Efficient Power Scheduling in Smart Homes Using Meta Heuristic Hybrid Grey Wolf Differential Evolution Optimization Technique

Abstract

With the emergence of automated environment, energy demand by consumer is increasing day by day. More than 80% of total electricity is being consumed in residential sector. In this paper, a heuristic optimization technique is proposed for the efficient utilization of energy sources to balance load between demand and supply sides. An optimization technique is proposed which is a hybrid of Enhanced differential evolution (EDE) algorithm and Gray wolf optimization (GWO). The proposed scheme is named as hybrid gray wolf differential evolution (HGWDE). It is applied for home energy management (HEM) with the objective function of cost minimization and reducing peak to average ratio (PAR). Load shifting is performed from on peak hours to off peak hours on basis of user preference and real time pricing (RTP) tariff defined by utility. However, there is a trade off between user comfort and above mentioned parameters. To validate the performance of proposed algorithm, simulations have been carried out in MATLAB. Results illustrate that PAR and electricity bill have been reduced to 53.02%, and 12.81% respectively.