均衡不同主体利益的集中型充电站多目标二层规划

Multi-objective Bi-level Programming of Centralized Charging Station Considering Benefits Balance for Different Subjects

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。

The construction main bodies of centralized charging stations are getting more and more diversified along with the deepening of reform of electric power systems.In order to balance the benefits between independent developers of centralized charging stations and distribution companies,a multi-objective model adopting bi-level programming is developed for centralized charging stations,which considers the peak load shaving effects of centralized charging stations as a controllable load where wind farms are already accessible.The upper multi-objective functions are yearly reduced values of network losses and the benefits of centralized charging developers,while the lower objective function is the subsidiary benefits of centralized charging developers.The strategy of solution by combining the non-inferior sorting genetic algorithm and adaptive mutation particle swarm optimization algorithm is used to optimize the location,capacity and scheduling of the centralized charging station.The results have verified the rationality of the model and the feasibility of the algorithm.