{"title":"Cost-Effective Energy Management of Grid-Connected PV and BESS: A Case Study","authors":"Sachinkumar Suthar, Nitish Kumar, N. Pindoriya","doi":"10.1109/ISGT-Asia.2019.8881426","DOIUrl":null,"url":null,"abstract":"In this paper, a linear programming based energy management algorithm is formulated for grid-connected solar PV and BESS. The aim is to minimize the cost of energy purchased from the utility grid and to maximize the utilization of solar photovoltaic generation while optimally scheduling the battery energy storage system subjected to the constraints – state of charge limits, charging and discharging rates of BESS. This algorithm utilizes different scenarios generated from the forecasted quantities to incorporate the uncertainty associated with them. Practical data collected from the testbed at Gujarat International Finance Tec city is used as the input parameters of the presented algorithm. The simulation results are compared with the base case scenario which does not use optimization. In comparison, it was confirmed that the presented algorithm minimizes the cost of energy purchased from the grid by optimally dispatching the BESS.","PeriodicalId":257974,"journal":{"name":"2019 IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISGT-Asia.2019.8881426","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
In this paper, a linear programming based energy management algorithm is formulated for grid-connected solar PV and BESS. The aim is to minimize the cost of energy purchased from the utility grid and to maximize the utilization of solar photovoltaic generation while optimally scheduling the battery energy storage system subjected to the constraints – state of charge limits, charging and discharging rates of BESS. This algorithm utilizes different scenarios generated from the forecasted quantities to incorporate the uncertainty associated with them. Practical data collected from the testbed at Gujarat International Finance Tec city is used as the input parameters of the presented algorithm. The simulation results are compared with the base case scenario which does not use optimization. In comparison, it was confirmed that the presented algorithm minimizes the cost of energy purchased from the grid by optimally dispatching the BESS.