A Smart Home Based on Renewable Energy with Net-Metering and Energy Storage Technology

Due to the rapid advancements in renewable energy and battery technologies, an increasing number of households are adopting renewable energy sources (RES) and energy storage systems (ESS) to decrease their home energy expenses. These homes commonly utilize home energy management systems (HEMS) for the management and scheduling all their electrical devices. Several research studies have focused on HEMS and optimization algorithms with the aim of reducing energy costs and peak-to-average ratio (PAR). However, these studies have not adequately addressed the utilization of electricity from the main grid and the process of selling excess electricity back to the grid. In this research, we introduce a novel HEMS architecture that considers the integration of RES, ESS, and their interactions with the main grid, including electricity selling. The proposed HEMS utilizes innovative mathematical formulas to assess energy costs and PAR patterns throughout the day. To optimize these formulas, we employ two different optimization techniques: particle swarm optimization (PSO) and binary particle swarm optimization (BPSO). The outcomes of research show significant reductions in home energy costs of up to 19.7% compared to previous approaches. By increasing the charge/discharge rate of ESS, we can further reduce energy costs by 4.3% for 0.6 kW and S.5% for 0.9 kW. Moreover, system leverages multi-objective optimization to achieve improved PAR while still maintaining acceptable energy costs.