This chapter is centered on the optimal design of an off-grid hybrid renewable microgrid, emphasizing the integration of photovoltaic (PV), wind turbine (WT), and fuel cell (FC) technologies with a hydrogen storage. The aim is to determine the most efficient sizes for these components using an innovative metaheuristic optimization technique, called weighted mean of vectors (INFO) and Beluga whale optimization (BWO). Introducing the INFO and BWO optimizers, this study tackles the multi-objective optimization task of reducing the cost of energy (COE), ensuring high reliability of the power supply through the loss of power supply probability (LPSP) index, and managing surplus energy within specified constraints. The suggested location for this hybrid system is in the Ataka region of the Suez Gulf, Egypt, positioned at latitude 30.0 and longitude 32.5, with a projected operational lifetime of 25 years. To validate the precision, suitability, and robustness of the INFO and BWO algorithms, it is rigorously tested across an off-grid hybrid microgrid system. The outcomes consistently demonstrate the superiority of the INFO algorithm, showcasing its ability to achieve the minimum fitness function value. Moreover, the chapter provides a comprehensive analysis of statistical metrics to underscore the effectiveness of the INFO algorithm. Comparative studies are conducted against several established optimization algorithms such as the salp swarm algorithm (SSA) and the grey wolf optimizer (GWO). Through extensive simulations, the INFO algorithm emerges as the top performer, showcasing remarkable efficacy in addressing complex engineering challenges. This establishes INFO as a formidable contender among contemporary algorithms, positioning it as a competitive choice for tackling intricate engineering optimization problems.