{"title":"一种基于神经元网络的从电表面板的能量记录中识别家用电器使用模式的程序","authors":"A. Prudenzi","doi":"10.1109/PESW.2002.985144","DOIUrl":null,"url":null,"abstract":"The paper illustrates an artificial neural network (ANN) based procedure for the identification of pattern-of-use of some main domestic electric appliances from daily profiles of energy recordings taken at household's meter panel at 15 minute steps. The paper describes the architecture used which is structured into multiple subsequent stages based on ANNs. The application of the procedure to some real daily load diagrams as recorded at few household meters demonstrates the efficiency of the proposed approach. The utility of ANNs for extracting further useful information concerning energy usage from data bases typically available for electric companies is finally discussed.","PeriodicalId":198760,"journal":{"name":"2002 IEEE Power Engineering Society Winter Meeting. Conference Proceedings (Cat. No.02CH37309)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2002-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"116","resultStr":"{\"title\":\"A neuron nets based procedure for identifying domestic appliances pattern-of-use from energy recordings at meter panel\",\"authors\":\"A. Prudenzi\",\"doi\":\"10.1109/PESW.2002.985144\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The paper illustrates an artificial neural network (ANN) based procedure for the identification of pattern-of-use of some main domestic electric appliances from daily profiles of energy recordings taken at household's meter panel at 15 minute steps. The paper describes the architecture used which is structured into multiple subsequent stages based on ANNs. The application of the procedure to some real daily load diagrams as recorded at few household meters demonstrates the efficiency of the proposed approach. The utility of ANNs for extracting further useful information concerning energy usage from data bases typically available for electric companies is finally discussed.\",\"PeriodicalId\":198760,\"journal\":{\"name\":\"2002 IEEE Power Engineering Society Winter Meeting. Conference Proceedings (Cat. No.02CH37309)\",\"volume\":\"60 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2002-08-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"116\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2002 IEEE Power Engineering Society Winter Meeting. Conference Proceedings (Cat. No.02CH37309)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PESW.2002.985144\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2002 IEEE Power Engineering Society Winter Meeting. Conference Proceedings (Cat. No.02CH37309)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PESW.2002.985144","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A neuron nets based procedure for identifying domestic appliances pattern-of-use from energy recordings at meter panel
The paper illustrates an artificial neural network (ANN) based procedure for the identification of pattern-of-use of some main domestic electric appliances from daily profiles of energy recordings taken at household's meter panel at 15 minute steps. The paper describes the architecture used which is structured into multiple subsequent stages based on ANNs. The application of the procedure to some real daily load diagrams as recorded at few household meters demonstrates the efficiency of the proposed approach. The utility of ANNs for extracting further useful information concerning energy usage from data bases typically available for electric companies is finally discussed.