Contribution into Robust Optimization of Renewable Energy Sources: Case Study of a Standalone Hybrid Renewable System in Cameroon

Abstract

Environment conservation is a matter subject affecting both developing and developed countries. Long-lasting energy can be achieved by attenuating Greenhouse gas emissions. All over the world, Hybrid Renewable Energy Sources (HRES) appear as a vital element when it comes to cover the rapid growth of the energy demand. Moreover, renewable energy (RE) is an unaffordable response to the fight against unpredicted events such as the diseases, industries development, reliability of energy sources, added to the various directives related to produce sustainable electricity. Henceforth, it is crucial to optimize the various sources for satisfying the electrical demand. In particular, this paper aims to value the hybridization of optimization techniques to achieve a robust optimization. Photovoltaic (PV), and Battery Storage Systems (BSS) constitute the various RE sources in this work. The main goal was to simultaneously minimize the Deficit of power supply probability (DPSP) and maximize the BSS capacities. Particle Swarm Optimization (PSO), Grey Wolf Optimizer (GWO), and hybridization of both techniques are employed to proceed with the optimization. This study reveals the performance of hybrid optimization used for several configurations of loads. Indeed, the results show that the autonomous day of the BSS can reach 03 days, while the DPSP can decrease towards 1%. Hence, the obtained HRES is eco-friendlier and more autonomous. Furthermore, the proposed idea provides improved reliability and robustness of our system under various types of loads due to different climate scenario. A statistical analysis shows a good stability and better efficiency while doing hybridization of both techniques.