华东师范大学学报（自然科学版） ›› 2023, Vol. 2023 ›› Issue (2): 143-154.doi: 10.3969/j.issn.1000-5641.2023.02.015

• 计算机科学 • 上一篇    下一篇

基于基尔霍夫定律和布尔方程的故障定位算法

鲁晓秋1(), 蔡阳1, 陈佳俊1, 周樨1, 周雪茗2, 唐赟喆2, 黄定江2,*()   

  1. 1. 国家电网上海市电力公司 金山供电公司, 上海　200540
    2. 华东师范大学 数据科学与工程学院, 上海　200062
  • 收稿日期:2021-08-25 出版日期:2023-03-25 发布日期:2023-03-23
  • 通讯作者: 黄定江 E-mail:lu_xq@126.com;djhuang@dase.ecnu.edu.cn
  • 作者简介:鲁晓秋, 男, 高级工程师, 研究方向为电力系统自动化. E-mail: lu_xq@126.com
  • 基金资助:
    国家自然科学基金(U1711262, 62072185, U1811264)

Fault location algorithm based on Kirchhoff ’s law and a Boolean equation

Xiaoqiu LU1(), Yang CAI1, Jiajun CHEN1, Xi ZHOU1, Xueming ZHOU2, Yunzhe TANG2, Dingjiang HUANG2,*()   

  1. 1. Jinshan Power Supply Company, State Grid Shanghai Electric Power Company, Shanghai　200540, China
    2. School of Data Science and Engineering, East China Normal University, Shanghai　200062, China
  • Received:2021-08-25 Online:2023-03-25 Published:2023-03-23
  • Contact: Dingjiang HUANG E-mail:lu_xq@126.com;djhuang@dase.ecnu.edu.cn

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摘要：

随着我国电力系统的不断发展, 供电的安全性和可靠性直接影响着地区的生产生活和民众的经济生活. 电网故障定位是电力调度系统中重要的组成部分. 传统的故障定位需要依靠调度人员大量的经验积累和人工判断, 而面对日益增长的需求, 仅依靠传统方法进行故障定位会增加误判率, 进而对电力系统的稳定运行造成威胁. 提出了一种基于基尔霍夫定律和布尔方程的电网故障定位算法, 将故障定位问题转化为布尔线性混合规划问题, 并结合模拟退火算法和遗传算法的思想进行求解, 实现了在小型电网中的故障快速定位, 有效降低了调度错误率, 缩短了从故障发生到故障隔离、故障处理的时间差, 节约了人力资源, 提高了调度效率.

关键词: 故障定位, 布尔方程, 基尔霍夫定律, 遗传算法

Abstract:

With the continuous development of China’s electric power system, the security and reliability of power supply directly affects regional production output and people’s economic life. As an important part of the power dispatch system, traditional fault locations rely on the cumulative experience and manual judgment of dispatchers. Faced with increasing demands, fault locations that rely solely on the traditional method are likely to result in an increase in misjudgment rates and pose a threat to the stable operation of the power system. This paper proposes a Boolean equation based on Kirchhoff’s law and the grid fault location algorithm to address this challenge. The fault location issue can effectively be converted to Boolean linear mixed programming problems and combined with simulated annealing algorithms. When these genetic algorithms are applied to the idea of a network and realized in the grid for fast positioning of small faults, the scheduling error rate can be reduced and the time difference from fault occurrence to fault isolation and fault processing can be shortened; in turn, this saves human resources and improves scheduling efficiency.

Key words: fault location, Boolean equation, Kirchhoff’s law, genetic algorithm

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