基于深度优先搜索和灰狼算法的微电网重构

Optimization Method Based on Depth-first Search and Grey Wolf Optimization Algorithm for Reconfiguration of Microgrid

针对主网发生非计划故障和微电网并网转孤岛时,微电网对负荷持续供电和系统稳定运行的问题,为了从全局高度对电力网络内设备协调控制,建立了微电网重构模型,提出了一种深度优先搜索和灰狼优化算法相混合的重构方法。该方法以开关状态和可调设备的功率为优化变量,针对重构优化过程中的非辐射状网架结构问题,用深度优先搜索对网架结构进行识别、分析和处理,用前推回代法计算网络潮流分布,以灰狼优化算法为框架,获得重构方案。仿真结果表明,所提出的混合重构方法,其全局搜索能力更强,其重构结果可行并且较优,而且重构策略以开关状态和功率的组合为优化变量,比仅有开关状态或仅有功率的变量,对系统优化调整更具有优势。

In order to solve the problem of continuous load supply and stable operation of the system when the main network with unplanned faults and the microgrid shifted from grid-connected to the island mode,from a global perspective of coordinating and controlling the equipment in the power network,a microgrid reconfiguration model was established and a reconfiguration method combining depth first search and gray wolf optimization algorithm was proposed.This method took the switch state and the power of the adjustable equipment as the optimization variables.Aiming at the problem of nonradiative grid structure in the process of reconstruction and optimization,the method used depth first search to identify,analyze and process the grid structure.The method used forward and backward method to calculate the network power flow distribution,and took gray wolf optimization algorithm to obtain the reconstruction scheme.The simulation results showed that the proposed hybrid reconfiguration method had stronger global search ability,and its reconfiguration results were feasible and better.Moreover,it was more advantageous than the only switch state or power variables for system optimization and adjustment that the reconfiguration strategy took the combination of switch state and power as the optimization variables.