{"title":"Distributed convex optimization of energy flows: The two-microgrid case","authors":"D. Gregoratti, J. Matamoros","doi":"10.1109/BlackSeaCom.2013.6623410","DOIUrl":null,"url":null,"abstract":"In this paper, a distributed convex optimization framework is developed to manage energy flows between is-landed microgrids. More specifically, the problem consists of two islanded microgrids with the additional capability of selling energy to one another. In order to avoid a central controller and to reduce communications requirements, a subgradient-based cost minimization algorithm is proposed that converges to the centralized solution in a practical number of iterations. Furthermore, this approach allows for a very intuitive, economics interpretation that explains the algorithm iterations in terms of “supply-demand model” and “market clearing”. Finally, numerical results show that microgrid cooperation brings a benefit, both globally (system level) and locally (microgrid level).","PeriodicalId":170309,"journal":{"name":"2013 First International Black Sea Conference on Communications and Networking (BlackSeaCom)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 First International Black Sea Conference on Communications and Networking (BlackSeaCom)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BlackSeaCom.2013.6623410","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
Abstract
In this paper, a distributed convex optimization framework is developed to manage energy flows between is-landed microgrids. More specifically, the problem consists of two islanded microgrids with the additional capability of selling energy to one another. In order to avoid a central controller and to reduce communications requirements, a subgradient-based cost minimization algorithm is proposed that converges to the centralized solution in a practical number of iterations. Furthermore, this approach allows for a very intuitive, economics interpretation that explains the algorithm iterations in terms of “supply-demand model” and “market clearing”. Finally, numerical results show that microgrid cooperation brings a benefit, both globally (system level) and locally (microgrid level).