Smart grid technology has given users the ability to regulate their home energy in a much more effective manner. In such scenarios, Home Energy Management (HEM) potentially becomes an arduous task, as it necessitates the optimal scheduling of smart appliances in order to reduce energy usage. In this research, a hybrid Harris Hawk Optimization-Sine Cosine Algorithm (hHHO-SCA) has been proposed to develop a meta-heuristic-based HEM system. The hybridization of HHO with SCA has been done to enhance the exploration and exploitation stages of HHO, hence improving its global search phase and effectively optimizing the energy usages. In addition to this, several knapsacks are utilized to guarantee that load demand for power users does not surpass a certain level during the peak hours. In terms of electricity prices and Peak to Average Ratio (PAR) reduction, the hybridization is demonstrated to be beneficial in achieving the objectives. Simulations are performed for a multi-family housing complex with a range of smart equipment. The results achieved with the proposed approach suggest that hHHO-SCA has been comparatively efficient in terms of cost reduction, and PAR, when compared to the other optimization techniques. Practical Application. This home energy management system can be applied to optimally schedule all the smart appliances in a building to minimize electricity consumption and provide the consumer with potential savings in electricity costs.
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