Energy management strategy and renewable energy integration within multi-microgrid framework utilizing multi-objective modified personal best particle swarm optimization

Abstract

This study focuses on multi-layer energy management systems of multi-microgrid smart distribution networks. Evaluation of effectiveness in real power losses for energy management (EM) within units is investigated. The demand response (DR) technique is incorporated in the optimization procedure. The DR program is not only the characteristic feature of smart distribution networks but also used in managing used power in individual units. Effusion limits of dispatchable generators are incorporated. First, individual microgrids execute EM to schedule units. Subsequently, using obtained data, smart distribution network (SDN) operators devise priority list (PL) in units that rely on the mean price and capacities, which can inject power to the SDN. PL promotes the utilization of renewables by financiers. Subsequently, global EM is executed. Meta-heuristic optimization, that is, multi-objective modified personal best particle swarm optimization is employed to effectively model unpredictability in power produced from renewable energy resources. Studies are executed in an altered IEEE 33 bus system. The outcomes achieved show reductions in costs: cost reductions are 26.18% in MG1, 4.65% in MG2, 13 % in MG3, and 28.27% in SDN, while considering losses; cost reductions without losses are 26.15% in MG1, 2.76% in MG2, 4% in MG3, and 26.6% in SDN incorporating DR in both cases.