Efficient Demand Side Management Using Hybridization of Elephant Herding Optimization and Firefly Optimization

Abstract

This paper presents a new algorithm to solve the problem of electricity cost reduction by hybridization of two meta-heuristic techniques, i.e., Elephant Herding Optimization (EHO) and Firefly Optimization (FF). A home energy management controller (HEMC), based on scheduling of different household electrical tasks is proposed to maintain balance between load and demand profile. The objective of this study is to determine lowest cost while considering user comfort maximization factor and peak to average ratio (PAR). The proposed algorithm, i.e., Hybrid Elephant and Firefly (HEF) optimization is analyzed comparatively to its' separate implemented versions to evaluate the performance and behavior towards scheduling process. Moreover, three different pricing models are used to calculate the total power consumption rate. Simulation results show that our proposed hybrid optimization technique performs more efficiently to achieve lowest cost and maximum consumer satisfaction.