含不同集群电动汽车的微电网优化调度

Microgrid optimization dispatching with different clusters of electric vehicles

文章考虑微电网中的可再生能源出力,针对不接受微电网直接调度的电动汽车集群,提出一种基于等效负荷的实时电价策略进行电动汽车有序充、放电引导。该策略与微电网直接调度策略相结合,对不同集群电动汽车进行充、放电管理,并综合考虑环境效益、车主收益与微网运行状态,建立了以微电网综合运行成本最低、负荷波动最小为目标的优化模型,并用灰狼优化算法求解。优化结果表明,所提出的策略能够合理调度各可控发电单元,引导电动汽车有序充、放电,减少微电网运行成本,降低等效负荷的波动。

The interaction between the electric vehicle and the micro-grid can effectively solve many negative problems caused by the disorderly charging of a large number of electric vehicles. For electric vehicle clusters that do not receive direct dispatch from microgrids, a real-time pricing strategy based on equivalence load is proposed to guide the charging and discharging of electric vehicles. This strategy is combined with the micro-grid direct dispatch strategy to perform charge and discharge management of different clusters of electric vehicles. Based on this consideration, considering the environmental benefits, the owner’s revenue, and the microgrid operating status, an optimization model was established with the goal of minimizing the overall operating costs and minimizing the load fluctuation of the microgrid, and was solved using the gray wolf optimization algorithm. The optimization results show that by reasonably scheduling the controllable power generation units and the charging and discharging of the electric vehicles, the operating costs of the microgrid can be effectively reduced and fluctuations in equivalent loads can be reduced. Finally, by comparing with the basic particle swarm algorithm and genetic algorithm, the advantage of the gray wolf optimization algorithm for solving the microgrid optimization scheduling problem is verified.