Personal comfort models – A new paradigm in thermal comfort for occupant-centric environmental control

Kim, Joyce; Schiavon, Stefano; Brager, Gail

doi:10.1016/j.buildenv.2018.01.023

Cited by 358 publications

(176 citation statements)

References 66 publications

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“…air velocity, clothing insulation and metabolic activity). Another alternative is to use personal comfort models [44] which predict individual thermal comfort responses rather than the average response of a larger population e.g. a floor or a whole building.…”

Section: Discussionmentioning

confidence: 99%

Analysis of the accuracy on PMV – PPD model using the ASHRAE Global Thermal Comfort Database II

Cheung

Schiavon

Parkinson

et al. 2019

Building and Environment

Self Cite

326

117

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The predicted mean vote (PMV) and predicted percentage of dissatisfied (PPD) are the most widely used thermal comfort indices. Yet, their performance remains a contested topic. The ASHRAE Global Thermal Comfort Database II, the largest of its kind, was used to evaluate the prediction accuracy of the PMV/PPD model. We focused on: (i) the accuracy of PMV in predicting both observed thermal sensation (OTS) or observed mean vote (OMV) and (ii) comparing the PMV-PPD relationship with binned OTS -observed percentage of unacceptability (OPU). The accuracy of PMV in predicting OTS was only 34%, meaning that the thermal sensation is incorrectly predicted two out of three times. PMV had a mean absolute error of one unit on the thermal sensation scale and its accuracy decreased towards the ends of the thermal sensation scale. The accuracy of PMV was similarly low for air-conditioned, naturally ventilated and mixed-mode buildings. In addition, the PPD was not able to predict the dissatisfaction rate. If the PMV model would perfectly predict thermal sensation, then PPD accuracy is higher close to neutrality but it would overestimate dissatisfaction by approximately 15-25% outside of it. Furthermore, PMV-PPD accuracy varied strongly between ventilation strategies, building types and climate groups. These findings demonstrate the low prediction accuracy of the PMV-PPD model, indicating the need to develop high prediction accuracy thermal comfort models. For demonstration, we developed a simple thermal prediction model just based on air temperature and its accuracy, for this database, was higher than PMV.

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Section: Discussionmentioning

confidence: 99%

Analysis of the accuracy on PMV – PPD model using the ASHRAE Global Thermal Comfort Database II

Cheung

Schiavon

Parkinson

et al. 2019

Building and Environment

Self Cite

326

117

View full text Add to dashboard Cite

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“…After reviewing the literatures of thermal comfort and public health, we propose the hypothesis that there might be some correlations 20 between the calculated minimum mortality temperature (MMT) in the public health area and the neutral temperature in the thermal comfort area. Such hypothesis is mainly based on the two findings:…”

Section: Review Of the Data And Models On Mortality And Ambient Tempementioning

confidence: 99%

“…[15,18,19]. Kim, et al [20] designed various subjective rating scales based different objectives and application scenarios; Wang, et al [21] reviewed the challenges facing to obtain correct subjective evaluations of indoor environments; and Zangheri, et al [22] presented the costs associated with measurement instrument and labor forces to conduct an accurate and large scale thermal comfort assessment. All of the difficulties have led to limited good quality data available from the fields [23].…”

Section: Introductionmentioning

confidence: 99%

Review of thermal comfort infused with the latest big data and modeling progresses in public health

Jiang

Luo

Wang

et al. 2019

Building and Environment

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Thermal environment is important for both occupants' comfort and health. Previously, the impacts of thermal environment were explored in the areas of thermal comfort and public health separately. This paper aims to bridge both disciplines by examining the correlation between comfort temperature and Minimum Mortality Temperature (MMT), which is a key index quantifying the association of health and weather temperature, through literature review and data-driven approach. It was found that the MMT data obtained from the public health area are generally in good agreement with the thermal neutral temperatures from the comfort perspective. The MMT data range from 17.2 o C to 30 o C, which are similar to the thermal neutral temperatures ranging from 19.5 o C to 30 o C based on the global field tests. Moreover, the MMT data demonstrate the potential to capture some complex distribution patterns of the field comfort data.The introduction of the health-temperature data could assist the intensive field experiments and modeling efforts and complement the thermal comfort dataset, which suffers from the problems of limited sample size. Some discrepancies between the two datasets were identified as well. The contextual factors other than the 2

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“…The characteristics of these models and their use can predict the indoor air temperature and the average vote prediction index for energy management. The works of Kim et al [3] give a new approach to thermal comfort modeling that predicts the response to an individual's thermal comfort, instead of the average response of a large population. The data collected in the everyday environment of individuals makes it possible to understand the comfort requirements of these individuals.…”

Section: Introductionmentioning

confidence: 99%

Determination of Parameters Influencing Thermal Comfort in a Building

Ouédraogo¹

2018

SJEE

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This paper presents a theoretical and an experimental study on the determination of thermal phase shift time and damping factors of building walls. The work consisted in evaluating the thermal comfort in a building. This study is a contribution to put in place a thermal regulation in Burkina Faso, a country with a dry tropical climate. This regulation will, in its application, reduce the energy consumption related to air conditioning in buildings. To do this, we theoretically determine the parameters influencing this comfort using the admittance method. This method makes it possible to analyze the thermal response of a building to a periodic energy demand. It is based on the modeling of the building component by the quadrupole method resulting from the writing of the thermal problem in the form of transfer matrix products. The principle is to link the flows and temperatures of both sides of a homogeneous wall through the equation of heat and the Fourier transform. The calculation method is validated by experimental results. For simple sheet walls based on their compositions, damping factors range from about 37.9% to 79.7% and thermal phase shift time from about 3.9 hours to 7.4 hours. However, the values of these parameters are better when the walls are double-sheeted, the maximum value of the damping factor is 11.5% and the minimum value of the thermal phase shift time is 9.7 h. The values of Mean Bias Difference (MBD) and Root Mean Square Difference (RMSD) show that the theoretical and experimental results are quite concordant. The admittance method can be used to evaluate the performance of building walls.

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Personal comfort models – A new paradigm in thermal comfort for occupant-centric environmental control

Cited by 358 publications

References 66 publications

Analysis of the accuracy on PMV – PPD model using the ASHRAE Global Thermal Comfort Database II

Analysis of the accuracy on PMV – PPD model using the ASHRAE Global Thermal Comfort Database II

Review of thermal comfort infused with the latest big data and modeling progresses in public health

Determination of Parameters Influencing Thermal Comfort in a Building

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