{"title":"Modeling and optimization in USEF-compliant hierarchical energy markets","authors":"D. B. Nguyen, J. Scherpen, B. Haar, F. Bliek","doi":"10.1109/ISGTEurope.2016.7856219","DOIUrl":null,"url":null,"abstract":"This paper presents a new model and optimization method for balancing in the Universal Smart Energy Framework. We address the problem of minimizing the error between the forecasted and the actual load in the power system that arise from the uncertainties of renewable energy production. The algorithm acts on multiple levels within the hierarchical energy market structure of the framework, where the levels correspond to different stakeholders. While pursuing the global objective, the stakeholders also have their own economic interests. The optimal solution is obtained as a result of iterative interactions between the stakeholders, namely, the Balance Responsible Party (BRP), the aggregators, and the Distribution System Operator (DSO). To illustrate the algorithm, we provide an example simulation.","PeriodicalId":330869,"journal":{"name":"2016 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISGTEurope.2016.7856219","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
This paper presents a new model and optimization method for balancing in the Universal Smart Energy Framework. We address the problem of minimizing the error between the forecasted and the actual load in the power system that arise from the uncertainties of renewable energy production. The algorithm acts on multiple levels within the hierarchical energy market structure of the framework, where the levels correspond to different stakeholders. While pursuing the global objective, the stakeholders also have their own economic interests. The optimal solution is obtained as a result of iterative interactions between the stakeholders, namely, the Balance Responsible Party (BRP), the aggregators, and the Distribution System Operator (DSO). To illustrate the algorithm, we provide an example simulation.