Scatter Search for Optimal Sizing of a Hybrid Renewable Energy System for Scheduling Green Hydrogen Production

At present, energy demands are mainly covered by the use of fossil fuels. The process of fossil fuel production increases pollution from oil extraction, transport to processing centers, treatment to obtain lighter fractions, and delivery and use by the final consumers. Such polluting circumstances are aggravated in the case of accidents involving fossil fuels. They are also linked to speculative markets. As a result, the trend is towards the decarbonization of lifestyles in advanced societies. The present paper addresses the problem of the optimal sizing of a hybrid renewable energy system for scheduling green hydrogen production. A local system fully powered by renewable energies is designed to obtain hydrogen from seawater. In order to monetize excess energy, the grid connection of the system is considered under realistic energy market constraints, designing an hourly purchasing strategy. This crucial problem, which has not been taken into account in the literature, is solved by the specific dispatch strategy designed. Several optimization methods have been used to solve this problem; however, the scatter search method has not previously been employed. In this paper, the problem is faced with a novel implementation of this method. The implementation is competitive in terms of performance when compared to, on the one hand, the genetic algorithm and differential evolution methods, which are well-known state-of-the-art evolutionary algorithms, and, on the other hand, the optimal foraging algorithm (OFA), a more recent algorithm. Furthermore, scatter search outperformed all other methods in terms of computational cost. This is promising for real-world applications that require quick responses.