Distributionally Robust Planning of Hydrogen-Electrical Microgrids for Sea Islands
Yuchen Dong, Zhengsong Lu, Xiaoyu Cao, Zhengwen He, Tanveer Hossain Bhuiyan, Bo Zeng
TL;DR
This work tackles robust planning for hydrogen–electrical microgrids on sea islands connected via maritime hydrogen transport. It develops a two-stage distributionally robust optimization framework with decision-dependent uncertainty and no complete recourse, solved by a primal-based column-and-constraint generation algorithm enhanced with strong cutting planes. The model integrates resource islands, load islands, and a cycle-based hydrogen transport network to enable spatial-temporal decoupling of generation and consumption. Numerical results show that targeted resilience investments and an expanded vessel fleet can substantially reduce worst-case losses with manageable cost increases, while the proposed algorithm achieves superior scalability and solution quality. Overall, the framework offers a practical, scalable approach to robustly decarbonize and harden isolated island energy systems under deep uncertainty.
Abstract
This paper presents a distributionally robust planning method for hydrogen-electrical microgrids over islands, where the cross-island energy exchange is supported by a maritime hydrogen transport network. This planning problem is complicated due to heterogeneous off-shore wind-driven uncertainties (i.e., renewable power, transport availability, demand fluctuations, and grid faulting), a subset of which exhibit endogenous uncertainty, as they can be affected by proactive measures (e.g., grid hardening) or infrastructure investment. To capture these features, a two-stage distributionally robust optimization (DRO) model is developed considering decision-dependent uncertainty (DDU), which encompasses variation of the underlying distributional ambiguity due to the change of the first stage decisions. Notably, the complete recourse property is missing, which is often neglected in existing DRO studies. Nevertheless, different from the case for land-based microgrids, this issue is critical and fundamental for sea island systems due to their particular physical and logistical requirements. To address these issues, we develop a C&CG algorithm that is customized with strong cutting planes to handle DRO with a varying DDU ambiguity set and feasibility requirements. Numerical results demonstrate the cost-effectiveness and resilience of the proposed planning framework, along with the nontrivial improvements of the algorithm in both solution accuracy and computational efficiency.