A multi-objective optimisation of relay protection settings in distribution networks based on improved grey wolf algorithm
Haicheng Zhou,
Hengchu Shi,
Qiutao Chen,
Penghui Yang and
Xi Zhang
International Journal of Energy Technology and Policy, 2024, vol. 19, issue 3/4, 302-320
Abstract:
In order to overcome the problems of high data mining accuracy, poor effectiveness, and long relay protection action time in traditional methods, a multi-objective optimisation method of relay protection settings in distribution networks based on improved grey wolf algorithm is proposed. Random forest algorithm is used for mining relay protection data in distribution networks. Taking the relay protection settings as the parameters to be optimised, a multi-objective optimisation function for relay protection settings is constructed using parameters such as relay protection action time, transmission line weight coefficient, and weight factors of vulnerability and sensitivity constraints. The improved grey wolf algorithm is used to solve the objective function and obtain relevant results. According to the analysis of relevant test results, the maximum data mining accuracy of the proposed method is 98.75%, good optimisation effect, and a maximum relay protection action time of 0.87 s.
Keywords: improved grey wolf algorithm; distribution network; relay protection settings; multi-objective optimisation; random forest algorithms; objective function. (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:ids:ijetpo:v:19:y:2024:i:3/4:p:302-320
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