Mojaharul Islam, Fuwen Yang, Jahangir Hossain, Chandima Ekanayeke, U. B. Tayab
{"title":"Battery Energy Management to Minimize the Grid Fluctuation in Residential Microgrids","authors":"Mojaharul Islam, Fuwen Yang, Jahangir Hossain, Chandima Ekanayeke, U. B. Tayab","doi":"10.1109/AUPEC.2018.8758005","DOIUrl":null,"url":null,"abstract":"The stochastic nature of renewable resources and loads leads to a large fluctuation of grid power in a grid-tied microgrid (MG) operation. Integrate battery energy storage system in MG is popular way to handle the stochastic nature of renewable resources to feed the stochastic load. In this paper, a battery management strategy is proposed using golden section search algorithm to minimize the grid power fluctuation by securing the battery constraints. The algorithm is applied in energy management system (EMS) of MG to minimize the grid peak power and grid power variation within a 24 hours duration by considering the random nature of renewable generations. The proposed battery management strategy is verified through the simulation experiment in a residential AC MG.","PeriodicalId":314530,"journal":{"name":"2018 Australasian Universities Power Engineering Conference (AUPEC)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 Australasian Universities Power Engineering Conference (AUPEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AUPEC.2018.8758005","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
The stochastic nature of renewable resources and loads leads to a large fluctuation of grid power in a grid-tied microgrid (MG) operation. Integrate battery energy storage system in MG is popular way to handle the stochastic nature of renewable resources to feed the stochastic load. In this paper, a battery management strategy is proposed using golden section search algorithm to minimize the grid power fluctuation by securing the battery constraints. The algorithm is applied in energy management system (EMS) of MG to minimize the grid peak power and grid power variation within a 24 hours duration by considering the random nature of renewable generations. The proposed battery management strategy is verified through the simulation experiment in a residential AC MG.