Energy Optimization in Home Energy Management System Using Artificial Fish Swarm Algorithm and Genetic Algorithm

In this paper, we have evaluated the performance of heuristic algorithms: Genetic Algorithm (GA) and Artificial Fish Swarm Algorithm (AFSA) for Demand Side Management. Our prime focus in this paper, is to optimally schedule appliances in a smart home in such a way that the Peak to Average Ratio (PAR) and the electricity cost can be reduced. The pricing scheme used in this paper is real time pricing. Our Simulation results validate that the two nature inspired schemes successfully reduce PAR and electricity cost by transferring load of on peak hours to off peak hours. Our results also depict a trade off between electricity cost and comfort of a user.