Hydrogen, as an ideal energy carrier, can facilitate multienergy flow interactions and enhance energy coordination across diverse types of parks. Multiple heterogeneous uncertainties introduced by the hydrogen industry chain exacerbate the complexity of the operational optimization process. To this end, a hybrid robust interval optimization method is proposed herein for hydrogen-based multipark integrated energy systems (HMIESs) that consider hydrogen delivery and transportation. First, a park-level joint operational optimization model is developed that integrates hydrogen production, storage, transportation, and utilization. Then, a novel vehicle-based dynamic transportation pattern is proposed to fully leverage the potential performance benefits of HMIESs synergy. Meanwhile, the uncertainties associated with hydrogen transportation and energy demand are characterized using an ambiguity set and probability distributions of uncertain scenarios, respectively. The predicted uncertainties of renewable energy sources are described using interval numbers. Moreover, the strong duality theory and segmented linearization technique are introduced to reformulate the complex hybrid nonlinear optimization problem into a tractable mixed-integer linear programming problem. Finally, the effectiveness of the proposed method is verified via comprehensive case studies. Results reveal that hydrogen interaction across HMIESs and adequate considerations of multiple uncertainties reduce the actual overall operating costs. • A hybrid robust interval optimization method is proposed for hydrogen-based multipark integrated energy systems (HMIESs). • A novel time-refined transportation model is developed to leverage the synergy of HMIES within a network framework. • Multiple heterogeneous uncertainties related to RESs, hydrogen transportation, and energy demand are adequately considered. • This dynamic model reduces the operating cost by 9.77%.
Zhang et al. (Sun,) studied this question.