Mingyue Ding, Jinxiao Huang, Jiazhen Li, N. Mastorakis, X. Zhuang
{"title":"Real-Time Load Identification by Active Power Feature Extraction and Switching Detection","authors":"Mingyue Ding, Jinxiao Huang, Jiazhen Li, N. Mastorakis, X. Zhuang","doi":"10.1109/MCSI.2016.030","DOIUrl":null,"url":null,"abstract":"With the intelligent development of the power system, load identification becomes an important task. A noninvasive household load identification method is proposed in this paper, which can be used to detect the load switching moments and identify the types of loads. A calculation method of feature value is proposed based on active power. A template method is proposed to detect the jumping of the feature curve, which can determine the load switching moments robustly and accurately. The types of loads can be identified by a threshold value method. The results show that the method can accurately determine the load switching moments and identify the types of loads, and it also has good robustness.","PeriodicalId":421998,"journal":{"name":"2016 Third International Conference on Mathematics and Computers in Sciences and in Industry (MCSI)","volume":"158 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 Third International Conference on Mathematics and Computers in Sciences and in Industry (MCSI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MCSI.2016.030","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
With the intelligent development of the power system, load identification becomes an important task. A noninvasive household load identification method is proposed in this paper, which can be used to detect the load switching moments and identify the types of loads. A calculation method of feature value is proposed based on active power. A template method is proposed to detect the jumping of the feature curve, which can determine the load switching moments robustly and accurately. The types of loads can be identified by a threshold value method. The results show that the method can accurately determine the load switching moments and identify the types of loads, and it also has good robustness.