Statistically Feasible Robust Scheduling of Harbour EH-VPP Considering Photovoltaic and Hydrogen Demand Uncertainties

Electric-hydrogen coupled virtual power plants (EH-VPPs) have emerged as a promising solution to enhance energy flexibility and economy in harbors by aggregating distributed energy and hydrogen systems. However, scheduling becomes challenging due to the uncertainty of ship hydrogen demand under varying navigation environments. This paper proposes a robust scheduling method for EH-VPPs that jointly considers PV output errors and navigation-induced hydrogen demand uncertainty. A hydrogen demand estimation model is developed based on environmental factors, including wave height and wind speed. To address the difficulty in obtaining accurate data distributions, a robust uncertainty model is formulated, and a statistically feasible chance-constrained framework is introduced to describe the impact of State Of Hydrogen and State Of Charge constraints. A robust optimization model integrating statistical feasibility is then established. Case studies demonstrate that the proposed method increases profits by ​​13.8%​​ compared to conventional robust optimisation method, and the violation probability of hydrogen and charge constraints is maintained below ​​5%​​, while violation rate is 0, under the conventional robust optimisation method, which is overly conservative.