风光储电动汽车换电站多目标运行优化

Multi-objective Optimization of Battery Swapping Station with Wind Photovoltaic and Energy Storage

针对可再生能源与电动汽车充换电负荷之间的协调优化问题,建立了含风光储发电单元的电动汽车换电站多目标运行优化模型。采用多种群和动态自适应策略,提出了一种改进的动态多种群多目标粒子群算法,对这一多维、多约束、非线性的多目标优化问题进行求解。以某地区实际电网数据进行算例仿真,验证了模型和算法的有效性。结果表明,优化后的风光储电动汽车换电站不仅可以实现可再生能源的就地消纳,而且有助于减小负荷峰谷差。

In allusion to the coordination between renewable energy sources （RES） and electric vehicle （EV） load, a multi-objective optimization model of the EVs＇ battery swapping station（BSS） containing wind, photovohaic（PV） and energy storage is built. As the model is multidimensional, nonlinear and having many constraints, this paper proposes an improved algorithm called dynamic multiple swarms in multi-objective particle swarm optimization （DSMOPSO） based on the multiple-swarms and dynamic adaptive strategy.A simulation based on an area＇s load data is made to show the effectiveness of the model and algorithm. The results show that the optimizated BSS can not only realize the local use of the RES, but also contribute to the peak-valley difference reduction.