Abstract

In this paper, Grey Wolf optimizer (GWO) is adapted for Power Scheduling Problem (PSP) of Smart Home with Smart Battery. GWO is the recent metaheuristic swarm-based optimization method stemmed by grey pack behaviour in hunting process. It has been successfully tailored to a wide variety of real-world optimization problems. PSP is tackled by scheduling the home appliances over a certain time horizon to minimize both the electricity bill and the peak-to-average ratio (PAR) as well as to improve the users comfort level. A new formulation for smart battery (SB) and its impact to achieve the objectives are also utilized and considered as the main part of this paper. The simulation results prove the efficiency of SB in minimizing the electricity bill and PAR and improving the user comfort. Furthermore, GWO proves its efficiency in obtaining the best schedule results in comparison with genetic algorithm (GA) results. In conclusion, SB has a high impact in power scheduling of appliances for smart home.

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