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Comparative Analysis of Indoor Thermal Comfort in a Residential Building by Applying Dynamic Clothing Insulation

동적 착의량 기반 열환경 제어에 따른 주거환경 열쾌적 분석

  • Received : 2021.01.10
  • Accepted : 2021.03.24
  • Published : 2021.04.30

Abstract

The purpose of this study is to confirm the necessity and significance of applying a dynamic clothing insulation for controlling the thermal environment. For this purpose, the comparative analysis of indoor thermal comfort in the residential building was conducted with three different control methods: 1) DBT (dry-bulb temperature)-based control, 2) PMV (predicted mean vote)-based controls reflecting the fixed clothing insulation, 3) PMV-based control reflecting the dynamic clothing insulation. DesignBuilder was employed for a residential building modeling and the thermal comfort analysis which was accessed with PMV and PPD (predicted percentage dissatisfied) indicators. As a result, the PMV-based control applying the dynamic clothing insulation satisfied the comfort ranges of the PMV and PPD at all times regardless of the season. On the other hand, in the case of the DBT-based control, the average PMV value was out of the comfort range in both seasons, and the PPD value was more than twice that of the PMV-based control reflecting the dynamic clothing insulation. In addition, PMV-based control reflecting fixed clothing insulation resulted in a slightly cold condition in the morning and at night in both seasons as presenting PMV values below -0.5 and PPD values over 10%. In conclusion, from this study, the possibility was confirmed that the PMV-based control reflecting dynamic clothing insulation can provide a comfortable thermal environment for the occupants. Therefore, it is necessary to apply the accurate value of the clothing insulation in order to comfortably control the thermal environment, and a follow-up research should be conducted to develop a prediction model of the real-time clothing insulation.

Keywords

References

  1. Altomonte, S., Schiavon, S., Kent, M., & Brager, G. (2019). Indoor environmental quality and occupant satisfaction in green-certified buildings. Building Research and Information, 47, 255-274. https://doi.org/10.1080/09613218.2018.1383715
  2. ASHRAE 55, (2017). Thermal environmental conditions for human occupancy. ASHRAE: Atlanta, USA.
  3. ASHRAE Guideline 10. (2011). Interactions Affecting the Achievement of Acceptable Indoor Environments. ASHRAE: Atlanta, USA.
  4. ASHRAE Handbook Fundamentals. (2017). In Thermal Comfort, ASHRAE, Atlanta.
  5. Choi, E.J., Yoo, Y., Park, B.R., Choi, Y.J., & Moon, J.W. (2020). Development of Occupant Pose Classification Model Using Deep Neural Network for Personalized Thermal Conditioning, Energies 13(1).
  6. de Carvalho, P.M., da Silva, M.G., & Ramos, J.E. (2013). Influence of weather and indoor climate on clothing of occupants in naturally ventilated school buildings. Building and environment, 59, 38-46. https://doi.org/10.1016/j.buildenv.2012.08.005
  7. Fanger, P.O. (1970). Thermal comfort. Analysis and applications in environmental engineering. Copenhagen: Danish Technical Press.
  8. Gao, J., Wang, Y., & Wargocki, P. (2015). Comparative analysis of modified PMV models and SET models to predict human thermal sensation in naturally ventilated buildings. Building and Environment, 92, 200-208. https://doi.org/10.1016/j.buildenv.2015.04.030
  9. Haldi, F., & Robinson, D. (2011). Modelling occupants' personal characteristics for thermal comfort prediction. International journal of biometeorology, 55(5), 681-694. https://doi.org/10.1007/s00484-010-0383-4
  10. Hawila, A., Merabtine, A., Chemkhi, M., Bennacer, R., & Troussier, N. (2018). An analysis of the impact of PMV-based thermal comfort control during heating period: A case study of highly glazed room. Journal of Building Engineering, 20, 353-366. https://doi.org/10.1016/j.jobe.2018.08.010
  11. Humphreys, M.A. (1974). Classroom Temperature, Clothing and Thermal Comfort--A Study of Secondary School Children in Summertime. Building Research Establishment Current Paper 22/74. Reprinted from The Building Services Engineer (JIHVE), 41, 191-202.
  12. ISO 18523-2. (2018). Energy performance of buildings - Schedule and condition of building, zone and space usage for energy calculation - Part 2: Residential buildings, ISO.
  13. ISO 7730. (2005). Ergonomics of the thermal environment - Analytical determination and interpretation of thermal comfort using calculation of the PMV and PPD indices and local thermal comfort criteria, ISO.
  14. Kosonen, R., & Tan, F. (2004). Assessment of productivity loss in air-conditioned buildings using PMV index. Energy and Buildings, 36, 987-993. https://doi.org/10.1016/j.enbuild.2004.06.021
  15. Licina, V.F., Cheung, T., Zhang, H., De Dear, R., Parkinson, T., Arens, E., ... & Li, P. (2018). Development of the ASHRAE global thermal comfort database II. Building and Environment, 142, 502-512. https://doi.org/10.1016/j.buildenv.2018.06.022
  16. Liu, W., Yang, D., Shen, X., & Yang, P. (2018). Indoor clothing insulation and thermal history: a clothing model based on logistic function and running mean outdoor temperature. Building and Environment, 135, 142-152. https://doi.org/10.1016/j.buildenv.2018.03.015
  17. Ministry of Environment. (2015). Plan for Indoor Air Quality Management(2015-2019).
  18. Moon, J.W. (2012). Performance of ANN-based predictive and adaptive thermal-control methods for disturbances in and around residential buildings, Building and Environment 48, 15-26. https://doi.org/10.1016/j.buildenv.2011.06.005
  19. Ngarambe, J., Yun, G. Y., & Kim, G. (2019). Prediction of indoor clothing insulation levels: A deep learning approach. Energy and Buildings, 202, 109402. https://doi.org/10.1016/j.enbuild.2019.109402
  20. Salata, F., Golasi, I., Ciancio, V., & Rosso, F. (2018). Dressed for the season: Clothing and outdoor thermal comfort in the Mediterranean population. Building And Environment, 146, 50-63. https://doi.org/10.1016/j.buildenv.2018.09.041
  21. Schiavon, S., & Lee, K.H. (2012 December). Predictive clothing insulation model based on outdoor air and indoor operative temperatures. In Proceedings of 7th Windsor Conference: The changing context of comfort in an unpredictable world (Vol. 1, No. 1, pp. 1-14).
  22. Spengler, J.D. (2012). Climate change, indoor environments, and health. Indoor Air, 22, 89-95. https://doi.org/10.1111/j.1600-0668.2012.00768.x
  23. Statistics Korea Time Use Survey. (2019). Time Use Survey Results in 2019, Statistics Korea, South Korea.
  24. Vecchi, R. D., Lamberts, R., & Candido, C.M. (2017). The role of clothing in thermal comfort: how people dress in a temperate and humid climate in Brazil. Ambiente Construido, 17(1), 69-81. https://doi.org/10.1590/s1678-86212017000100124
  25. Wang, Z., Cao, B., Ji, W., & Zhu, Y. (2020). Study on clothing insulation distribution between half-bodies and its effects on thermal comfort in cold environments. Energy and Buildings, 211, 109796. https://doi.org/10.1016/j.enbuild.2020.109796
  26. Wu, T., Cao, B., & Zhu, Y. (2018). A field study on thermal comfort and air-conditioning energy use in an office building in Guangzhou. Energy and Buildings, 168, 428-437. https://doi.org/10.1016/j.enbuild.2018.03.030
  27. Ministry of Land, Infrastructure and Transport. (2020). Construction standards for energy-saving eco-friendly housing. Koream MOLIT, 2020
  28. De Carli, M., Olesen, B., Zarrella, A. & Zecchin, R. (2007). People's clothing behaviour according to external weather and indoor environment. Building and Environment. 42. 3965-3973. https://doi.org/10.1016/j.buildenv.2006.06.038