Whale Optimization Algorithm for Community Microgrid Energy Scheduling

Abstract

A microgrid is a local electricity network that supplies electrical energy to the local community from various distributed generation (DG) systems. It can be operated independently or in coordination with the national utility grid of a country. Microgrid operators face different operational challenges and uncertainties while meeting the electricity demand of their customers. This research aims to develop a community microgrid (CMG) energy scheduling strategy considering the electricity price, renewable generation, and load demand uncertainty. The considered CMG system is connected to a utility grid and comprises of a solar photovoltaic (PV) plant, a wind generation system, a micro-turbine, an energy storage system (ESS), and a lumped load. A versatile mathematical optimization problem is formulated and solved using an efficient meta-heuristic technique called the whale optimization algorithm (WOA). The proposed strategy combines an intelligent control system with management software to track the CMG customers’ energy requirements and meet the demand with minimal cost by optimizing the available resources. The findings from the research verify the utilization of the ESS in the microgrid to reduce the overall operating costs.