Multi-Objective Optimization of Autonomous Microgrids with Reliability Consideration

Microgrids operating on renewable energy resources have potential for powering rural areas located far from existing grid infrastructures. These small power systems typically host a hybrid system of diverse architecture and size. An effective integration energies requires careful design. Sizing methodologies often lack the consideration reliability this aspect is limited to adequacy. There exists an inherent trade-off between integration, cost, reliability. To bridge gap, sizing methodology has been developed perform multi-objective optimization, considering three design objectives mentioned above. This method based non-dominated sorting genetic algorithm (NSGA-II) that returns set optimal solutions under all objectives. aims identify trade-offs reliability, cost allowing choose adequate accordingly. As case study, we consider autonomous microgrid, currently being installed in area Mali. The results show increasing can be done at least if carried out initial stage.