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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| Language: | English |
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Nature Portfolio
2025-07-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-025-05313-5 |
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| author | Yirui Wang Ruize Tian Siguang Zheng Changyue Lu Shuang Zhou |
| author_facet | Yirui Wang Ruize Tian Siguang Zheng Changyue Lu Shuang Zhou |
| author_sort | Yirui Wang |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-57d2235c642244dc87d71b0c43e10e1f |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-57d2235c642244dc87d71b0c43e10e1f2025-08-20T04:02:46ZengNature PortfolioScientific Reports2045-23222025-07-0115112210.1038/s41598-025-05313-5Multi-objective optimal scheduling of islands considering offshore hydrogen productionYirui Wang0Ruize Tian1Siguang Zheng2Changyue Lu3Shuang Zhou4International Education Institute, North China Electric Power UniversitySchool of Electrical Engineering, Southwest Jiaotong UniversityThe School of Electrical and Information Engineering, Tianjin UniversitySchool of Electrical Engineering and Automation, Wuhan UniversityInternational Education Institute, North China Electric Power UniversityAbstract 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.https://doi.org/10.1038/s41598-025-05313-5Offshore islandsElectric-hydrogen-transport couplingRenewable energy microgridsCarbon emission reductionImproved grey wolf optimizer |
| spellingShingle | Yirui Wang Ruize Tian Siguang Zheng Changyue Lu Shuang Zhou Multi-objective optimal scheduling of islands considering offshore hydrogen production Scientific Reports Offshore islands Electric-hydrogen-transport coupling Renewable energy microgrids Carbon emission reduction Improved grey wolf optimizer |
| title | Multi-objective optimal scheduling of islands considering offshore hydrogen production |
| title_full | Multi-objective optimal scheduling of islands considering offshore hydrogen production |
| title_fullStr | Multi-objective optimal scheduling of islands considering offshore hydrogen production |
| title_full_unstemmed | Multi-objective optimal scheduling of islands considering offshore hydrogen production |
| title_short | Multi-objective optimal scheduling of islands considering offshore hydrogen production |
| title_sort | multi objective optimal scheduling of islands considering offshore hydrogen production |
| topic | Offshore islands Electric-hydrogen-transport coupling Renewable energy microgrids Carbon emission reduction Improved grey wolf optimizer |
| url | https://doi.org/10.1038/s41598-025-05313-5 |
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