Community microgrid (CMG) is a local grid that serves a specific energy-consuming community. One of the critical challenges of the CMG is energy scheduling by minimizing the operating and maintenance expenditures through optimal utilization of the available resources. Consideration of the degradation cost of energy storage systems (ESS) is essential in modeling the CMG energy-scheduling problem that is rarely incorporated in literature. This paper uses and formulates a multi-objective optimization model for CMG energy scheduling where the ESS degradation cost is incorporated with other critical constraints. A recent but powerful and distinct meta-heuristic optimization technique, the Equilibrium Optimizer (EO), is employed to solve the modeled problem. The EO, inspired by control volume mass balance models, predicts both dynamic and equilibrium states. The obtained results verified the powerfulness and effectiveness of the employed algorithm. Hence, it reinforces the performance of the algorithm over other techniques used in CMG energy scheduling.

Community microgrid,Distributed generators,Energy scheduling,Energy storage systems,Equilibrium optimizer,Renewable energy resources