Yu Long, Wenjun Ruan, Kang Xie, Yuhang Sun, Siwei Li, Long Yu, Liang Yue, Chang Liu, Meimei Duan
{"title":"Exploring load disaggregation method for industrial loads considering economy-climate-production factors based on clustering technologies","authors":"Yu Long, Wenjun Ruan, Kang Xie, Yuhang Sun, Siwei Li, Long Yu, Liang Yue, Chang Liu, Meimei Duan","doi":"10.1117/12.2682336","DOIUrl":null,"url":null,"abstract":"Power demand response is a significant method to provide regulation resources for the power system by adjusting the operating power of equipment. To obtain the regulation potential of each equipment, the load disaggregation is necessary from a large number of the smart meter data. However, the existing disaggregation methods mainly focus on residential and commercial users with the similar and fixed equipment. The industrial user loads are various, which is affected by many factors, such as the climate. To solve the above problems, this paper proposes a load disaggregation method for industrial loads considering economy-climate-production factors based on clustering technologies. First, the main affecting factors of the industrial production are analyzed from three dimensions, including the production load, the non-production load and the security load. On this basis, data marking and clustering methods are proposed to classify the industrial load data. Subsequently, an industrial load disaggregation method is presented for obtaining each type of the load power based on the single variable method. Finally, the effectiveness of the proposed models and methods is illustrated by numerical studies.","PeriodicalId":177416,"journal":{"name":"Conference on Electronic Information Engineering and Data Processing","volume":"12 20","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Conference on Electronic Information Engineering and Data Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1117/12.2682336","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
Power demand response is a significant method to provide regulation resources for the power system by adjusting the operating power of equipment. To obtain the regulation potential of each equipment, the load disaggregation is necessary from a large number of the smart meter data. However, the existing disaggregation methods mainly focus on residential and commercial users with the similar and fixed equipment. The industrial user loads are various, which is affected by many factors, such as the climate. To solve the above problems, this paper proposes a load disaggregation method for industrial loads considering economy-climate-production factors based on clustering technologies. First, the main affecting factors of the industrial production are analyzed from three dimensions, including the production load, the non-production load and the security load. On this basis, data marking and clustering methods are proposed to classify the industrial load data. Subsequently, an industrial load disaggregation method is presented for obtaining each type of the load power based on the single variable method. Finally, the effectiveness of the proposed models and methods is illustrated by numerical studies.