Optimal Energy Scheduling of Residential Building with Battery Cost

This paper proposes a day-ahead energy management program for a residential house while taking into account the degradation costs of a battery to reflect the true operational costs. In the method, charging-discharging cycling costs are integrated into the energy exchange program for evaluating their effect on the operating costs. The optimisation problem formulated is solved using a framework, in which particle swarm optimisation (PSO) algorithm and Rainflow counting algorithm are used. Simulation results demonstrate that including cycling costs to the objective function estimates the appropriate operating costs of the scheduled energy. It is also found that the proposed algorithm can decrease electricity costs by around 11.29% as compared to the baseline approach. Simulation results also prove the effectiveness of the proposed method in managing battery energy effectively.