基于白鲸优化算法的配电网故障恢复方法  

Distribution Network Fault Recovery Strategy Based on Beluga Whale Optimization Algorithm

作　　者：田书欣 付斌 符杨 米阳 李振坤 苏向敬 TIAN Shuxin;FU Bin;FU Yang;MI Yang;LI Zhenkun;SU Xiangjing(School of Electrical Engineering,Shanghai University of Electric Power,Shanghai 200090,China)

机构地区：[1]上海电力大学电气工程学院,上海200090

出　　处：《上海电力大学学报》2024年第3期206-213,共8页Journal of Shanghai University of Electric Power

基　　金：国家自然科学基金(52007112)。

摘　　要：提出了一种基于白鲸优化(BWO)算法的配电网故障恢复方法。首先,建立光储、风储系统模型以及负荷模型,以故障后重要负荷损失量最小为目标函数,进行配电网的初步孤岛划分。其次,以网络损耗和开关操作次数加权求和最小为目标,采用BWO算法求解,获取孤岛划分与开关操作配合的故障恢复结果。然后,通过3种场景对比,验证了所提方法能够在不同故障时段获得配电网故障恢复的最优结果。最后,将BWO算法与二进制粒子群优化算法、灰狼优化算法的运行结果进行对比,验证了BWO算法寻优效果更好。A distribution network fault recovery method using the beluga whale optimization(BWO)algorithm is proposed.Firstly,the optical storage and wind storage system models as well as the load model are established.The initial islanding of the distribution network is performed with the objective function of minimizing the amount of important load loss after a fault.Secondly,with the objective of minimizing the weighted sum of network loss and the number of switch operations,the BWO algorithm is used to solve the problem and obtain the fault recovery results of the islanding and switch action cooperation.Thirdly,three scenarios are set up for comparison to verify that the proposed method is able to produce optimal fault recovery results for distribution networks at different fault times.Finally,the results of BWO algorithm are compared with binary particle swarm optimization algorithm and gray wolf optimization algorithm,and the results show that BWO algorithm has better optimization effect.

关 键 词：配电网 白鲸优化算法 故障恢复 孤岛划分 网络重构 风光荷时变性 

分 类 号：TM734[电气工程—电力系统及自动化]