基于遗传算法的电网故障行波定位装置的优化配置

李泽文; 易志鹏; 杨毅; 李想; 杨雨薇

引用本文:	李泽文,易志鹏,杨毅,等.基于遗传算法的电网故障行波定位装置的优化配置[J].电力系统保护与控制,2015,43(3):77-83.
	LI Zewen,YI Zhipeng,YANG Yi,et al.Optimal placement of traveling wave fault location equipment for power grid based on genetic algorithm[J].Power System Protection and Control,2015,43(3):77-83

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基于遗传算法的电网故障行波定位装置的优化配置
李泽文¹, 易志鹏^1,2, 杨毅¹, 李想¹, 杨雨薇³
1.智能电网运行与控制湖南省重点实验室,长沙理工大学，湖南长沙 410114;2.国网黄山供电公司，安徽黄山 245000;3.湖南省电力培训中心，湖南长沙 410131

摘要:

为了提高电网故障行波定位系统的稳定性和经济性，提出了一种电网故障行波定位装置的优化配置方法。该方法首先根据配置规则建立的约束关系进行故障行波定位装置的初始配置，然后运用遗传算法对得到的初始配置方案进行优化，最后对于行波定位装置配置数目相同的方案根据配置冗余度进行方案优选。该方法将优化过程与配置过程有效结合，可缩小遗传算法的寻优范围，从而提高遗传算法的求解速度。最后对某系统进行仿真验证表明，经过优化后的配置方案可以在不影响电网故障定位鲁棒性和准确性的基础上适当减少故障行波定位装置的配置，有利于节约投资。

关键词: 行波故障定位优化配置遗传算法冗余度

DOI：10.7667/j.issn.1674-3415.2015.03.011

分类号:

基金项目:国家自然科学基金项目(51377012，51207013)；湖南省科技重大专项(2012FJ1003)；湖南省自然科学基金项目(13JJ6044)；湖南省教育厅重点项目(14A002)；湖南省高校产业化培育项目(13CY008)

Optimal placement of traveling wave fault location equipment for power grid based on genetic algorithm

LI Zewen¹, YI Zhipeng^1,2, YANG Yi¹, LI Xiang¹, YANG Yuwei³

1.Hunan Province Key Laboratory of Smart Grids Operation and Control, Changsha University of Science and Technology, Changsha 410114, China;2.Hunan Electric Power Corporation Training Center, Changsha 245000, China;3.Hunan Electric Power Training Center, Changsha 410131, China

Abstract:

In order to improve the economy of the power grid traveling wave fault location system, an optimal method of power grid traveling wave fault location equipment (TWFLE) is proposed. First, configuration rules are established under the constraint relationships TWFLE initial configuration, and then genetic algorithm is used to optimize the initial configuration, the solutions of final configuration with the same number are selected based on large redundancy configuration. The configuration process and optimization effective integration process are combined, which can reduce the scope of genetic algorithm optimization and thus improve solution speed. Simulation results show that the optimal scheme can reduce the number of TWFLE without influence on reliability and accuracy of fault location, so it can save investment effectively.

Key words: traveling wave fault location optimal placement genetic algorithm redundancy

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