Home Energy Managment System Using Meta-heuristic Techniques

In this paper, we have evaluated the performance of Home Energy Management (HEM) using two meta-heuristic techniques: Chicken Swarm Optimization (CSO) and Bacterial Foraging Algorithm (BFA). We have classified the appliances in two catagories: fixed and shiftable/elastic appliances. Time of Use (ToU) pricing scheme is used for the calculation of electricity bill. The main objective of this paper is the minimization of electricity cost, reduction of Peak to Average (PAR) and balancing of load between peak and off peak hours while taking User Comfort (UC) under consideration. These algrithms performs efficiently in achieving multiple objectives. However results and simulations shows that CSO performs better than BFA in terms of PAR reduction, while BFA performs better in reducing electrcity cost.