基于混合DE/PSO算法的分布式电源配电网故障定位

Quan Zhou, Bolin Zheng, Caisheng Wang, Junhui Zhao, Yang Wang
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引用次数: 10

摘要

故障定位一直是配电网管理中的一项重要而富有挑战性的任务。当更多的分布式发电(DG)加入到配电网中时,这个问题变得更加复杂。本文通过开发一种新的开关函数来处理多DG源配电网断路器/开关的开/关信息,提出了一种故障定位方法。该检测方法基于粒子群优化(PSO)和差分进化(DE)的二元混合算法,旨在解决“过早收敛”问题。它是一种具有信息交换机制的双种群进化方案。该算法能够自适应适应多个dg的变化。该方法可用于多源配电网的多故障区段定位。仿真结果表明,该方法既能准确有效地识别单个故障,也能有效地识别多个故障,并具有一定的容错能力。
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Fault location for distribution networks with distributed generation sources using a hybrid DE/PSO algorithm
Fault location has been an important and challenging task in distribution network management. The issue has become more complicated when more distributed generation (DG) are added to distribution networks. This paper presents a fault location method by developing a new switch function to process the ON/OFF information of circuit breakers/switches for distribution networks with multiple DG sources. The proposed detection method is based on a binary hybrid algorithm of particle swarm optimization (PSO) and differential evolution (DE), which targets for solving “premature convergence” issues. It is a two-population evolution scheme with information exchange mechanism. The algorithm can adaptively accommodate the changes caused by multiple DGs. The proposed method is used to locate multiple fault sections in multi-source distribution networks. The simulation results indicate that the proposed method can identify either single or multiple faults accurately and efficiently with the tolerance capability of error messages.
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