Distributionally robust planning of hydrogen-electrical microgrids for sea islands

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 in 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. • Distributionally robust planning of sea-island microgrids under wind-based uncertainty. • Spatiotemporal decoupling of energy supply-demand through maritime hydrogen transport. • Model induced energy demands and fault risks via decision-dependent uncertainty sets. • Propose a DRO model to optimize investment and operation under island-specific constraints. • Develop a tailored C&CG algorithm with effective worst-case distribution computation.

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Publication Details

Journal
Applied Energy
Published
2026-03-03
DOI
https://doi.org/10.1016/j.apenergy.2026.127630
Primary Topic
Hybrid Renewable Energy Systems
Type
article
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article

Distributionally robust planning of hydrogen-electrical microgrids for sea islands

Zhengwen He, Zhengsong Lu, Tanveer Hossain Bhuiyan, Xiaoyu Cao et al.
Applied Energy
Hybrid Renewable Energy Systems
article

Distributionally robust planning of hydrogen-electrical microgrids for sea islands

Zhengwen He, Zhengsong Lu, Tanveer Hossain Bhuiyan, Xiaoyu Cao, Yuchen Dong, Bo Zeng
article en

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 in 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. • Distributionally robust planning of sea-island microgrids under wind-based uncertainty. • Spatiotemporal decoupling of energy supply-demand through maritime hydrogen transport. • Model induced energy demands and fault risks via decision-dependent uncertainty sets. • Propose a DRO model to optimize investment and operation under island-specific constraints. • Develop a tailored C&CG algorithm with effective worst-case distribution computation.

Applied EnergyVol. 411
University of Pittsburgh (US), The University of Texas at San Antonio (US), Xi'an Jiaotong University (CN)
Life below water
Openalex Percentile: Top 40%
Hybrid Renewable Energy Systems
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