智慧电力2024,Vol.52Issue(2) :63-70.

基于连接状态定位的智能变电站二次系统故障定位方法

Fault Location Method for Intelligent Substation Secondary System Based on Connection State Location

李远 苏适 杨家全 王志明 潘振宁
智慧电力2024,Vol.52Issue(2) :63-70.

基于连接状态定位的智能变电站二次系统故障定位方法

Fault Location Method for Intelligent Substation Secondary System Based on Connection State Location

李远 1苏适 2杨家全 2王志明 3潘振宁4
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作者信息

  • 1. 云南电网有限责任公司红河供电局,云南蒙自 661100
  • 2. 云南电网有限责任公司电力科学研究院,云南昆明 650217
  • 3. 南方电网数字电网集团有限公司,广东广州 510000
  • 4. 华南理工大学电力学院,广东广州 510640
  • 折叠

摘要

变电站二次回路及系统运行状态因设备自身及物理连接等原因具有一定的不确定性,二次系统故障定位难度较大.提出一种基于连接状态定位的智能变电站二次系统故障定位方法.首先将二次系统设备拓扑连接关系抽象为矩阵描述,二次系统设备节点状态量作为相应矩阵元素;然后通过矩阵算法对二次系统连接状态进行定位,确定与故障有关的矩阵元素;在连接状态定位后利用模糊径向基神经网络将故障相关矩阵元素与故障集中各故障情况对应,进行故障搜索定位.故障算例结果表明,所提出的二次系统故障定位方法具有较高的准确率.

Abstract

The secondary circuit of substation and the operating state of system have certain uncertainties caused by the equipment itself and physical connection,and it is difficult to locate the fault in the secondary system.This paper proposes a fault location method for the secondary system in smart substations based on connection state location.Firstly,the topological connection relationship of the secondary system equipment is abstracted into a matrix description,and the state parameters of the secondary system are used as the corresponding matrix elements.Then the secondary system connection state is located with a matrix algorithm to determine the matrix elements related to the fault.After locating the connection state,the fuzzy radial basis(RBF)neural network is used to make the fault correlation matrix elements corresponding to the fault conditions in a fault set,and the fault search and location are carried out.The results of the fault example show that the proposed fault location method for the secondary system has high fault location accuracy.

关键词

智能变电站/二次系统/连接状态/模糊径向基神经网络/故障搜索定位

Key words

smart substation/secondary system/connection state/RBF neural network/fault search and location

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基金项目

国家自然科学基金(52207105)

云南电网公司科技项目(YNKJXM20220131)

出版年

2024
智慧电力
陕西省电力公司

智慧电力

CSTPCDCSCD北大核心
影响因子:0.831
ISSN:1673-7598
被引量3
参考文献量27
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