论文部分内容阅读
随着电力体制改革的深入,集中型充电站的建设主体越来越多样化,为实现集中型充电站独立开发商和配电公司的利益均衡,在已有风电场接入的配电网中,考虑集中型充电站作为可控负荷对电网的削峰填谷作用,建立了能够反映不同主体利益的集中型充电站多目标二层规划模型。上层多目标函数为电网网损年减少值和集中型充电站开发商的效益,下层目标函数为集中型充电站的辅助收益。采用改进非劣排序遗传算法和自适应变异粒子群算法相结合的多目标二层求解策略对集中型充电站的位置、容量和调度进行优化,结果验证了该模型的合理性和算法的可行性。
With the deepening of the power system reform, the construction of centralized charging stations has become more and more diversified. In order to realize the balanced interests of independent developers and distribution companies of centralized charging stations, in the distribution network with wind farm access , A multi-objective two-level programming model of centralized charging station that can reflect the interests of different subjects is established considering the charging and discharging of centralized charging station as the peak load and valley filling of grid. The upper multi-objective function is the loss reduction value of the power grid and the benefit of the developer of the centralized charging station, and the lower objective function is the auxiliary gain of the centralized charging station. The location, capacity and scheduling of the centralized charging station are optimized by using the improved non-inferior sequencing genetic algorithm and the adaptive mutation particle swarm optimization algorithm. The results verify the rationality of the model and the feasibility of the algorithm .