Haoyang Shen, H. Hino, N. Murata, S. Wakao, Y. Hayashi
{"title":"Automatic extraction of basic electricity consumption patterns in household","authors":"Haoyang Shen, H. Hino, N. Murata, S. Wakao, Y. Hayashi","doi":"10.1109/ICRERA.2012.6477336","DOIUrl":null,"url":null,"abstract":"Electricity consumption in households varies dependent on a lot of possible reasons such as lifestyle, family configuration, and weather. It is of great importance to optimize the electricity generation system to install for each household. In our previous work, we proposed a clustering approach for extracting a small number of basic electricity consumption patterns in a household. In this study, we apply the method to a larger dataset with many households. In the previous work, we determined the number of basic patterns in a heuristic manner. In this work, we use gap statistics to automatically determine an appropriate number of basic patterns, and we obtained a reasonable result on a large-scale data.","PeriodicalId":239142,"journal":{"name":"2012 International Conference on Renewable Energy Research and Applications (ICRERA)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 International Conference on Renewable Energy Research and Applications (ICRERA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICRERA.2012.6477336","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Electricity consumption in households varies dependent on a lot of possible reasons such as lifestyle, family configuration, and weather. It is of great importance to optimize the electricity generation system to install for each household. In our previous work, we proposed a clustering approach for extracting a small number of basic electricity consumption patterns in a household. In this study, we apply the method to a larger dataset with many households. In the previous work, we determined the number of basic patterns in a heuristic manner. In this work, we use gap statistics to automatically determine an appropriate number of basic patterns, and we obtained a reasonable result on a large-scale data.