Optimal Energy Management in Smart House using Metaheuristic Optimization Techniques

This paper presents the optimal energy management in the smart house to reduce electricity costs at the TOU tariff using the optimal load shifting technique. In this study, three meta-heuristic optimization techniques: Gray Wolf Optimization (GWO), Whale Optimization Algorithm (WOA), and Binary Bat Algorithm (BBA), were used to find the optimal load shifting considering the electricity cost minimization. The simulation is based on the TOU tariff of Thailand's Provincial Electric Authority (PEA). The simulation results showed that the average reduction in electricity cost was 13.59%, and the average peak ratio was 15.25% compared to the initial load profile. However, the results obtained from each technique are slightly different. By the simulation results, the optimal energy management in smart houses helps reduce electricity costs at the TOU tariff.