A methodology for optimal energy management for efficient and profitable hydrogen production and storage

Abstract Recently, the production of low-carbon hydrogen through water electrolysis and its use is considered a promising strategy for abating greenhouse gasses in industrial and automotive sectors. Indeed, hydrogen can be generated from renewable energy sources and then stored to produce energy or to be used as feedstock in several industrial processes. Hydrogen production and utilization business case is strongly dependent on electricity price, that influences the operating cost and therefore the hydrogen cost per kilogram. In this work, the electricity supply is assumed from grid; however, with the proposed modeling, it was possible to demonstrate how the energy management can support the optimal use of energy and enable a more efficient hydrogen supply chain even when renewable sources are not available. For this purpose, it was necessary to find optimal price-driven energy strategies, to manage hydrogen demand, production, and storage. The proposed model allows to achieve the optimal hydrogen storage system size to evaluate the profitability of different control strategies. Electricity price estimations were performed through three procedures to compare the prediction accuracy of a traditional regression algorithm with profile decomposition, and a neural network-based technique. Four hydrogen production profiles have been evaluated in terms of the necessary storage capacity to fulfill the hydrogen demand profiles. Simulation results showed that the use of modulation of power following the estimated electricity price profile allows to minimize the return of investment, and therefore the payback period. Graphical abstract