An Enhanced Intelligent Algorithm on Fault Location System

With the rapid development of modern society and the gradual improvement of people's living standards, the society and individuals have put forward higher requirements for safety and reliability of power supply. Therefore, the development of power distribution automation system as one of the important ways to improve the safety and reliability of power supply, when the fault occurs, the feeder terminal can report the fault information to the master station; then the master station, according to the corresponding information reported, uses the corresponding algorithm to detect the fault location quickly and accurately, and isolate it. For the non-fault power outage area, power supply is restored to reduce the loss of production and life. Therefore, studying the fault location and isolation technology for distribution network is very important to improve the reliability of distribution network. At present, the research on the fault location of smart grid has made some progress, and many scholars have proposed different programs respectively. In a published research, the developed software system can realize the information interaction among Energy Management System (EMS), Supervisory Control and Data Acquisition (SCADA) and Fault Information System (FIS); when complicated and rare faults occur, it can support operators to determine and change the fault component rapidly, so as to shorten the handling time of accidents and improve the efficiency of accident handling. In another study, the researchers improved particle swarm optimization for wavelet neural networks, and used the improved method for distribution network fault location, providing an important reference for the design and research of practical fault location system.