Open AccessResearch on Distribution Network Fault Location based on Improved Genetic Algorithm
Author(s) -
Hao Wang,
Kaifeng Mei,
Zhu Chen,
Chengjian Zhai,
Meng Li
Publication year - 2022
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2216/1/012053
Subject(s) - recloser , fault (geology) , genetic algorithm , convergence (economics) , computer science , algorithm , key (lock) , automation , engineering , machine learning , electrical engineering , computer security , mechanical engineering , circuit breaker , seismology , economic growth , economics , geology
Compared with the traditional recloser fault location without communication channel, feeder automation based on FTU is in line with the development of modern distribution system. FTU plays a key role in the whole system, but the location is inaccurate due to the lack of information caused by FTU itself or communication fault. When using genetic alogrithms for distribution network fault location, the result often converges prematurely or converges to an infeasible solution due to algorithm reasons. Aiming at the above problems, an improved genetic algorithm is proposed for distribution network fault location. Through simulation analysis, it can be found that the improved genetic algorithm has high convergence and good optimal fitness, which can better solve the convergence problems of the unmodified algorithm, which is of great significance for distribution network fault location.