{"title":"A Review of Research on New Power System under Typhoon Disaster","authors":"Ruizeng Wei, Huan He, Lei Wang","doi":"10.1109/ACPEE56931.2023.10135630","DOIUrl":null,"url":null,"abstract":"The integration of distributed generation(DG) into the power system has changed the original structure of the power system. In order to ensure the safe and stable operation of the new power system, further studies need to be made. First of all, this paper mainly reviews the research on the pre-disaster technology of the existing power system to cope with typhoon disasters. Then, according to different factors, the damage prediction is divided into the damage prediction considering disaster environment, the damage prediction considering disaster uncertainty, and the power failure prediction for the user area. In addition, this paper also summarizes the application of various traditional algorithms optimization algorithms and machine learning in the field of power system. Finally, by analyzing the shortcomings of the existing research, several optimization directions for the future new power system to cope with typhoon disasters are summarized.","PeriodicalId":403002,"journal":{"name":"2023 8th Asia Conference on Power and Electrical Engineering (ACPEE)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 8th Asia Conference on Power and Electrical Engineering (ACPEE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ACPEE56931.2023.10135630","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
The integration of distributed generation(DG) into the power system has changed the original structure of the power system. In order to ensure the safe and stable operation of the new power system, further studies need to be made. First of all, this paper mainly reviews the research on the pre-disaster technology of the existing power system to cope with typhoon disasters. Then, according to different factors, the damage prediction is divided into the damage prediction considering disaster environment, the damage prediction considering disaster uncertainty, and the power failure prediction for the user area. In addition, this paper also summarizes the application of various traditional algorithms optimization algorithms and machine learning in the field of power system. Finally, by analyzing the shortcomings of the existing research, several optimization directions for the future new power system to cope with typhoon disasters are summarized.