Bio-Inspired Optimization Techniques for Home Energy Management in Smart Grid

Abstract

Smart Grid (SG) plays a noteworthy role in minimizing the Electricity Cost (EC) through Demand Side Management (DSM). Smart homes are the part of SG, pays a lot in minimizing EC via scheduling the appliances. Home Energy Management (HEM) have been extensively used for energy management in smart homes. In this paper, for the effective utilization of energy in a smart home, we propose a solution that consists of bio-inspired techniques: Genetic Algorithm (GA), Flower Pollination Algorithm (FPA) and hybrid of these two, Genetic Flower Pollination Algorithm (GFPA). All of these techniques applied to the appliances that are essential in a home. Our proposed solution leads to find an optimal scheduling pattern that reduces EC, Peak to Average Ratio (PAR) and maximize User Comfort (UC). In our work, we have considered one home. We divide appliances into three categories, non-interruptible, interruptible and fixed appliances. Simulation results show that our proposed schemes performed better in terms of EC, UC and PAR. We have done this work for three different Operational Time Intervals (OTIs) 15, 30 and 60 minutes for each appliance.