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<p>The rapid expansion of the offshore wind power sector, combined with the inherent variability of this energy source and challenges in consumption, has brought these issues to the forefront. As such, it is increasingly important to investigate offshore wind power hydrogen production (OWPHP) technology and its coordination with demand response on the load side to mitigate fluctuations in offshore wind power, increase wind power consumption, and reduce carbon emissions. This paper proposes a two-stage robust optimization approach for a hydrogen-based integrated energy system, accounting for OWPHP and multi-type demand response. First, to address the challenges of offshore wind power consumption, the operational mechanisms of hydrogen production, transportation, and storage technologies were explored, leading to the construction of an optimization model for OWPHP. Second, to enhance the efficiency of hydrogen utilization, a multi-stage hydrogen energy utilization model was developed, which incorporates methane reactor (MR), hydrogen fuel cell (HFC), and hydrogen blending with fuel gas. Third, to fully leverage the regulatory potential of demand-side resources, a multi-type demand response model was established, integrating price-based, incentive-based, and substitution-based responses, aiming to increase offshore wind power consumption. Finally, considering the uncertainties in offshore wind and photovoltaic power generation, an adjustable uncertainty set was employed to model the fluctuations in power output. A two-stage robust optimization model was then developed to minimize total system costs under worst-case scenario. Subsequently, the model is solved using a column constraint generation algorithm and CPLEX toolbox. The case study results show that after the introduction of the OWPHP technology, the wind power consumption level can be significantly improved. The curtailment of wind power cost, the total cost of the system, and the carbon emissions are reduced by approximately 28.60%, 3.72%, and 10.25%, respectively. Moreover, considering the multi-link utilization of hydrogen energy can further enhance the system's economic efficiency and low-carbon performance. Compared with the traditional demand response model, the multi-type demand response model can give full play to the regulation capacity of the demand side to a greater extent, reducing the total cost of the IES and carbon emissions by about 2.11% and 2.47% respectively. In addition, through two-layer optimization, the proposed two-stage robust optimization method has better economic efficiency, low-carbon performance, and robustness compared with traditional uncertainty methods.</p>

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Two-stage robust optimization of a hydrogen-based integrated energy system considering offshore wind power hydrogen production and multi-type demand response

  • 期刊论文

  • 发表日期：

    2025年6月7日

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  • Ying Wang

摘要

The rapid expansion of the offshore wind power sector, combined with the inherent variability of this energy source and challenges in consumption, has brought these issues to the forefront. As such, it is increasingly important to investigate offshore wind power hydrogen production (OWPHP) technology and its coordination with demand response on the load side to mitigate fluctuations in offshore wind power, increase wind power consumption, and reduce carbon emissions. This paper proposes a two-stage robust optimization approach for a hydrogen-based integrated energy system, accounting for OWPHP and multi-type demand response. First, to address the challenges of offshore wind power consumption, the operational mechanisms of hydrogen production, transportation, and storage technologies were explored, leading to the construction of an optimization model for OWPHP. Second, to enhance the efficiency of hydrogen utilization, a multi-stage hydrogen energy utilization model was developed, which incorporates methane reactor (MR), hydrogen fuel cell (HFC), and hydrogen blending with fuel gas. Third, to fully leverage the regulatory potential of demand-side resources, a multi-type demand response model was established, integrating price-based, incentive-based, and substitution-based responses, aiming to increase offshore wind power consumption. Finally, considering the uncertainties in offshore wind and photovoltaic power generation, an adjustable uncertainty set was employed to model the fluctuations in power output. A two-stage robust optimization model was then developed to minimize total system costs under worst-case scenario. Subsequently, the model is solved using a column constraint generation algorithm and CPLEX toolbox. The case study results show that after the introduction of the OWPHP technology, the wind power consumption level can be significantly improved. The curtailment of wind power cost, the total cost of the system, and the carbon emissions are reduced by approximately 28.60%, 3.72%, and 10.25%, respectively. Moreover, considering the multi-link utilization of hydrogen energy can further enhance the system's economic efficiency and low-carbon performance. Compared with the traditional demand response model, the multi-type demand response model can give full play to the regulation capacity of the demand side to a greater extent, reducing the total cost of the IES and carbon emissions by about 2.11% and 2.47% respectively. In addition, through two-layer optimization, the proposed two-stage robust optimization method has better economic efficiency, low-carbon performance, and robustness compared with traditional uncertainty methods.