Distributionally robust optimization-based scheduling for a hydrogen-coupled integrated energy system considering carbon trading and demand response
Addressing climate change and facilitating the large-scale integration of renewable energy sources (RESs) have driven the development of hydrogen-coupled integrated energy systems (HIES), which enhance energy sustainability through coordinated electricity, thermal, natural gas, and hydrogen utilizat...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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KeAi Communications Co., Ltd.
2025-04-01
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| Series: | Global Energy Interconnection |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2096511725000301 |
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| author | Zhichun Yang Lin Cheng Huaidong Min Yang Lei Yanfeng Yang |
| author_facet | Zhichun Yang Lin Cheng Huaidong Min Yang Lei Yanfeng Yang |
| author_sort | Zhichun Yang |
| collection | DOAJ |
| description | Addressing climate change and facilitating the large-scale integration of renewable energy sources (RESs) have driven the development of hydrogen-coupled integrated energy systems (HIES), which enhance energy sustainability through coordinated electricity, thermal, natural gas, and hydrogen utilization. This study proposes a two-stage distributionally robust optimization (DRO)-based scheduling method to improve the economic efficiency and reduce carbon emissions of HIES. The framework incorporates a ladder-type carbon trading mechanism to regulate emissions and implements a demand response (DR) program to adjust flexible multi-energy loads, thereby prioritizing RES consumption. Uncertainties from RES generation and load demand are addressed through an ambiguity set, enabling robust decision-making. The column-and-constraint generation (C&CG) algorithm efficiently solves the two-stage DRO model. Case studies demonstrate that the proposed method reduces operational costs by 3.56%, increases photovoltaic consumption rates by 5.44%, and significantly lowers carbon emissions compared to conventional approaches. Furthermore, the DRO framework achieves a superior balance between conservativeness and robustness over conventional stochastic and robust optimization methods, highlighting its potential to advance cost-effective, low-carbon energy systems while ensuring grid stability under uncertainty. |
| format | Article |
| id | doaj-art-943b403efb204fa685ca19470b49abc8 |
| institution | Kabale University |
| issn | 2096-5117 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | KeAi Communications Co., Ltd. |
| record_format | Article |
| series | Global Energy Interconnection |
| spelling | doaj-art-943b403efb204fa685ca19470b49abc82025-08-20T03:47:41ZengKeAi Communications Co., Ltd.Global Energy Interconnection2096-51172025-04-018217518710.1016/j.gloei.2025.02.002Distributionally robust optimization-based scheduling for a hydrogen-coupled integrated energy system considering carbon trading and demand responseZhichun Yang0Lin Cheng1Huaidong Min2Yang Lei3Yanfeng Yang4Distribution Network Technology Center, Electric Power Research Institute of State Grid Hubei Co. Ltd, Wuhan 430077, PR ChinaResearch Center for Energy Internet of Things, Wuxi Research Institute of Applied Technologies, Tsinghua University, Wuxi 214026, PR ChinaDistribution Network Technology Center, Electric Power Research Institute of State Grid Hubei Co. Ltd, Wuhan 430077, PR ChinaDistribution Network Technology Center, Electric Power Research Institute of State Grid Hubei Co. Ltd, Wuhan 430077, PR ChinaResearch Center for Energy Internet of Things, Wuxi Research Institute of Applied Technologies, Tsinghua University, Wuxi 214026, PR China; Corresponding author.Addressing climate change and facilitating the large-scale integration of renewable energy sources (RESs) have driven the development of hydrogen-coupled integrated energy systems (HIES), which enhance energy sustainability through coordinated electricity, thermal, natural gas, and hydrogen utilization. This study proposes a two-stage distributionally robust optimization (DRO)-based scheduling method to improve the economic efficiency and reduce carbon emissions of HIES. The framework incorporates a ladder-type carbon trading mechanism to regulate emissions and implements a demand response (DR) program to adjust flexible multi-energy loads, thereby prioritizing RES consumption. Uncertainties from RES generation and load demand are addressed through an ambiguity set, enabling robust decision-making. The column-and-constraint generation (C&CG) algorithm efficiently solves the two-stage DRO model. Case studies demonstrate that the proposed method reduces operational costs by 3.56%, increases photovoltaic consumption rates by 5.44%, and significantly lowers carbon emissions compared to conventional approaches. Furthermore, the DRO framework achieves a superior balance between conservativeness and robustness over conventional stochastic and robust optimization methods, highlighting its potential to advance cost-effective, low-carbon energy systems while ensuring grid stability under uncertainty.http://www.sciencedirect.com/science/article/pii/S2096511725000301Hydrogen-coupled integrated energy system (HIES)Low-carbon operationDistributionally robust optimization (DRO)Carbon tradingDemand response (DR)Economy |
| spellingShingle | Zhichun Yang Lin Cheng Huaidong Min Yang Lei Yanfeng Yang Distributionally robust optimization-based scheduling for a hydrogen-coupled integrated energy system considering carbon trading and demand response Global Energy Interconnection Hydrogen-coupled integrated energy system (HIES) Low-carbon operation Distributionally robust optimization (DRO) Carbon trading Demand response (DR) Economy |
| title | Distributionally robust optimization-based scheduling for a hydrogen-coupled integrated energy system considering carbon trading and demand response |
| title_full | Distributionally robust optimization-based scheduling for a hydrogen-coupled integrated energy system considering carbon trading and demand response |
| title_fullStr | Distributionally robust optimization-based scheduling for a hydrogen-coupled integrated energy system considering carbon trading and demand response |
| title_full_unstemmed | Distributionally robust optimization-based scheduling for a hydrogen-coupled integrated energy system considering carbon trading and demand response |
| title_short | Distributionally robust optimization-based scheduling for a hydrogen-coupled integrated energy system considering carbon trading and demand response |
| title_sort | distributionally robust optimization based scheduling for a hydrogen coupled integrated energy system considering carbon trading and demand response |
| topic | Hydrogen-coupled integrated energy system (HIES) Low-carbon operation Distributionally robust optimization (DRO) Carbon trading Demand response (DR) Economy |
| url | http://www.sciencedirect.com/science/article/pii/S2096511725000301 |
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