Multi-objective optimal scheduling of islands considering offshore hydrogen production
Abstract Ocean islands possess abundant renewable energy resources, providing favorable conditions for developing offshore clean energy microgrids. However, geographical isolation poses significant challenges for direct energy transfer between islands. Recent electrolysis and hydrogen storage techno...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-07-01
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| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-05313-5 |
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| Summary: | Abstract Ocean islands possess abundant renewable energy resources, providing favorable conditions for developing offshore clean energy microgrids. However, geographical isolation poses significant challenges for direct energy transfer between islands. Recent electrolysis and hydrogen storage technology advancements have created new opportunities for distributed energy utilization in these remote areas. This paper presents a low-carbon economic dispatch strategy designed explicitly for distant oceanic islands, incorporating energy self-sufficiency rates and seasonal hydrogen storage (SHS). We propose a power supply model for offshore islands considering hydrogen production from offshore wind power. The proposed model minimizes operational and carbon emission costs while maximizing energy self-sufficiency. It considers the operational constraints of the island’s energy system, the offshore transportation network, the hydrogen storage infrastructure, and the electricity-hydrogen-transportation coupling of hydrogen storage (HS) and seasonal hydrogen storage (SHS) services. To optimize the dispatch process, this study employs an improved Grey Wolf Optimizer (IGWO) combined with the Differential Evolution method to enhance population diversity and refine the position updating mechanism. Simulation results demonstrate that integrating HS and SHS effectively enhances energy self-sufficiency and reduces carbon emissions. For instance, hydrogenation costs decreased by 21.4% after optimization, and the peak-valley difference was reduced by 16%. These findings validate the feasibility and effectiveness of the proposed approach. |
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| ISSN: | 2045-2322 |