Degradation-Aware Stochastic BPSO Optimization of Smart Home Energy Management under TOU Tariff

Abstract

The increasing deployment of photovoltaic (PV) systems, residential energy storage systems (ESS), and electric vehicles (EVs) presents new opportunities for reducing household electricity costs under Time-of-Use (TOU) tariffs. However, effective coordination of ESS charging/discharging, Vehicle-to-Home (V2H) operation, and deferrable load scheduling remains challenging, especially when battery degradation is considered. This paper proposes a degradation-aware Home Energy Management System (HEMS) based on a stochastic Binary Particle Swarm Optimization (BPSO) framework for smart homes equipped with PV–ESS–EV systems. The model integrates a power balance formulation, ESS/EV operational constraints, V2H availability, load-shifting decisions, and a throughput-based degradation cost to optimize 24-hour household energy scheduling. Five operational scenarios (S1–S5) are evaluated to quantify the impacts of ESS integration, V2H, load shifting, and degradation-aware control. The results show that ESS and V2H significantly reduce peak-period grid import, while BPSO-based load shifting achieves the lowest daily operating cost. Incorporating degradation awareness reduces ESS throughput by 30.81%, providing a cost–health trade-off that extends battery longevity. The proposed framework demonstrates an effective and practical approach for improving economic performance and sustainable operation of residential PV–ESS–EV systems under TOU pricing.