Optimal Bidirectional Home Energy Management System Considering Photovoltaic and Battery Storage Energy

In this paper, a home energy management system (HEMS) architecture with an energy storage system and photovoltaic is proposed for the buying/selling of electricity from/to the main grid. This paper suggests a price-based demand response (DR)-integrated binary particle swarm optimization gravitational search algorithm (BPSOGSA) for the optimization of the HEMS. The suggested method minimizes the home energy cost and schedules the home appliances based on the real-time price-based DR signals received from the utility while meeting the limitations imposed by the users. According to the simulated results, the proposed methodology also reduces the peak-to-average ratio (PAR) and hence improves the load curve significantly. The proposed methodology is proven to find a better solution for the same number of functions examined when compared to the existing method like binary particle swarm optimization (BPSO). In the considered HEMS system, the hybrid optimization algorithm BPSOGSA reduces the home energy cost by 10.22% and PAR by 2.88% compared to the BPSO algorithm.