基于IWOA的配电网故障定位方法  

Fault Location Method for Distribution Network Based on Improved IWOA

作　　者：王宇杉 王晨 王淑侠[2] 邬蓉蓉 陶金磊 WANG Yushan;WANG Chen;WANG Shuxia;WU Rongrong;TAO Jinlei(School of Automation,Guangxi University of Science and Technology,Liuzhou 545616,China;School of Mechatronics,Northwestern Polytechnic University,Xi’an 710072,China;Guangxi Power Grid Co.,Ltd.Electric Power Research Institute,Nanning 530023,China;School of Electrical and Electronic Engineering,University Sains Malaysia,Penang 14300,Malaysia)

机构地区：[1]广西科技大学自动化学院,广西柳州545616 [2]西北工业大学机电学院,陕西西安710072 [3]广西电网有限责任公司电力科学研究院,广西南宁530023 [4]马来西亚理科大学电气与电子工程学院,槟城14300

出　　处：《智慧电力》2024年第11期98-105,共8页Smart Power

基　　金：国家自然科学基金资助项目(62363002)。

摘　　要：针对传统方法进行配电网故障定位时收敛速度慢和准确性低的问题,提出了一种基于改进鲸鱼优化算法(IWOA)的配电网故障定位方法。首先,通过Circle混沌映射优化初始种群,调整螺旋因子、惯性权重和收敛因子以提升收敛速度和全局搜索能力,并融入大猩猩算法竞争机制,提升局部搜索能力。其次,通过对故障馈线段建模,并结合IWOA优化故障定位精度与速度。最后,通过仿真实验对IWOA、鲸鱼算法(WOA)、灰狼算法(GWO)、粒子群优化灰狼算法(PSOGWO)进行对比,结果表明IWOA在准确性和速度上有显著优势,且准确率在94.6%以上。A fault location method for distribution networks based on the improved whale optimization algorithm(IWOA)is proposed to address the problems of slow convergence speed and low accuracy in traditional methods.Firstly,the initial population is optimized through Circle chaotic mapping,and the spiral factor,inertia weight,and convergence factor are adjusted to improve the convergence speed and global search ability.The Gorilla algorithm competition mechanism is also incorporated to enhance local search ability.Secondly,by modeling the fault feeder line segment and combining it with IWOA to optimize the accuracy and speed of fault location.Finally,in the simulation experiment,IWOA is compared with whale algorithm(WOA),grey wolf algorithm(GWO),and particle swarm optimization grey wolf optimization(PSOGWO).The results show that IWOA has significant advantages in the accuracy and speed,with an accuracy rate of over 94.6%.

关 键 词：配电网 故障定位 鲸鱼算法 分布式电源 大猩猩算法 

分 类 号：TM727[电气工程—电力系统及自动化]