{"title":"基于盲源分离的负荷分布分解:一种小波辅助的独立分量分析方法","authors":"Yongli Zhu, Songtao Lu","doi":"10.1109/PESGM.2014.6938947","DOIUrl":null,"url":null,"abstract":"In this paper, a Blind-source separation method, i.e. Independent Component Analysis (ICA) is used for disaggregating the substation load profile into different patterns, i.e. residential and commercial groups. The smart meter data from a down town substation has been used. Principle Component Analysis (PCA) is applied for data reduction. Wavelet analysis is used to extract the trend signal from the original load profile as inputs for the ICA routine. Final results verify the effectiveness of this load profile disaggregation approach.","PeriodicalId":149134,"journal":{"name":"2014 IEEE PES General Meeting | Conference & Exposition","volume":"286 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"25","resultStr":"{\"title\":\"Load profile disaggregation by Blind source separation: A wavelets-assisted independent component analysis approach\",\"authors\":\"Yongli Zhu, Songtao Lu\",\"doi\":\"10.1109/PESGM.2014.6938947\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, a Blind-source separation method, i.e. Independent Component Analysis (ICA) is used for disaggregating the substation load profile into different patterns, i.e. residential and commercial groups. The smart meter data from a down town substation has been used. Principle Component Analysis (PCA) is applied for data reduction. Wavelet analysis is used to extract the trend signal from the original load profile as inputs for the ICA routine. Final results verify the effectiveness of this load profile disaggregation approach.\",\"PeriodicalId\":149134,\"journal\":{\"name\":\"2014 IEEE PES General Meeting | Conference & Exposition\",\"volume\":\"286 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-07-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"25\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 IEEE PES General Meeting | Conference & Exposition\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PESGM.2014.6938947\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE PES General Meeting | Conference & Exposition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PESGM.2014.6938947","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Load profile disaggregation by Blind source separation: A wavelets-assisted independent component analysis approach
In this paper, a Blind-source separation method, i.e. Independent Component Analysis (ICA) is used for disaggregating the substation load profile into different patterns, i.e. residential and commercial groups. The smart meter data from a down town substation has been used. Principle Component Analysis (PCA) is applied for data reduction. Wavelet analysis is used to extract the trend signal from the original load profile as inputs for the ICA routine. Final results verify the effectiveness of this load profile disaggregation approach.