Alsharif, A.Almabsout, E.Ahmed, A.A.Khaleel, M.Nassar, Y.F.El-Khozoadar, H.J.2024-09-292024-09-292024979-835037263-2https://doi.org/10.1109/MI-STA61267.2024.10599729https://hdl.handle.net/20.500.14619/93084th IEEE International Maghreb Meeting of the Conference on Sciences and Techniques of Automatic Control and Computer Engineering, MI-STA 2024 -- 19 May 2024 through 21 May 2024 -- Tripoli -- 201424Hybrid Renewable Power Systems (HRPSs) have been extensively employed at regional, national, and different levels due to their capability of decreasing Carbon Dioxide (CO2) emissions and reducing energy consumption amount. However, the main challenge of Renewable Energy Sources (RESs) is the uncertainties of the demand and source integration that may be addressed by nature-inspired metaheuristic algorithms. The optimal operation of a Microgrid (MG) includes Photovoltaic (PV), Wind Turbine (WT), and Battery (BT), as integrated sources for the distributed generation system. This paper proposes the utilization of the Whale Optimization Algorithm (WOA) in order to overcome sizing limitations. The aforesaid optimization algorithm benchmarked with the Antlion Optimization (ALO) algorithm that coupled with a supervisory control algorithm called energy management strategy to meet the objective functions. The main objectives of this study are to obtain a hybrid system with lower cost and lower reliability. The results of the system show better performance on WOA as the main findings in terms of cost (0.01/kWh) and LPSP (0.08%). The aforementioned result contributes a cost-effective system with lower loss, and providing sustainable living which means electricity is available most of the time. © 2024 IEEE.eninfo:eu-repo/semantics/closedAccessHRPSsMGsPVRESsWOAConference Object10.1109/MI-STA61267.2024.105997292-s2.0-85201157399295N/A290