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Hydrogen fueling stations (HFSs) will proliferate in the near future as they are prerequisites for the fast developing hydrogen-powered vehicles (HVs). The HFSs can utilize cheap renewable energy from, e.g., wind turbines (WTs), to generate and store hydrogen on site locally. Conventional studies usually ignore the independence of the WT and HFSs and perform joint operation optimization to them. This article, however, proposes a cooperative operation model for the WT and HFSs considering individual benefit. Nash bargaining theory is employed to deal with the energy trading and benefit sharing problems during the cooperation. In particular, the conditional value-at-risk (CVaR) is used to characterize the risk-preference degree of HFSs against the uncertainties of electricity price. Moreover, an improved benders decomposition (BD) algorithm is proposed to solve the energy trading problem in a distributed manner for privacy concern; while an analytical method is developed to solve the payment bargaining problem. Numerical experiments based on two case studies indicate that the cooperation can greatly reduce the hydrogen production cost for HFSs. In addition, the proposed algorithm outperforms conventional alternating direction method of multipliers (ADMM) algorithm in the case studies.
Wu et al. (2020) studied this question.