Wenjie Wang, Dongning Jia, Bo Cheng, Bo Yin, Xianqing Huang, Jiali Xu, Yan Fu, Xiaolong Zhu
{"title":"Research on Non-intrusive Load Energy Consumption Optimization Technology Based on Industrial Electricity","authors":"Wenjie Wang, Dongning Jia, Bo Cheng, Bo Yin, Xianqing Huang, Jiali Xu, Yan Fu, Xiaolong Zhu","doi":"10.1109/WCEEA56458.2022.00017","DOIUrl":null,"url":null,"abstract":"Industrial electricity accounts for 70% of the total electricity consumption in China. Compared with foreign advanced industrial countries, there are some problems such as serious waste of electric energy, low utilization rate of electric energy and lack of energy monitoring. In view of the above problems, this paper studies the energy consumption analysis and optimization technology of industrial power, and develops a non-intrusive energy consumption monitoring equipment suitable for industrial power, aiming at improving the current situation of high energy consumption and low energy efficiency in China's industry. These equipments are deployed and applied in Weichai intelligent production line, and the characteristic parameters of voltage and current of electric load in production line are extracted. Through data mining algorithms such as correlation analysis and cluster analysis, the characteristic map of industrial load is extracted, and an integrated energy consumption management and control system is established, which provides decision-making basis for industrial energy consumption optimization, and provides a starting point for enterprises to conduct energy management and control and energy conservation and emission reduction.","PeriodicalId":143024,"journal":{"name":"2022 International Conference on Wireless Communications, Electrical Engineering and Automation (WCEEA)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Conference on Wireless Communications, Electrical Engineering and Automation (WCEEA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WCEEA56458.2022.00017","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
Industrial electricity accounts for 70% of the total electricity consumption in China. Compared with foreign advanced industrial countries, there are some problems such as serious waste of electric energy, low utilization rate of electric energy and lack of energy monitoring. In view of the above problems, this paper studies the energy consumption analysis and optimization technology of industrial power, and develops a non-intrusive energy consumption monitoring equipment suitable for industrial power, aiming at improving the current situation of high energy consumption and low energy efficiency in China's industry. These equipments are deployed and applied in Weichai intelligent production line, and the characteristic parameters of voltage and current of electric load in production line are extracted. Through data mining algorithms such as correlation analysis and cluster analysis, the characteristic map of industrial load is extracted, and an integrated energy consumption management and control system is established, which provides decision-making basis for industrial energy consumption optimization, and provides a starting point for enterprises to conduct energy management and control and energy conservation and emission reduction.