A Novel Meta-Heuristic Hybrid Enhanced Differential Harmony Wind Driven (EDHWDO) Optimization Technique for Demand Side Management in Smart Grid

Abstract

In recent decades numerous Demand Side Management (DSM) techniques have been merged for Smart Grid (SG). These techniques have been very effective in minimizing cost. However, lack in other characteristics like effective control over Peak Average Ratio (PAR) that why they are not equally beneficial for the utility. Due to different characteristic of different operations some techniques are really work well for cost and some for PAR. We have evaluated and extracted different operations from Harmony Search Algorithm (HSA), Enhanced Differential Evolution (EDE) and Wind Driven Optimization (WDO) for controlling cost along with PAR. A hybrid Enhanced Differential Harmony Wind Driven Optimization (EDHWADO) is formed that combines the cost effectiveness of WDO, HSA and PAR controlling operation through integration of EDE. The proposed hybrid engine proved to be most cost effective in comparison to Genetic Algorithm (GA), WDO along effective PAR control and User Comfort (UC) maximization. Real Time Pricing (RTP) signals are used to evaluate real time behavior of appliances. Three categories of appliances are used; fixed, elastic and shiftable. On basis of performances metrics, simulations proved that EDHWDO leads substantial cost saving along with enhancing user comfort and also helps in significant cost reduction.