Distributionally Robust Chance-Constrained Dispatch for Mobile Hydrogen Energy Systems Under Supply and Demand Uncertainties

Mobile hydrogen energy systems (MHESs) provide a flexible cross-regional hydrogen supply chain solution, where hydrogen is produced using surplus renewable energy, stored, and then transported to customers via tube trailers. Considering the uncertainties of renewable energy and hydrogen demands, we propose a data-driven distributionally robust chance-constrained (DRCC) dispatch model for MHESs. On the supply side, multiple operational states (production, standby, idle) and transitions of water electrolyzers are considered. On the transportation side, hydrogen delivery is formulated as a vehicle routing problem with time windows. Furthermore, the formulated DRCC model based on the Wasserstein ambiguity set is converted to a mixed-integer linear program with conditional value at risk approximation. Case studies are conducted on an MHES based on the traffic network of Xi'an City in China to verify the validity of the proposed method.