Optimizing PV power utilization in standalone battery systems with forecast-based charging management strategy

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.

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Publication Details

Journal
Global Energy Interconnection
Published
2025-05-19
DOI
https://doi.org/10.1016/j.gloei.2025.01.006
Citations
2
Primary Topic
Advanced Battery Technologies Research
Type
article
Field-Weighted Citation Impact
1.37
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article

Optimizing PV power utilization in standalone battery systems with forecast-based charging management strategy

Ashish Kumar Karmaker, Utpal Kumar Das
2 citations
Global Energy Interconnection
Advanced Battery Technologies Research
1.37
article

Optimizing PV power utilization in standalone battery systems with forecast-based charging management strategy

Ashish Kumar Karmaker, Utpal Kumar Das
article en
2 citations

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.

Global Energy InterconnectionVol. 8(3)
University of Canberra (AU), UNSW Sydney (AU), Dhaka University of Engineering & Technology (BD)
Affordable and clean energy
Openalex Percentile: Top 19%
Advanced Battery Technologies Research
1.37
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Optimizing PV power utilization in standalone battery systems with forecast-based charging management strategy — Ashish Kumar Karmaker, Utpal Kumar Das · Global Energy Interconnection (2025) | TGRS Research Map | TGRS