A Residential Home Energy Management System using Hybrid Particle Swarm-Grey Wolf Optimization

With the evolution of technology since the last decade, smart appliances are now the trend in most developed countries and soon will be a part of a typical user all over the world. The phenomenon of the smart grid allows controlling the time of operation of the appliances through two-way communication with the utility by employing a demand response program with the help of an energy management centre. In this paper, a hybrid of particle swarm optimization and grey wolf optimization technique is proposed and implemented for scheduling home appliances to minimize the electricity consumption bill. Real-time pricing (RTP) and inclined block rate RTP demand response programs have also been implemented to limit the peak-to-average ratio (PAR). Several cases have been compared with different conditions and found that the proposed strategy gives improved results in terms of electricity cost as well as PAR value.