The Hybrid Renewable Energy Systems (HRES) are essential to provide reliable energy in areas without grid access. Designing these kind of systems faces challenges, like intermittent renewable inputs, mitigating operational uncertainties, and ensuring long-term system stability. To solve these obstacles, many researchers has been integrating advanced solutions, in controlling, predicting and optimizing algorithms, these efforts not only reduce costs but also increase sustainability of the system and the most important the reliability, to avoid the oversizing of the system and the power demand issues. Such strategies significantly advance global renewable energy adoption, by ensuring the demand with less costs. This informative paper focuses on optimizing the reliability of the HRES with multi-objective optimization using the metaheuristics algorithms. The idea is the evaluation of the system reliability with other objectives like minimizing costs, CO2 emission by using different metaheuristic algorithm (GA, PSO). Future work will validate the framework using real-world data. Our paper focused on the effect of others objective function and algorithms on the HRES reliability.