Comparison of BFA and EWA in home energy management system using RTP

Abstract

With the usage of demand side management (DSM) techniques, consumers such as residential, commercial and industrial are more flexible to use electricity according to their need. Many techniques are proposed to manage electricity cost, load, peak to average ratio (PAR) and user comfort of consumer appliances. In this paper we proposed a technique Earthworm Optimization Algorithm (EWA) that is developed for residential area in SG and compare with the Bacterial Foraging Algorithm (BFA). These algorithms are used for the scheduling the appliance load in real time pricing. Both algorithms are used to shifting the load from on-peak hours to off-peak hours in RTP and reduced the electric cost and PAR. We compare both algorithms in terms of electricity cost, PAR and used comfort. Our simulation results show that the EWA outperformed the BFA in terms of electricity cost however, BFA reduced the PAR as compared to EWA.