization based on an improved artificial bee colony algorithm is proposed. The electric vehicle travel time probability density and battery charging characteristics are obtained as key factors to calculate the electric vehicle charging load demand,and an optimization model is established based on the improved artificial bee colony algorithm to optimize the electric vehicle charging strategy. The simulation results show that the peak-to-valley difference of electric vehicle charging load is reduced by 449.2kW after the optimization of the strategy proposed in this paper,and the optimization effect of power grid load fluctuation is obvious.