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With the rapid advancement of technology in the energy sector and the demand for sustainable energy practices, the world is aiming at fostering the hydrogen economy and developing proper energy management utilizing green hydrogen. To ensure the successful adoption of hydrogen-driven renewable energy systems, a thorough understanding of the degree to which hybrid renewable energy systems (HRESs) can be optimized whilst meeting commercial and societal goals is critical. The work presented here is comprehensive and geared towards reviewing the application of artificial intelligence (AI) in HRESs, particularly solar photovoltaic and wind energy that are integrated with fuel cells (FCs). Common AI methods such as genetic algorithm, particle swarm optimization, simulated annealing, random forest, k-nearest neighbors, support vector machine, and artificial neural network are introduced, current FCs …