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Multi-objective optimization of a solar-driven trigeneration system considering power-to-heat storage and carbon tax

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  • Chen, Yuzhu
  • Hu, Xiaojian
  • Xu, Wentao
  • Xu, Qiliang
  • Wang, Jun
  • Lund, Peter D.

Abstract

Advanced solar driven tri-generation systems are highly relevant to reduce emissions and increase energy security. Here, solar collectors and photovoltaics are coupled to a tri-generation system to produce multiple final energy forms simultaneously for an office building. The excess solar electricity is employed for cooling/heating through a power-to-heat conversion employing thermal energy storage. Comprehensive optimization is performed to maximize the energy, environmental, and economic benefits, and the carbon tax is included to monetize the emissions. A coupled decision-making method is then used to choose the ideal scheme from the optimized sets of system configuration accompanied with a sensitivity analysis against key parameters. Compared to the conventional system, the proposed system improves the energy performance by 41.4% and the environmental benefits by 41.7% with the highest solar energy utilization rate. The economic performance improves in the best case by 14.4% only, but with the lowest utilization rate of solar energy. The ideal solution covers 30%, 54%, and 62% of the electricity, cooling, and heating loads, respectively, and the corresponded energy, environmental, and economic performance improves by 29.1%, 34.6%, and 7.7%, respectively. The sensitivity analysis shows that the economic performance is more sensitive to the electricity price than to the carbon tax.

Suggested Citation

  • Chen, Yuzhu & Hu, Xiaojian & Xu, Wentao & Xu, Qiliang & Wang, Jun & Lund, Peter D., 2022. "Multi-objective optimization of a solar-driven trigeneration system considering power-to-heat storage and carbon tax," Energy, Elsevier, vol. 250(C).
    • Handle: RePEc:eee:energy:v:250:y:2022:i:c:s0360544222006594
    DOI: 10.1016/j.energy.2022.123756
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    References listed on IDEAS

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    6. Pourmoghadam, Peyman & Kasaeian, Alibakhsh, 2023. "Economic and energy evaluation of a solar multi-generation system powered by the parabolic trough collectors," Energy, Elsevier, vol. 262(PA).
    7. Xiong, Kang & Hu, Weihao & Cao, Di & Li, Sichen & Zhang, Guozhou & Liu, Wen & Huang, Qi & Chen, Zhe, 2023. "Coordinated energy management strategy for multi-energy hub with thermo-electrochemical effect based power-to-ammonia: A multi-agent deep reinforcement learning enabled approach," Renewable Energy, Elsevier, vol. 214(C), pages 216-232.
    8. Li, Ling-Ling & Qu, Li-Nan & Tseng, Ming-Lang & Lim, Ming K. & Ren, Xin-Yu & Miao, Yan, 2024. "Optimization and performance assessment of solar-assisted combined cooling, heating and power system systems: Multi-objective gradient-based optimizer," Energy, Elsevier, vol. 289(C).
    9. Chen, Yuzhu & Xu, Jinzhao & Wang, Jun & Lund, Peter D., 2022. "Optimization of a weather-based energy system for high cooling and low heating conditions using different types of water-cooled chiller," Energy, Elsevier, vol. 252(C).

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