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Capacity configuration and optimization of PV/T coupled gas turbine multi-energy cogeneration system for data center

Author

Listed:
  • Liu, Yang
  • Hang, Chenzhe
  • Yue, Han
  • Chu, Shangling
  • Liu, Haowen
  • Han, Yumeng
  • Zhang, Heng
  • Huang, Jiguang
  • Xu, Dinghua

Abstract

The escalating energy consumption and substantial carbon emissions from data centers have become critical challenges that require urgent addressing. To tackle these issues, this study integrates solar energy with a conventional natural gas-based combined cooling, heating, and power (CCHP) system, establishing a novel photovoltaic/thermal (PV/T) coupled gas turbine multi-energy cogeneration system. Given that data centers generate considerable amounts of low-grade waste heat, this heat is repurposed as a source for the heat pump to improve its efficiency. To enhance the overall energy efficiency, reduce annual total costs (ATC) and carbon dioxide emissions (CDE), a multi-objective optimization model is developed using the TRNSYS and Grasshopper platforms, with the NSGA-III algorithm employed to obtain the Pareto-optimal solutions. Research indicates that with an airflow rate of 106.21 kg/s, the gas-fired boiler capacity is 62.7 kW, the water-source heat pump capacity is 453 kW, and the PV/T area is 1001 m2. The system energy efficiency reaches 46.10 %, with an ATC of 9099200 USD and a CDE of 51556000 kg. Under optimal operating conditions, the CCHP system proposed in this paper achieves a 3.85 % reduction in ATC and a 22.68 % decrease in CDE compared to the SP system.

Suggested Citation

  • Liu, Yang & Hang, Chenzhe & Yue, Han & Chu, Shangling & Liu, Haowen & Han, Yumeng & Zhang, Heng & Huang, Jiguang & Xu, Dinghua, 2026. "Capacity configuration and optimization of PV/T coupled gas turbine multi-energy cogeneration system for data center," Energy, Elsevier, vol. 342(C).
    • Handle: RePEc:eee:energy:v:342:y:2026:i:c:s0360544225051941
    DOI: 10.1016/j.energy.2025.139552
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    as
    1. Wang, Yihan & Chen, Tingsen & Khan, Sheher Yar & Liu, Shuli & Shen, Yongliang & Shao, Yingjuan & Ji, Wenjie & Xu, Zhiqi, 2025. "Evaluation and optimization of a novel CPC-PV/T driven cooling, heating and power cogeneration system based on thermochemical energy storage," Energy, Elsevier, vol. 316(C).
    2. Zhang, Yingbo & Tang, Hong & Li, Hangxin & Wang, Shengwei, 2025. "Unlocking the flexibilities of data centers for smart grid services: Optimal dispatch and design of energy storage systems under progressive loading," Energy, Elsevier, vol. 316(C).
    3. Ma, Weiwu & Fang, Song & Liu, Gang, 2017. "Hybrid optimization method and seasonal operation strategy for distributed energy system integrating CCHP, photovoltaic and ground source heat pump," Energy, Elsevier, vol. 141(C), pages 1439-1455.
    4. Yang, Xinyi & Wang, Yilin & Wang, Ranxu & Zhang, Heng & Chen, Haiping & Huang, Jiguang & Gao, Dan, 2025. "Integrated PV/T coupled PEM system for low-carbon office buildings: Dynamic simulation, multi-energy synergy, and economic analysis," Energy, Elsevier, vol. 330(C).
    5. Hyvönen, Johannes & Mori, Taro & Saunavaara, Juha & Hiltunen, Pauli & Pärssinen, Matti & Syri, Sanna, 2024. "Potential of solar photovoltaics and waste heat utilization in cold climate data centers. Case study: Finland and northern Japan," Renewable and Sustainable Energy Reviews, Elsevier, vol. 201(C).
    6. Das, Barun K. & Tushar, Mohammad Shahed H.K. & Zaman, Forhad, 2021. "Techno-economic feasibility and size optimisation of an off-grid hybrid system for supplying electricity and thermal loads," Energy, Elsevier, vol. 215(PA).
    7. Ali Yildirim, Mehmet & Bartyzel, Filip & Vallati, Andrea & Woźniak, Magdalena Kozień & Ocłoń, Paweł, 2023. "Efficient energy storage in residential buildings integrated with RESHeat system," Applied Energy, Elsevier, vol. 335(C).
    8. Hu, Yuanyuan & Yang, Jing & Ruan, Xiaoli & Chen, Yuling & Li, Chengjiang & Zhang, Zhaohu & Zhang, Wei, 2025. "Green optimization for micro data centers: Task scheduling for a combined energy consumption strategy," Applied Energy, Elsevier, vol. 393(C).
    9. 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).
    10. Han, Jie & Ouyang, Leixin & Xu, Yuzhen & Zeng, Rong & Kang, Shushuo & Zhang, Guoqiang, 2016. "Current status of distributed energy system in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 288-297.
    11. Xu, Rui & Liu, Fang, 2025. "Dynamic modeling and co-optimization of configuration and operation for a solar-assisted ejector heat pump with energy storages," Energy, Elsevier, vol. 320(C).
    12. Das, Barun K. & Al-Abdeli, Yasir M. & Kothapalli, Ganesh, 2017. "Optimisation of stand-alone hybrid energy systems supplemented by combustion-based prime movers," Applied Energy, Elsevier, vol. 196(C), pages 18-33.
    13. Kahil, Hussain & Sharma, Shiva & Välisuo, Petri & Elmusrati, Mohammed, 2025. "Reinforcement learning for data center energy efficiency optimization: A systematic literature review and research roadmap," Applied Energy, Elsevier, vol. 389(C).
    14. Lugo, S. & García-Valladares, O. & Best, R. & Hernández, J. & Hernández, F., 2019. "Numerical simulation and experimental validation of an evacuated solar collector heating system with gas boiler backup for industrial process heating in warm climates," Renewable Energy, Elsevier, vol. 139(C), pages 1120-1132.
    15. Wang, Jiangjiang & Chen, Yuzhu & Lior, Noam & Li, Weihua, 2019. "Energy, exergy and environmental analysis of a hybrid combined cooling heating and power system integrated with compound parabolic concentrated-photovoltaic thermal solar collectors," Energy, Elsevier, vol. 185(C), pages 463-476.
    16. Ren, Fukang & Wei, Ziqing & Zhai, Xiaoqiang, 2021. "Multi-objective optimization and evaluation of hybrid CCHP systems for different building types," Energy, Elsevier, vol. 215(PA).
    17. Diallo, Thierno M.O. & Zhao, Xudong & Dugue, Antoine & Bonnamy, Paul & Javier Miguel, Francisco & Martinez, Asier & Theodosiou, Theodoros & Liu, Jing-Sheng & Brown, Nathan, 2017. "Numerical investigation of the energy performance of an Opaque Ventilated Façade system employing a smart modular heat recovery unit and a latent heat thermal energy system," Applied Energy, Elsevier, vol. 205(C), pages 130-152.
    18. Sheykhi, Mohammad & Mehregan, Mahmood & Ghorbani, Saeed & Emamian, Amin & Kayhani, Mohammad Hassan & Delouei, Amin Amiri & Kharazmi, Shahabodin & Sheykhian, Mohammad Kazem & Zhu, Shunmin, 2025. "Simulation and performance optimization of a novel hybrid CCHP system based on the prime movers of internal combustion engine and Stirling engine," Applied Energy, Elsevier, vol. 393(C).
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