基于双层粒子群算法的主动配电网分布式电源规划

Optimal Distributed Generation Planning in Active Distribution Network Based on Bi-level Particle Swarm Optimization Algorithm

随着电力市场化程度的提高,主动配电网中需求侧资源与分布式电源的协调综合优化利用能减缓高峰时段电网阻塞,提高电力资产利用率。分布式电源规划与科学合理的接入对主动配电网中需求侧资源的优化利用至关重要。论文选取风力发电机、光伏发电机和微型燃气轮机为待规划分布式电源,以年综合费用最小为目标函数,以分布式电源渗透率、年最大负荷中断量、待规划节点处分布式电源装机容量等多种电气量为约束条件,建立考虑需求侧响应的分布式电源规划模型。基于分解协调思想,将模型分解为规划层和运行层,并采用双层粒子群算法求解。以IEEE33节点配电系统为算例,验证了规划方法的有效性。

With the improvement of the degree of power marketization,the coordinated and optimized utilization of demand-side resources and distributed power sources in the active distribution network can alleviate grid congestion during peak hours and increase the utilization rate of power assets.Distributed generation planning and reasonable access to the power grid are very important for the optimal utilization of demand side resources.In this paper,wind turbine generator,photovoltaic generator and micro turbine generator are selected as the distributed generation to be planned.The annual comprehensive cost minimum is taken as the objective function,and a variety of electrical parameters,such as the permeability maximum of the distributed generation,the annual load interruption maximum and the disposal capacity maximum of the distributed generation at the node to be planned,are taken as the constraint conditions.Then the distributed generation planning model considering demand side response is established.Based on the decomposition and coordination idea,the model is decomposed into planning layer and operation layer,and the bi-level particle swarm optimization algorithm is applied to solve the model.Finally the IEEE33 node distribution system is taken as an example to verify the effectiveness of the planning method.