A. Collin, R. Langella, A. Testa, S. Djokic, X. Xiao
{"title":"用于潮流和电能质量分析的商业负荷部门模型","authors":"A. Collin, R. Langella, A. Testa, S. Djokic, X. Xiao","doi":"10.1109/SPEEDAM.2018.8445213","DOIUrl":null,"url":null,"abstract":"In this paper, a component-based modelling methodology is applied to the commercial load sector. This approach allows for greater insight into the temporal variations in the electrical characteristics of the commercial load sector than currently available modelling practices. This is illustrated by analyzing the half hourly changes in the voltage dependency of the demand and harmonic distortion of a generic UK commercial load sector representation; however, the methodology can be applied wherever similar datasets exist. The results highlight differences between on-peak and off-periods, and provide a useful starting place for probabilistic model development.","PeriodicalId":117883,"journal":{"name":"2018 International Symposium on Power Electronics, Electrical Drives, Automation and Motion (SPEEDAM)","volume":"2002 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Commercial Load Sector Models for Power Flow and Power Quality Analysis\",\"authors\":\"A. Collin, R. Langella, A. Testa, S. Djokic, X. Xiao\",\"doi\":\"10.1109/SPEEDAM.2018.8445213\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, a component-based modelling methodology is applied to the commercial load sector. This approach allows for greater insight into the temporal variations in the electrical characteristics of the commercial load sector than currently available modelling practices. This is illustrated by analyzing the half hourly changes in the voltage dependency of the demand and harmonic distortion of a generic UK commercial load sector representation; however, the methodology can be applied wherever similar datasets exist. The results highlight differences between on-peak and off-periods, and provide a useful starting place for probabilistic model development.\",\"PeriodicalId\":117883,\"journal\":{\"name\":\"2018 International Symposium on Power Electronics, Electrical Drives, Automation and Motion (SPEEDAM)\",\"volume\":\"2002 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 International Symposium on Power Electronics, Electrical Drives, Automation and Motion (SPEEDAM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SPEEDAM.2018.8445213\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 International Symposium on Power Electronics, Electrical Drives, Automation and Motion (SPEEDAM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SPEEDAM.2018.8445213","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Commercial Load Sector Models for Power Flow and Power Quality Analysis
In this paper, a component-based modelling methodology is applied to the commercial load sector. This approach allows for greater insight into the temporal variations in the electrical characteristics of the commercial load sector than currently available modelling practices. This is illustrated by analyzing the half hourly changes in the voltage dependency of the demand and harmonic distortion of a generic UK commercial load sector representation; however, the methodology can be applied wherever similar datasets exist. The results highlight differences between on-peak and off-periods, and provide a useful starting place for probabilistic model development.