Equilibrium Optimizer for Community Microgrid Energy Scheduling

The local electricity grid serving a small community is called the community microgrid (CMG). Among many challenges of the CMG, the most critical one is energy scheduling through optimal utilization of available resources to minimize overall operating and maintenance expenditures. In addition, the energy storage systems (ESS) degradation costs are neglected in many formulations reported in the literature that should be considered in the modeling. This article proposes a cost-minimization mathematical formulation for CM energy scheduling incorporating the ESS degradation cost and other critical constraints. The equilibrium optimizer (EO), an effective and distinct meta-heuristic optimization algorithm, is employed to evaluate the modeled optimization formulation. The algorithm, inspired by control volume mass balance models, predicts equilibrium and dynamic states. The obtained results verify the efficacy of the employed optimizer in achieving quality outcomes. Thus, it reinforces the performance of the employed strategy over others for CMG energy scheduling.