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Operating optimization for improved energy consumption of a TAC system affected by nighttime thermal loads of building envelopes

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  • Mao, Ning
  • Pan, Dongmei
  • Song, Mengjie
  • Li, Zhao
  • Xu, Yingjie
  • Deng, Shiming

Abstract

Task/ambient air conditioning (TAC) system is reported to be an energy efficient technology with available methods to control thermal comfortable level for sleeping environments. Better performance in energy saving for TAC systems in sleeping environment has been demonstrated in previous studies. However, it should be noticed that the building envelope thermal load affects the indoor thermal environment and operation of the air conditioning system due to the heat transfer through the envelope. The variation of indoor thermal environment will directly affect the performance of the TAC system, especially the set of operation parameters. Therefore, an optimization study on the TAC system operation considering the effects of envelope thermal load was carried out in this paper. Firstly, a full factorial design method was used to construct the simulation case matrix. Secondly, the models of the energy consumption and thermal comfort were established using operating parameters and envelope thermal load. Thirdly, comfort surface and comfort lines were obtained to calculate the optimum operating parameters at which the energy consumption was at the lowest. Finally, the energy consumption at the optimum status was calculated. The results show that the TAC system at the optimum status can save 1.4 to 1.7 kWh each night.

Suggested Citation

  • Mao, Ning & Pan, Dongmei & Song, Mengjie & Li, Zhao & Xu, Yingjie & Deng, Shiming, 2017. "Operating optimization for improved energy consumption of a TAC system affected by nighttime thermal loads of building envelopes," Energy, Elsevier, vol. 133(C), pages 491-501.
    • Handle: RePEc:eee:energy:v:133:y:2017:i:c:p:491-501
    DOI: 10.1016/j.energy.2017.04.106
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    Citations

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    Cited by:

    1. Shen, Yuxuan & Pan, Yue, 2023. "BIM-supported automatic energy performance analysis for green building design using explainable machine learning and multi-objective optimization," Applied Energy, Elsevier, vol. 333(C).
    2. Mao, Ning & Song, Mengjie & Pan, Dongmei & Deng, Shiming, 2018. "Comparative studies on using RSM and TOPSIS methods to optimize residential air conditioning systems," Energy, Elsevier, vol. 144(C), pages 98-109.
    3. Jiying Liu & Shengwei Zhu & Moon Keun Kim & Jelena Srebric, 2019. "A Review of CFD Analysis Methods for Personalized Ventilation (PV) in Indoor Built Environments," Sustainability, MDPI, vol. 11(15), pages 1-33, August.
    4. Hernández-Romero, Ilse María & Fuentes-Cortés, Luis Fabián & Nápoles-Rivera, Fabricio, 2019. "Conditions accommodating a dominant stakeholder in the design of renewable air conditioning systems for tourism complexes," Energy, Elsevier, vol. 172(C), pages 808-822.
    5. Ping Wang & Guangcai Gong & Yan Zhou & Bin Qin, 2018. "A Simplified Calculation Method for Building Envelope Cooling Loads in Central South China," Energies, MDPI, vol. 11(7), pages 1-18, July.
    6. Song, Mengjie & Xu, Xiangguo & Mao, Ning & Deng, Shiming & Xu, Yingjie, 2017. "Energy transfer procession in an air source heat pump unit during defrosting," Applied Energy, Elsevier, vol. 204(C), pages 679-689.

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