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Influence of Three Dynamic Predictive Clothing Insulation Models on Building Energy Use, HVAC Sizing and Thermal Comfort

Author

Listed:
  • Kwang Ho Lee

    (Department of Architectural Engineering, Hanbat National University, San 16-1, Dukmying-Dong, Yusung-Gu, Daejeon 305-719, Korea)

  • Stefano Schiavon

    (Center for the Built Environment, University of California at Berkeley, 390 Wurster Hall, Berkeley, CA 94720, USA)

Abstract

In building energy simulation, indoor thermal comfort condition, energy use and equipment size are typically calculated based on the assumption that the clothing insulation is equal to a constant value of 0.5 clo during the cooling season and 1.0 clo during the heating season. The assumption is not reflected in practice and thus it may lead to errors. In reality, occupants frequently adjust their clothing depending on the thermal conditions, as opposed to the assumption of constant clothing values above, indicating that the clothing insulation variation should be captured in building simulation software to obtain more reliable and accurate results. In this study, the impact of three newly developed dynamic clothing insulation models on the building simulation is quantitatively assessed using the detailed whole-building energy simulation program, EnergyPlus version 6.0. The results showed that when the heating ventilation and air conditioning system (HVAC) is controlled based on indoor temperature the dynamic clothing models do not affect indoor operative temperatures, energy consumption and equipment sizing. When the HVAC is controlled based on the PMV model the use of a fixed clothing insulation during the cooling (0.5 clo) and heating (1.0 clo) season leads to the incorrect estimation of the indoor operative temperatures, energy consumption and equipment sizing. The dynamic clothing models significantly ( p < 0.0001) improve the ability of energy simulation tools to assess thermal comfort. The authors recommend that the dynamic clothing models should be implemented in dynamic building energy simulation software such as EnergyPlus.

Suggested Citation

  • Kwang Ho Lee & Stefano Schiavon, 2014. "Influence of Three Dynamic Predictive Clothing Insulation Models on Building Energy Use, HVAC Sizing and Thermal Comfort," Energies, MDPI, vol. 7(4), pages 1-18, March.
  • Handle: RePEc:gam:jeners:v:7:y:2014:i:4:p:1917-1934:d:34490
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    Citations

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    Cited by:

    1. Georgios Martinopoulos & Vasiliki Kikidou & Dimitrios Bozis, 2018. "Energy Assessment of Building Physics Principles in Secondary Education Buildings," Energies, MDPI, vol. 11(11), pages 1-15, October.
    2. Kyungsoo Lee & Haneul Choi & Joon-Ho Choi & Taeyeon Kim, 2019. "Development of a Data-Driven Predictive Model of Clothing Thermal Insulation Estimation by Using Advanced Computational Approaches," Sustainability, MDPI, vol. 11(20), pages 1-18, October.
    3. Diana Enescu, 2019. "Models and Indicators to Assess Thermal Sensation Under Steady-State and Transient Conditions," Energies, MDPI, vol. 12(5), pages 1-43, March.

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