Optimal scheduling of distributed energy resources in microgrid systems based on electricity market pricing strategies by a novel hybrid optimization technique

Abstract

The upsurge in microgrid demand is an important aspect of imparting energy in future primarily because of the involvement of renewable energy sources, which alleviates the emission of toxic gases from fossil fuelled generators. The grid-connected mode of microgrid operation is the most economical and definitive mode of service wherein the grid is actively involved in the buying and selling of power prompting diminished generation cost of microgrid system. These cases, pertaining to two different low voltage microgrid systems, are applied consecutively for obtaining the generation cost of the systems and thus devise the cheapest strategy among them. The Grey Wolf Optimizer (GWO) is improvised by incorporating strategies from population-based Sine Cosine Algorithm (SCA) along with position updating methods of crows from Crow Search Algorithm (CSA) to form a hybrid modified Grey Wolf Optimizer Sine Cosine Algorithm Crow Search Algorithm (GWOSCACSA) algorithm. The implementation of the proposed technique produces a comprehensive generator cost reduction of the microgrid system. It was evident from the results that generation cost was minimum when Time of Usage (TOU) based market pricing strategy was considered. Further, it was also established that dynamic grid participation was reduced 47% in the system generation cost for the same scenario compared to the case when the grid was operating passively. The statistical analysis endorses the improvements of GWOSCACSA over other algorithms presented in the state-of-art-literature.