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A new thermal comfort approach comparing adaptive and PMV models

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  • Orosa, José A.
  • Oliveira, Armando C.

Abstract

In buildings with heating, ventilation, and air-conditioning (HVAC), the Predicted Mean Vote index (PMV) was successful at predicting comfort conditions, whereas in naturally ventilated buildings, only adaptive models provide accurate predictions. On the other hand, permeable coverings can be considered as a passive control method of indoor conditions and, consequently, have implications in the perception of indoor air quality, local thermal comfort, and energy savings. These energy savings were measured in terms of the set point temperature established in accordance with adaptive methods. Problems appear when the adaptive model suggests the same neutral temperature for ambiences with the same indoor temperature but different relative humidities. In this paper, a new design of the PMV model is described to compare the neutral temperature to real indoor conditions. Results showed that this new PMV model tends to overestimate thermal neutralities but with a lower value than Fanger’s PMV index. On the other hand, this new PMV model considers indoor relative humidity, showing a clear differentiation of indoor ambiences in terms of it, unlike adaptive models. Finally, spaces with permeable coverings present indoor conditions closer to thermal neutrality, with corresponding energy savings.

Suggested Citation

  • Orosa, José A. & Oliveira, Armando C., 2011. "A new thermal comfort approach comparing adaptive and PMV models," Renewable Energy, Elsevier, vol. 36(3), pages 951-956.
    • Handle: RePEc:eee:renene:v:36:y:2011:i:3:p:951-956
    DOI: 10.1016/j.renene.2010.09.013
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    References listed on IDEAS

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    1. Orosa, José A. & Oliveira, Armando C., 2009. "Hourly indoor thermal comfort and air quality acceptance with passive climate control methods," Renewable Energy, Elsevier, vol. 34(12), pages 2735-2742.
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    Cited by:

    1. Zhang, Sheng & Lu, Yalin & Niu, Dun & Lin, Zhang, 2022. "Energy performance index of air distribution: Thermal utilization effectiveness," Applied Energy, Elsevier, vol. 307(C).
    2. Iasmin Lourenço Niza & Evandro Eduardo Broday, 2022. "An Analysis of Thermal Comfort Models: Which One Is Suitable Model to Assess Thermal Reality in Brazil?," Energies, MDPI, vol. 15(15), pages 1-19, July.
    3. Ke, Wei & Ji, Jie & Zhang, Chengyan & Wang, Chuyao & Xie, Hao & Tian, Xinyi, 2023. "A seasonal experimental study on a novel CdTe based multi-layer PV ventilated window system integrated with PCM under different operating modes," Energy, Elsevier, vol. 285(C).
    4. Minsu Lee & Jaemin Jeong & Jaewook Jeong & Jaehyun Lee, 2021. "Exploring Fatalities and Injuries in Construction by Considering Thermal Comfort Using Uncertainty and Relative Importance Analysis," IJERPH, MDPI, vol. 18(11), pages 1-30, May.
    5. Enescu, Diana, 2017. "A review of thermal comfort models and indicators for indoor environments," Renewable and Sustainable Energy Reviews, Elsevier, vol. 79(C), pages 1353-1379.

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