Optimization and comparative analysis of hybrid renewable energy systems for sustainable and clean energy production in rural Cameroon considering the loss of power supply probability concept

• The cost-effectiveness of a PV/Wind/TES and PV/Wind/PHES was analyzed. • Various metaheuristic algorithms applied to various hybrid systems are compared. • Techno-economic analysis is conducted for hybrid systems for a commercial building. • Sensitivity analysis has been performed to examine the performance of the hybrid systems. • Optimally designed hybrid system enables a substantial reduction in CO 2 emissions. This study investigates a hybrid photovoltaic (PV) / wind turbine system integrated with thermal energy storage (TES) and pumped-hydro energy storage (PHES) as a sustainable and reliable power solution for remote areas. The optimization of PV/Wind/TES and PV/Wind/PHES systems is performed for a commercial building in Kousseri, Cameroon, focusing on minimizing the system’s net present cost (NPC) while meeting the load demand. Three meta -heuristic algorithms namely, the water evaporation optimization, Cuckoo Search Algorithm (CSA), and teaching–learning-based optimization are applied, and the results are compared in terms of NPC, excess energy fraction, electricity demand fulfillment, and CO 2 emission reduction. System reliability is assessed using the maximum allowable loss of power supply probability, with values set at 0%, 2%, 5%, and 10%. The results indicate that the CSA algorithm outperforms the others, with the PV/Wind/TES configuration being the most cost-effective, followed by PV/TES, Wind/TES, PV/Wind/PHES, PV/PHES, and Wind/PHES systems. Additionally, the Wind/PHES system is identified as the most reliable and efficient in reducing CO 2 emissions, making it a superior alternative to conventional fossil fuel-based power plants.