A novel grid-connected microgrid energy management system with optimal sizing using hybrid grey wolf and cuckoo search optimization algorithm

Renewable energy systems, particularly in countries with limited fossil fuel resources, are promising and environmentally sustainable sources of electricity generation. Wind, solar Photovoltaic (PV), biomass gasifier-based systems have gotten much attention recently for providing to energy-deficient areas. However, due the intermittent nature renewable energy, a completely system is unreliable may cause operation problems. Energy storage volatile generation best way combat problem. This paper proposes hybrid grid-connected wind-solar PV Microgrid (MG) devices meet entire value load demand adopted buildings an intended region ensure economic dispatch as well make trade field by supplying/receiving to/from utility grid. The control plan uses battery units compensate gap if priority resources (wind turbine PV) incapable meeting demand. Additionally, gasifier used fallback option batteries fail perform their duty. At any time, excess can be utilized charge sell rest utility. insufficient demand, required acquired from A Hybrid Grey Wolf Cuckoo Search Optimization (GWCSO) algorithm achieving optimal sizing proposed MG. To assess technique’s robustness, results compared those obtained using (GWO) algorithm. GWCSO method yielded lower total number component units, annual cost, Net Present Cost (NPC), Levelized Of (LCOE) than GWO algorithm, whereas has lowest deviation, indicating that it more accurate robust