Optimal scheduling of hydrogen energy hub for stable demand with uncertain photovoltaic and biomass

Single hydrogen production methods cannot meet the stable hydrogen demand for many engineering applications under carbon emission requirements. This paper proposes a hydrogen energy hub (HEH) for stable and green hydrogen production from variable renewable energy inputs. The HEH integrates water electrolysis, biomass gasification, and natural gas reforming, which are coupled and coordinated with complementary utilization of both materials and energy. The uncertainties associated with biomass moisture content (MC) and photovoltaic (PV) generation for hydrogen production are considered. The impact of MC on the production rate of biomass is quantified and embedded in a thermodynamic equilibrium model, and inaccurate PV forecasts are also taken into account. A systematic model of HEH is developed to improve the economic benefit of system operation while providing probabilistic guarantees on the robustness of stable hydrogen production. A double -loop robust algorithm is adapted to efficiently solve the robust model, with the outer loop developing a day -ahead scheduling scheme and the inner loop figuring out the worst -case scenario. Finally, the effectiveness of the proposed model is demonstrated through case studies in terms of cost reduction, decision robustness, and computational efficiency. A 9.9% improvement in energy efficiency can be achieved through complementary utilization. The robust optimization is able to achieve an average total cost reduction of 37.52% over the deterministic optimization in 1000 random scenarios.