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 |
| Published: |
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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| Summary: | 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. |
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| ISSN: | 2096-5117 |