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Investigation on the all-day electrical/thermal and antifreeze performance of a new vacuum double-glazing PV/T collector in typical climates — Compared with single-glazing PV/T

Author

Listed:
  • Li, Zhaomeng
  • Ji, Jie
  • Zhang, Feng
  • Zhao, Bin
  • Xu, Ruru
  • Cui, Yu
  • Song, Zhiying
  • Wen, Xin

Abstract

The top heat dissipation accounts for the main part of heat loss of water-type PV/T systems, and the PV/T collectors are vulnerable to frozen-water expansion and pipe cracking on cold winter nights. This study proposes to apply the vacuum double-glass in PV/T for its high thermal resistance and thus good heat preservation. Mathematical models of the vacuum double-glazing PV/T and single-glazing PV/T system are developed. Then they are validated by a daytime test and a freezing test. A case study is conducted about the all-day performance of them in winter of 3 typical areas. Results show that vacuum double-glazing PV/T performs well in the cold winter of Hefei with the thermal efficiency increased by 15.7% relatively and the completely-frozen time postponed by 3.5 h, while the electrical efficiency drops by relatively 15.5%, negatively affected by the increased temperature insides and the lower glass cover transmittance. Parametric discussions are conducted (pipes diameter, glass extinction, tube pitch, PV packing factor) and it shows varying influences on the daytime thermal, electrical, and anti-freezing performance of the two PV/T. By adjusting the structure parameters, the thermal and antifreeze performance of vacuum double-glazing PV/T in winter is guaranteed.

Suggested Citation

  • Li, Zhaomeng & Ji, Jie & Zhang, Feng & Zhao, Bin & Xu, Ruru & Cui, Yu & Song, Zhiying & Wen, Xin, 2021. "Investigation on the all-day electrical/thermal and antifreeze performance of a new vacuum double-glazing PV/T collector in typical climates — Compared with single-glazing PV/T," Energy, Elsevier, vol. 235(C).
    • Handle: RePEc:eee:energy:v:235:y:2021:i:c:s036054422101478x
    DOI: 10.1016/j.energy.2021.121230
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    References listed on IDEAS

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    Cited by:

    1. Scott, Connor & Ahsan, Mominul & Albarbar, Alhussein, 2023. "Machine learning for forecasting a photovoltaic (PV) generation system," Energy, Elsevier, vol. 278(C).
    2. Li, Zhaomeng & Ji, Jie & Zhao, Xudong & Li, Guiqiang & Cui, Yu & Song, Zhiying & Yao, Tingting, 2022. "Parametric analysis on G-PV/T collector: Performance optimization and energy trade-off among two critical structures under various outside conditions," Energy, Elsevier, vol. 255(C).
    3. Zhou, Haihua & Cai, Jingyong & Zhang, Tao & Xu, Lijie & Li, Qifen & Ren, Hongbo & Shi, Zhengrong & Zhou, Fan, 2023. "Performance analysis on the concentrated photovoltaic /thermal air collector with phase change material and vacuum double-glazing for temperature regulation," Renewable Energy, Elsevier, vol. 207(C), pages 27-39.

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