Ma Jie, Sun Shiming, Cen Hongxing, Qian Hanjia, Wang Xiaofei, Zhou Mengqi
{"title":"Analysis and Application of Customer Load with Special Line and Private Transformer Based on Artificial Intelligence","authors":"Ma Jie, Sun Shiming, Cen Hongxing, Qian Hanjia, Wang Xiaofei, Zhou Mengqi","doi":"10.1109/ICDSBA51020.2020.00019","DOIUrl":null,"url":null,"abstract":"In this study the customer load power curve characteristics with special line and private transformer, which can be obtained by big data technology processing, are analyzed for getting the time-varying characteristics of load power in typical power consumption industry and composition proportion of power consumption industry. Furthermore, an approach for systems automatic identification using artificial inteligence was proposed, so that the situation regarding the production of a factory is possible to grasp in real time. In the special period of the epidemic situation, it has provided a strong technical support for the power companies in Jiangsu Province and other cities to master the production situation of large-scale enterprises. In the long term, research into load model identification and cluster analysis technology based on bus in this paper, will constitute the basis of future work in bus load forecasting. Also it will be a good infrastructure for making value added services related to electricity industry.","PeriodicalId":354742,"journal":{"name":"2020 4th Annual International Conference on Data Science and Business Analytics (ICDSBA)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 4th Annual International Conference on Data Science and Business Analytics (ICDSBA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDSBA51020.2020.00019","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
In this study the customer load power curve characteristics with special line and private transformer, which can be obtained by big data technology processing, are analyzed for getting the time-varying characteristics of load power in typical power consumption industry and composition proportion of power consumption industry. Furthermore, an approach for systems automatic identification using artificial inteligence was proposed, so that the situation regarding the production of a factory is possible to grasp in real time. In the special period of the epidemic situation, it has provided a strong technical support for the power companies in Jiangsu Province and other cities to master the production situation of large-scale enterprises. In the long term, research into load model identification and cluster analysis technology based on bus in this paper, will constitute the basis of future work in bus load forecasting. Also it will be a good infrastructure for making value added services related to electricity industry.