{"title":"Demand Response Strategy Considering User Satisfaction Based on NILM Technology","authors":"Tian Kaiyuan, Zhang Shifeng, Wei Gang, Fang Yan","doi":"10.1109/ICPST56889.2023.10165172","DOIUrl":null,"url":null,"abstract":"Aiming at the problems of the diversity of power grid residents' loads and the satisfaction of the user side in the process of demand response (DR), combining the DR model and the idea of data mining, proposes a DR model based on Non-Intrusive Load Monitoring (NILM) technology, which considers user satisfaction with electricity. The simulation results show that compared with the traditional DR model, this model can minimize the impact of DR on residential users' power consumption comfort, reduce the cost of power consumption for users while enhancing their satisfaction with power consumption, and make the load power curve more stable, which is conducive to the safe and stable operation of the power grid. Through the in-depth mining of historical power consumption data of users using NILM technology, the basis for the improvement of DR is provided, which is conducive to continuously improving the implementation effect of DR and giving full play to the important role of DR in the safe and stable operation of the power grid.","PeriodicalId":231392,"journal":{"name":"2023 IEEE International Conference on Power Science and Technology (ICPST)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 IEEE International Conference on Power Science and Technology (ICPST)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPST56889.2023.10165172","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
Aiming at the problems of the diversity of power grid residents' loads and the satisfaction of the user side in the process of demand response (DR), combining the DR model and the idea of data mining, proposes a DR model based on Non-Intrusive Load Monitoring (NILM) technology, which considers user satisfaction with electricity. The simulation results show that compared with the traditional DR model, this model can minimize the impact of DR on residential users' power consumption comfort, reduce the cost of power consumption for users while enhancing their satisfaction with power consumption, and make the load power curve more stable, which is conducive to the safe and stable operation of the power grid. Through the in-depth mining of historical power consumption data of users using NILM technology, the basis for the improvement of DR is provided, which is conducive to continuously improving the implementation effect of DR and giving full play to the important role of DR in the safe and stable operation of the power grid.