An Adaptive Battery Scheduling Framework for Residential Photovoltaic Energy Storage Systems

The increasing penetration of residential rooftop photovoltaic (PV) systems has intensified the need for efficient Battery Energy Storage Systems (BESS) capable of mitigating the intermittent nature of solar power generation and improving residential energy self-sufficiency. Effective battery scheduling plays a critical role in maximizing photovoltaic energy utilization, reducing dependence on the utility grid, and ensuring reliable battery operation under dynamic residential load conditions. This paper proposes an Adaptive Battery Scheduling Framework (ABSF) for residential photovoltaic energy storage systems that employs a computationally efficient adaptive rule-based decision strategy for intelligent battery charging, discharging, and grid power management. The proposed framework continuously evaluates photovoltaic generation, battery state of charge, household electricity demand, and utility grid conditions to determine the most appropriate battery operating mode while maintaining battery operation within predefined safety limits.The framework is implemented in MATLAB and Simulink using a modular software architecture comprising photovoltaic generation modeling, battery modeling, weather analysis, residential load profiling, adaptive scheduling, and performance evaluation modules. Simulation studies are conducted under realistic twenty-four-hour residential operating conditions using time-varying solar irradiance and household load profiles. The obtained results demonstrate effective battery scheduling through intelligent charging during periods of surplus photovoltaic generation and controlled discharging during peak demand, resulting in improved photovoltaic energy utilization, reduced grid energy import, enhanced battery utilization, and reliable residential energy supply. Owing to its low computational complexity, modular architecture, and adaptability to changing operating conditions, the proposed framework provides a practical and scalable solution for next-generation residential photovoltaic battery energy storage systems.