Siting and sizing of the hydrogen refueling stations with on-site water electrolysis hydrogen production based on robust regret

In recent years, hydrogen fuel cell vehicles (HFCVs), as a pollution-free and clean tool, have begun to replace internal combustion engine vehicles. However, the proliferation of HFCVs has been hindered, due to a large amount of capital required for the construction of hydrogen infrastructures including hydrogen refueling stations (HRFSs). To address this challenge, this article aims to rationally determine the sites and sizes of HRFSs to facilitate the advance of hydrogen economy. To that end, considering the investment cost of each component, a robust model for siting and sizing of HRFSs is carried out. Moreover, the uncertainty of hydrogen demand of HFCVs is considered and the added power loss is incorporated into the model when HRFSs are connected to a grid. This article proposes a model to alleviate the operation cost of HRFSs, yield the revenue and promote the development of HRFSs and HFCVs through scheduling hydrogen production and sizing the capacity of each unit of HRFSs. In order to improve solving efficiency, nonlinear parts of the model are transformed into second-order cone programming and the two-stage LaGrange relaxation algorithm is presented to achieve the optimal solution. The power-traffic network is taken as an example to account for the proposed model. Four HRFSs are planned according to the robust model and the rated power of electrolyzers in each HRFS is 6.41, 5.91, 6.41, and 5.23 MW, respectively; for compressors it is 292, 269, 292, and 238 kW, respectively; the capacities for hydrogen storage tanks are 900, 840, 861, and 763 kg, respectively. Compared with the robust regret under deterministic hydrogen demand, the robust regret considering the 10% hydrogen demand fluctuation is reduced by 78.15%, which reveals that the solution of the proposed model is more in line with the decision-maker' psychological will. HIGHLIGHTS A robust regret model for HRFSs is built to adapt to any uncertain demand cases. A combination of traffic demand network and distribution power grid is considered. The optimal sites and sizes of HRFSs and hydrogen production schedule are obtained. The interval-based method is adopted to model the hydrogen demand uncertainty. The LaGrange relaxation algorithm is employed to get the global optimal solution.