Multi-Objective Optimization Algorithms for a Hybrid AC/DC Microgrid Using RES: A Comprehensive Review

Optimization methods for a hybrid microgrid system that integrated renewable energy sources (RES) and supplies reliable power to remote areas, were considered in order overcome the intermittent nature of RESs. The AC/DC was constructed with solar photovoltaic system, wind turbine, battery storage, converter, diesel generator. There is steady increase utilization microgrids; consequently, it necessary solve optimization techniques. Therefore, present study proposed utilizing multi-objective using evolutionary algorithms. In this context, few papers reviewed regarding determine capacity optimal design Here, consisted minimum cost energy, net cost, low operating carbon emissions high fraction. These determined by (MOO) sizing based on grey wolf optimizer (MOGWO) particle swarm (MOPSO). Similarly, different algorithms (MOGA, MOGOA etc.) reduces increases reliability islanded systems.