含新能源发电的电动汽车充电站充电功率在线优化策略研究

Research on on-line charging power optimization strategy for EV charging station with renewable energy generation

针对含新能源发电系统的电动汽车充电站充电功率优化问题,提出了一种充电功率在线实时优化策略,依据新能源发电出力及电动汽车当前状态信息动态调整未来24 h内充电站各充电桩充电功率,该在线优化策略依据电动汽车充电负荷特点,在初始化阶段利用基于状态依赖的决策向量分类方法,降低了每次优化待优化矩阵维度;在优化过程中利用微分演化算法,分别对有效决策向量组合以及决策向量进行优化,旨在快速、准确地对充电站中各充电桩未来24 h内的充电计划进行实时优化。该优化策略对降低充电站运行成本、改善因电动车充电引起的负荷波动具有一定的参考价值。

Aiming at the charging power optimization problem of EV charging stations with renewable energy generations,an on-line optimization strategy of charging power in real time is proposed.During the optimization process,a state dependence based decision variables classification method in the initial stage is proposed to reduce the optimized matrix dimensions.In the optimization process,the differential evolution algorithm(DEA)is utilized to optimize the effective decision vector combination and decision vector respectively,by which both the quickness and accuracy can be achieved to optimize the charging plan of each charging pile in the charging station in the next 24 hours.The proposed optimization strategy has a certain reference value for reducing the charging cost and improving load fluctuation caused by EV charging.