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<p>The decarbonization and resilience enhancement of building energy systems face critical challenges due to the intermittent nature of solar/wind power and the continuous demand for heat/electricity. To address this, this article proposed a hybrid energy system synergizing renewable generation with hydrogen fuel cells (HFCs), which is designed to fulfill daily electricity and hot water requirements. The article employs a two-stage optimization framework including a multi-objective NSGA-II algorithm that simultaneously minimizes lifecycle costs and carbon emissions to determine optimal system configurations and an entropy-weighted technique for order preference by similarity to ideal solution (TOPSIS) method that evaluates Pareto-optimal solutions across fluctuating energy prices and demand scenarios. One of the key contributions of this article is forming a comprehensive system model integrating HFC dynamics, renewable intermittency, and thermal energy storage. Secondly, a data-driven weighting mechanism to balance multi-criteria decision conflicts is set up. Case studies on a commercial building demonstrated the system’s efficiency of 40.4% reduction in carbon footprint with 36.68% renewable energy penetration. Moreover, HFCs operated &gt; 80% of annual hours, with 55% of runtime at rated power. This framework provides policymakers and urban planners with a scalable toolkit for deploying hydrogen-integrated sustainable energy systems in buildings.</p>

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Research on the optimization design method of solar-wind-hydrogen hybrid energy system based on NSGA-II and entropy-weight TOPSIS framework

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年1月30日

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  • Ying Wang,
  • Xun Dong,
  • Jian Wang

摘要

The decarbonization and resilience enhancement of building energy systems face critical challenges due to the intermittent nature of solar/wind power and the continuous demand for heat/electricity. To address this, this article proposed a hybrid energy system synergizing renewable generation with hydrogen fuel cells (HFCs), which is designed to fulfill daily electricity and hot water requirements. The article employs a two-stage optimization framework including a multi-objective NSGA-II algorithm that simultaneously minimizes lifecycle costs and carbon emissions to determine optimal system configurations and an entropy-weighted technique for order preference by similarity to ideal solution (TOPSIS) method that evaluates Pareto-optimal solutions across fluctuating energy prices and demand scenarios. One of the key contributions of this article is forming a comprehensive system model integrating HFC dynamics, renewable intermittency, and thermal energy storage. Secondly, a data-driven weighting mechanism to balance multi-criteria decision conflicts is set up. Case studies on a commercial building demonstrated the system’s efficiency of 40.4% reduction in carbon footprint with 36.68% renewable energy penetration. Moreover, HFCs operated > 80% of annual hours, with 55% of runtime at rated power. This framework provides policymakers and urban planners with a scalable toolkit for deploying hydrogen-integrated sustainable energy systems in buildings.