基于遗传粒子群法的配电网故障定位研究
投稿时间:2019-12-07  修订日期:2020-03-03  点此下载全文
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作者单位邮编
张波* 国网安徽省电力有限公司 230022
唐亮 国网安徽省电力有限公司 
梁晓伟 国网安徽省电力有限公司电力科学研究院 
李明 国网安徽省电力有限公司信息通信分公司 
张靖 国网安徽省电力有限公司信息通信分公司 
唐轶轩 国网安徽省电力有限公司信息通信分公司 
中文摘要:针对分布式电源接入后配电网故障定位困难的现状,本文构造了适应多分布式电源接入的故障电流编码方式、开关函数和评价函数,提出了基于改进遗传粒子群法的配电网故障定位方法,该方法有效融合了遗传算法在全局搜索方面和粒子群法在局部搜索方面的优势。建立配电网故障定位仿真实例,通过配电网系统单重故障和多重故障及FTU上传故障信息出现畸变情况的仿真对比分析,结果表明本文方法具有更高的定位准确率和较快的收敛速度,且本文方法抗干扰性更强。本文研究成果可为配电网故障定位提供有效的参考和技术指导。
中文关键词:配电网  故障定位  分布式电源  遗传算法  粒子群算法
 
Research on Fault Location of Distribution Network Based on GeneticParticle Swarm Optimization
Abstract:In view of the difficulty in locating distribution network fault after the access of distributed power supply, fault current coding mode, switching function and evaluation function are constructed to adapt to multi-distributed power supply access in this paper, and a fault location method based on improved genetic particle swarm optimization is proposed, the method effectively combines the advantages of genetic algorithm in global search and particle swarm optimization in local search. A simulation example of distribution network fault location is presented, the simulation of single fault and multiple fault of distribution network system and the distortion of fault information uploaded by FTU were compared and analyzed, the results show that the proposed method has higher accuracy and faster convergence rate, and the method in this paper has stronger anti-interference. The research results of this paper can provide effective reference and technical guidance for fault location of distribution network.
keywords:distribution network  fault location  distributed power supply  genetic algorithm  particle swarm optimization
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