MGWOSCACSA: A Novel Hybrid Algorithm for Energy Management of Microgrid Systems

Abstract

Optimal scheduling of distributed energy resources (DER) in a microgrid system is a crucial step to accord an economic check in the planning and operation of the system. Among the many DERs, involvement of renewable energy sources (RES) also plays an important role in diminishing the release of harmful pollutants to the atmosphere from fossil-fuelled generators. This paper involves a novel hybrid method of recently developed three strong optimization methods viz. grey wolf optimizer (GWO), sine cosine algorithm (SCA) and crow search algorithm (CSA) to minimize the overall cost of a grid-connected microgrid system. The results were then compared to that of GWO, MGWO and those mentioned in literature. Numerical and pictorial results assert that proposed MGWOSCACSA outperformed all the optimization techniques in yielding consistent and superior quality results.