{"title":"Optimizing PV power utilization in standalone battery systems with forecast-based charging management strategy","authors":"Utpal Kumar Das , Ashish Kumar Karmaker","doi":"10.1016/j.gloei.2025.01.006","DOIUrl":null,"url":null,"abstract":"<div><div>Optimizing photovoltaic (PV) power utilization in battery systems is challenging due to solar intermittency, battery efficiency, and lifespan management. This paper proposes a novel forecast-based battery charging management (BCM) strategy to enhance PV power utilization. A string of Li-ion battery cells with diverse capacities and states of charge (SOC) is contemplated in this constant current/constant voltage (CC/CV) battery-charging scheme. Significant amounts of PV power are often wasted because the CC/CV mode cannot fully exploit the available power to maintain appropriate charging rates. To address this issue, the proposed BCM algorithm selects an optimal set of battery cells for charging at any given time based on forecasted PV power generation, ensuring maximum power is obtained from the PV system. Additionally, a support vector regression (SVR)-based forecasting model is developed to predict PV power generation precisely. The results indicate that the anticipated BCM strategy achieves an overall utilization rate of 87.47% of the PV-generated power for battery charging under various weather conditions.</div></div>","PeriodicalId":36174,"journal":{"name":"Global Energy Interconnection","volume":"8 3","pages":"Pages 407-419"},"PeriodicalIF":2.6000,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Global Energy Interconnection","FirstCategoryId":"1087","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2096511725000404","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
引用次数: 0
Abstract
Optimizing photovoltaic (PV) power utilization in battery systems is challenging due to solar intermittency, battery efficiency, and lifespan management. This paper proposes a novel forecast-based battery charging management (BCM) strategy to enhance PV power utilization. A string of Li-ion battery cells with diverse capacities and states of charge (SOC) is contemplated in this constant current/constant voltage (CC/CV) battery-charging scheme. Significant amounts of PV power are often wasted because the CC/CV mode cannot fully exploit the available power to maintain appropriate charging rates. To address this issue, the proposed BCM algorithm selects an optimal set of battery cells for charging at any given time based on forecasted PV power generation, ensuring maximum power is obtained from the PV system. Additionally, a support vector regression (SVR)-based forecasting model is developed to predict PV power generation precisely. The results indicate that the anticipated BCM strategy achieves an overall utilization rate of 87.47% of the PV-generated power for battery charging under various weather conditions.