Adaptive robust scheduling of a hydro/photovoltaic/pumped-storage hybrid system in day-ahead electricity and hydrogen markets

Abstract

A hybrid energy generation system (HEGS) exploits the synergies of various energy to improve the utilization rate of renewable energy while enhancing economic efficiency. In deregulated energy markets, this study proposes a scheduling model for HEGS trading in both day-ahead electricity and hydrogen markets to maximize total profits based on price arbitrage. This HEGS is based on a real case in Southwest China and comprises three hydro units, two photovoltaic (PV) plants a pumped-storage facility, and an electrolyzer. The uncertainty of available PV power generation is modelled using polyhedral uncertainty set and then the proposed model is cast as an adaptive robust optimization (ARO) model in which the conservativeness can be controlled by the PV uncertainty budget (ΓPV). Then the column-and-constraint generation algorithm is employed to solve this model. The numerical results reveal that the total profit of HEGS trading in two markets can be increased compared to the case of only trading in the electricity market. For instance, the increase in the total profit is 1.01 % (i.e. 5091 CNY) when ΓPV = 2. Besides, the total profit is considerably affected by ΓPV. As ΓPV increases from 2 to 8 (i.e. the robustness increases), the total profit decreases from 507,045.5 CNY to 503,036.1 CNY. Moreover, sensitivity analysis of the total profit related to the pumped-storage capacity and hydrogen price are also presented.