基于非线性互补约束的含DG配电网故障区段定位方法

荣泽成; 陈璟华; 郭壮志; 许俊宁; 陈友鹏

doi:10.12052/gdutxb.190125

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基于非线性互补约束的含DG配电网故障区段定位方法

更新时间：2026-05-27

- 基于非线性互补约束的含DG配电网故障区段定位方法
- A Fault Segment Location Method for DG Distribution Network Based on Nonlinear Complementary Constraints
- 广东工业大学学报 2020年37卷第4期页码：51-58
- 作者机构：
  
  1. 广东工业大学自动化学院,广东,广州,510006
  2. 河南工程学院电气信息工程学院,河南,郑州,451191
- 作者简介：
  
  荣泽成(1995–)，男，硕士研究生，主要研究方向为电力系统安全运行与控制，E-mail：798500473@qq.com
- 基金信息：
  
  国家自然科学基金资助项目(51707057)
- DOI：10.12052/gdutxb.190125
  中图分类号： TM771
- 网络首发：2020-07-11，
  
  纸质出版：2020
- 稿件说明：
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荣泽成, 陈璟华, 郭壮志, 许俊宁, 陈友鹏. 基于非线性互补约束的含DG配电网故障区段定位方法[J]. 广东工业大学学报, 2020, 37(4): 51-58.

Rong Ze-cheng, Chen Jing-hua, Guo Zhuang-zhi, et al. A Fault Segment Location Method for DG Distribution Network Based on Nonlinear Complementary Constraints[J]. 2020, 37(4): 51-58.
荣泽成, 陈璟华, 郭壮志, 许俊宁, 陈友鹏. 基于非线性互补约束的含DG配电网故障区段定位方法[J]. 广东工业大学学报, 2020, 37(4): 51-58. DOI： 10.12052/gdutxb.190125.

Rong Ze-cheng, Chen Jing-hua, Guo Zhuang-zhi, et al. A Fault Segment Location Method for DG Distribution Network Based on Nonlinear Complementary Constraints[J]. 2020, 37(4): 51-58. DOI： 10.12052/gdutxb.190125.

摘要

随着分布式电源的接入

配电网故障过电流方向不再唯一

传统的故障区段定位方法将不适用

本文提出含分布式电源(Distributed Generation，DG)配电网故障区段定位的非线性互补约束光滑化模型和求解方法。基于逻辑关系的间接故障定位方法在数值稳定性和决策效率上的不足

本文构建了可适应多个DG投切情况的基于代数关系的开关函数。2个仿真算例与对比实验表明

含DG配电网故障区段定位的非线性互补约束光滑化方法在进行故障定位时具有较高的容错性能

且能够实现多信息畸变下的准确定位

由此可见本方案在数值稳定性上胜于智能算法。

Abstract

With the access of distributed generation(DG)

the direction of fault overcurrent in the distribution network is no longer unique

and hence the traditional method about fault section location will not be applicable. A nonlinear complementary constrained smoothing model is proposed with a solution method for fault section location in distribution networks with DG. Considering the deficiencies in numerical stability and decision efficiency based on logical relationship of the indirect fault location method

a switch function is constructed based on algebraic relationships that can adapt to multiple DG switching situations. Two simulation algorithms and contrast experiments show that nonlinear complementary constrained smoothing method of fault section location in distribution networks with DG has a high fault tolerance performance and can achieve exact orientation under multi-information distortion

and so it can be seen that our algorithm is superior to intelligence algorithms in numerical stability.

关键词

Keywords

references

DU H W, SUN Y M , LIU H J, et al . Fault location and isolation of distribution network based on genetic algorithm [J ] . Power System Technology, 2000, 24(5): 52-55.

刘俊夫. 基于BP神经网络的配电网故障区段定位优化方法研究[D]. 恩施: 湖北民族学院, 2018.

FU J C, LU Q S. Fault sections location of distribution network based on bat algorithm [J]. Power System Protection and Control, 2015, 43(16): 100-105.

项晓鸣. 基于蝙蝠算法和元胞自动机的配电网故障定位研究[D]. 武汉: 湖北工业大学, 2017.

程璞. 基于粒子群算法的配电网故障定位研究[D]. 淮南: 安徽理工大学, 2017.

ZHENG T, PAN Y M, GUO K Y, et al . Fault location of distribution network based on immune algorithm [J ] . Power System Protection and Control, 2014, 42(1): 77-83.

QIN L J, YANG W T. Application and optimization of ant colony algorithm in fault location of distribution network [J]. Electrical Applications, 2015, 34(22): 73-76.

ZHANG B, HAO Z, BO Z. New development in relay protection for smart grid [J]. Protection and Control of Modern Power Systems, 2016, 1(1): 14.

CHEN K, ZHANG Y, WANG H Y, et al . Fault-section location of distribution network containing distributed generation based on immune algorithm [J ] . Power System Protection and Control, 2017, 45(24): 57-62.

XU P F, XING R Z. Fault location of distribution network with distributed generation supply by particle swarm optimization algorithm [J]. Power Technology, 2018, 42(4): 591-592.

ZHOU Q, ZHENG B L, LIAO R J, et al . Fault segment location of distributed generation distribution network based on particle swarm optimization and differential evolution algorithm [J ] . Power System Protection and Control, 2013, 41(4): 33-37.

WANG Y F, JIA Y B. Improved matrix algorithm for fault location in DG distribution network [J]. Computer Simulation, 2018, 35(4): 58-64.

LIU P C, LI X L. Fault-section location of distribution network containing distributed generation based on the multiple-population genetic algorithm [J]. Power System Protection and Control, 2016, 44(2): 36-41.

WU X H, ZHENG M, TANG X B, et al . A new matrix algorithm for fault section locating in distribution system [J ] . Journal of Nanjing Normal University (Engineering Technology), 2003(2): 54-57.

LUO M, YANG H G. An improved general matrix algorithm for fault locating in distribution system [J]. Power System Protection and Control, 2012, 40(5): 64-68.

WEI Z N, HE H, ZHENG Y P. A refined genetic algorithm for the fault sections location [J]. Proceedings of the CSEE, 2002(4): 128-131.

GUO Z Z, XU Q X, HONG J J, et al . Integer linear programming based fault section diagnosis method with high fault-tolerance and fast performance for distribution network [J ] . Proceedings of the CSEE, 2017, 37(3): 786-795.

GUO Z Z, XU Q X, HONG J J, et al . A novel fault section location model with complementarity constraints and its optimization algorithm for distribution network [J ] . Proceedings of the CSEE, 2016, 36(14): 3342-3751.

CHEN H, ZHOU Y S, LIU S H, et al . Fault location of DG-containing distribution network based on improved harmony algorithm [J ] . Journal of Electric Power Science and Technology, 2018, 33(2): 123-128.

TAO W Q, YANG G, DING M, et al . Application of improved memetic algorithm in fault location of DG distribution network [J ] . Journal of Electronic Measurement and Instrument, 2016, 30(2): 265-273.

PEI W J, TAN Y H, WANG F, et al . Application of bat algorithm in fault location of DG distribution network [J ] . Computer Engineering and Applications, 2016, 52(22): 218-221.

WANG D, WU X Q, WANG Z H. Fault location of distributed generation distribution network based on improved genetic algorithm [J]. Journal of Northeast Electric Power University, 2016, 36(1): 1-7.

黄知伟. 基于云粒子群算法的含DG配电网故障定位[D]. 武汉: 湖北工业大学, 2016.

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