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Optimization of a New Phase Change Material Integrated Photovoltaic/Thermal Panel with The Active Cooling Technique Using Taguchi Method

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  • Xiaohong Liu

    (College of Architecture, Hunan University, Changsha 410082, Hunan, China
    Design Institute of University of South China, Co., LTD, Hengyang 421001, Hunan, China
    Hunan University Design Institute Co., LTD, Changsha 410082, Hunan, China
    National Center for International Research Collaboration in Building Safety and Environment, Hunan University, Changsha 410082, Hunan, China)

  • Yuekuan Zhou

    (National Center for International Research Collaboration in Building Safety and Environment, Hunan University, Changsha 410082, Hunan, China
    Department of Building Services Engineering, Faculty of Construction and Environment, The Hong Kong Polytechnic University, Hong Kong 999077, China
    College of Civil Engineering, Hunan University, Changsha 410082, Hunan, China)

  • Chun-Qing Li

    (School of Engineering, RMIT University, Melbourne 3000, Australia)

  • Yaolin Lin

    (College of Architecture, Hunan University, Changsha 410082, Hunan, China)

  • Wei Yang

    (College of Engineering and Science, Victoria University, Melbourne 8001, Australia)

  • Guoqiang Zhang

    (College of Architecture, Hunan University, Changsha 410082, Hunan, China
    National Center for International Research Collaboration in Building Safety and Environment, Hunan University, Changsha 410082, Hunan, China
    College of Civil Engineering, Hunan University, Changsha 410082, Hunan, China)

Abstract

This paper investigates the energy performances of a hybrid system composed of a phase change materials-ventilated Trombe wall (PCMs-VTW) and a photovoltaic/thermal panel integrated with phase change material (PV/T-PCM). Equivalent overall output energy (Q E ) was proposed for energy performance evaluation regarding different energy forms, diversified conversions and hybrid thermal storages. This study focuses on parameters’ optimization of the PV/T-PCM system and parameters in the PCMs-VTW are kept optimal. Based on the experimentally validated numerical modelling, nine trial experiments have been conducted following Taguchi L 9 (3 4 ) standard orthogonal array. The higher the better concept was implemented and the optimal combination of operating parameters was thereafter identified by using signal-to-noise (S/N) ratio and Analysis of Variance (ANOVA) method. The results show that Q E is highly dependent on the mass flow rate, followed by the diameter of active cooling water pipe. However, the inlet cooling water temperature and the thickness of PCM have limited influence on Q E . The optimal combination of each factor was identified as B3A3C2D1 (mass flow rate of 1 kg/s, diameter of water pipe of 0.6 m, inlet cooling water temperature of 15 °C and the thickness of PCM of 20 mm) with the highest Q E of 20,700 kWh.

Suggested Citation

  • Xiaohong Liu & Yuekuan Zhou & Chun-Qing Li & Yaolin Lin & Wei Yang & Guoqiang Zhang, 2019. "Optimization of a New Phase Change Material Integrated Photovoltaic/Thermal Panel with The Active Cooling Technique Using Taguchi Method," Energies, MDPI, vol. 12(6), pages 1-22, March.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:6:p:1022-:d:214336
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    5. Zhou, Yuekuan & Zheng, Siqian & Zhang, Guoqiang, 2019. "Study on the energy performance enhancement of a new PCMs integrated hybrid system with the active cooling and hybrid ventilations," Energy, Elsevier, vol. 179(C), pages 111-128.
    6. Yu, Qinghua & Chen, Xi & Yang, Hongxing, 2021. "Research progress on utilization of phase change materials in photovoltaic/thermal systems: A critical review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 149(C).
    7. Zhou, Yuekuan & Zheng, Siqian, 2020. "Climate adaptive optimal design of an aerogel glazing system with the integration of a heuristic teaching-learning-based algorithm in machine learning-based optimization," Renewable Energy, Elsevier, vol. 153(C), pages 375-391.
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    9. Hwi-Ung Choi & Kwang-Hwan Choi, 2022. "Performance Evaluation of PVT Air Collector Coupled with a Triangular Block in Actual Climate Conditions in Korea," Energies, MDPI, vol. 15(11), pages 1-12, June.
    10. Lin, Yaolin & Feng, Haoming & Yang, Wei & Hao, Xiaoli & Tian, Lin & Yuan, Xingping, 2022. "Thermal performance optimization of a semi-nested building coupled with an earth-to-air heat exchanger using iterative Taguchi method," Renewable Energy, Elsevier, vol. 195(C), pages 1275-1290.
    11. Zhou, Yuekuan & Zheng, Siqian, 2020. "Multi-level uncertainty optimisation on phase change materials integrated renewable systems with hybrid ventilations and active cooling," Energy, Elsevier, vol. 202(C).
    12. Karthikeyan Velmurugan & Rajvikram Madurai Elavarasan & Pham Van De & Vaithinathan Karthikeyan & Tulja Bhavani Korukonda & Joshuva Arockia Dhanraj & Kanchanok Emsaeng & Md. Shahariar Chowdhury & Kuaan, 2022. "A Review of Heat Batteries Based PV Module Cooling—Case Studies on Performance Enhancement of Large-Scale Solar PV System," Sustainability, MDPI, vol. 14(4), pages 1-65, February.
    13. Zhang, Haihua & Yang, Dong & Tam, Vivian W.Y. & Tao, Yao & Zhang, Guomin & Setunge, Sujeeva & Shi, Long, 2021. "A critical review of combined natural ventilation techniques in sustainable buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 141(C).
    14. Zhou, Yuekuan & Zheng, Siqian & Zhang, Guoqiang, 2020. "Machine learning-based optimal design of a phase change material integrated renewable system with on-site PV, radiative cooling and hybrid ventilations—study of modelling and application in five clima," Energy, Elsevier, vol. 192(C).
    15. Jerzy Szyszka, 2022. "From Direct Solar Gain to Trombe Wall: An Overview on Past, Present and Future Developments," Energies, MDPI, vol. 15(23), pages 1-25, November.
    16. Zhou, Yuekuan & Zheng, Siqian & Liu, Zhengxuan & Wen, Tao & Ding, Zhixiong & Yan, Jun & Zhang, Guoqiang, 2020. "Passive and active phase change materials integrated building energy systems with advanced machine-learning based climate-adaptive designs, intelligent operations, uncertainty-based analysis and optim," Renewable and Sustainable Energy Reviews, Elsevier, vol. 130(C).

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