{"title":"Optimization model for two-level microgrid operation with demand response","authors":"Kailang Gao","doi":"10.1117/12.2682376","DOIUrl":null,"url":null,"abstract":"The article establishes a two-layer optimization model, in which the user-side load and the microgrid operation are combined. The upper layer of optimization establishes a demand response model based on the adjustable characteristics of the load and the time characteristics of the time-sharing tariff. To give full play to the characteristics of the demand response that can cut the peaks and fill the valleys, to reduce the energy cost on the user side and improve the energy utilization, and the lower-level optimization is based on the best demand response results obtained from the upper layer of optimization. Based on the supply-demand balance, Regulating the output power of distributed energy sources at various times of the day, in order to reduce the cost of microgrid system operation. Finally, the proposed method is validated by solving the two-layer optimization model with an improved particle swarm algorithm.","PeriodicalId":177416,"journal":{"name":"Conference on Electronic Information Engineering and Data Processing","volume":"597 1","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/10.1117/12.2682376","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
The article establishes a two-layer optimization model, in which the user-side load and the microgrid operation are combined. The upper layer of optimization establishes a demand response model based on the adjustable characteristics of the load and the time characteristics of the time-sharing tariff. To give full play to the characteristics of the demand response that can cut the peaks and fill the valleys, to reduce the energy cost on the user side and improve the energy utilization, and the lower-level optimization is based on the best demand response results obtained from the upper layer of optimization. Based on the supply-demand balance, Regulating the output power of distributed energy sources at various times of the day, in order to reduce the cost of microgrid system operation. Finally, the proposed method is validated by solving the two-layer optimization model with an improved particle swarm algorithm.