Abstract
Home energy management systems have been widely used for energy management in smart homes. Management of energy in smart home is a difficult task and requires efficient scheduling for smart appliances in a home. A meta-heuristic optimization technique is proposed in this paper. The proposed Harmony Search Gray Wolf Optimization (HSGWO) is a hybrid of Harmony Search Algorithm (HSA) and Gray Wolf Optimization (GWO). The pricing signal used for the calculation of electricity cost is Real Time Pricing (RTP). The basic aim of this paper is to reduce electricity cost, Peak to Average Ratio (PAR) and maximization of user comfort. Simulation results show that HSGWO performs better as compared to HSA and GWO. The findings demonstrate that there is a trade off between electricity cost and user comfort.
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