Pengfei Lv, Dapeng Wang, H. Sun, B. Guo, Rila Sachu
{"title":"On-line phase-splitting intelligent analysis of line loss in low-voltage platform based on genetic algorithm","authors":"Pengfei Lv, Dapeng Wang, H. Sun, B. Guo, Rila Sachu","doi":"10.1117/12.2671452","DOIUrl":null,"url":null,"abstract":"When the power connection between the station area and the user changes, it is necessary to realize the user's return journey and return journey confirmation as soon as possible, which can improve the level of line loss management. Based on RBF neural adaptive genetic algorithm, the \"intelligent analysis system of line Loss online phase division in low-voltage substation\" can automatically control the phase reversal without manual intervention of base station users. Intelligent analysis of line loss and phase division of low voltage transformer is carried out by integrating various data of instrument. Based on the analysis of traditional circuit theory, a complete theoretical line loss calculation strategy is developed by using depth-first node determination method, supplemented by advanced artificial intelligence algorithm, which can achieve fast and accurate calculation under the condition of limited measurement data. To develop and build intelligent tools for substation regional line loss management, provide technical tools for substation regional line loss monitoring and control for line loss managers, improve the level of line information, damage calculation and analysis.","PeriodicalId":202840,"journal":{"name":"International Conference on Mathematics, Modeling and Computer Science","volume":"81 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Mathematics, Modeling and Computer Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1117/12.2671452","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
When the power connection between the station area and the user changes, it is necessary to realize the user's return journey and return journey confirmation as soon as possible, which can improve the level of line loss management. Based on RBF neural adaptive genetic algorithm, the "intelligent analysis system of line Loss online phase division in low-voltage substation" can automatically control the phase reversal without manual intervention of base station users. Intelligent analysis of line loss and phase division of low voltage transformer is carried out by integrating various data of instrument. Based on the analysis of traditional circuit theory, a complete theoretical line loss calculation strategy is developed by using depth-first node determination method, supplemented by advanced artificial intelligence algorithm, which can achieve fast and accurate calculation under the condition of limited measurement data. To develop and build intelligent tools for substation regional line loss management, provide technical tools for substation regional line loss monitoring and control for line loss managers, improve the level of line information, damage calculation and analysis.