{"title":"Electrical abnormality determination of the users based on EEMD","authors":"Xiaoqiang Zhong, Zhiwei Guo, Dongdong Xu, Hao Zhong, Yu Dong","doi":"10.1109/ICICIP.2014.7010314","DOIUrl":null,"url":null,"abstract":"Currently power supply enterprises have less attention on the behavior of users in electricity. It is difficult for them to find the abnormality of the power users in time. To solve this problem, this paper gave a method of abnormality determination based on EEMD. In the model, we decomposed electricity load signals into a number of intrinsic mode functions (IMF) and the residual trend. Different IMF components represent different disturbance factors of different cycles, and the residual trend represents the general trend rejecting the fluctuations. Based on the theory of power load clustering, we chose certain enterprise and got the electric load data. The correlation research of the data could be served as the diagnosis of electrical abnormality of users. The experiment shows that the method proposed in this paper can determine the electrical abnormality of users effectively.","PeriodicalId":408041,"journal":{"name":"Fifth International Conference on Intelligent Control and Information Processing","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Fifth International Conference on Intelligent Control and Information Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICICIP.2014.7010314","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
Currently power supply enterprises have less attention on the behavior of users in electricity. It is difficult for them to find the abnormality of the power users in time. To solve this problem, this paper gave a method of abnormality determination based on EEMD. In the model, we decomposed electricity load signals into a number of intrinsic mode functions (IMF) and the residual trend. Different IMF components represent different disturbance factors of different cycles, and the residual trend represents the general trend rejecting the fluctuations. Based on the theory of power load clustering, we chose certain enterprise and got the electric load data. The correlation research of the data could be served as the diagnosis of electrical abnormality of users. The experiment shows that the method proposed in this paper can determine the electrical abnormality of users effectively.