A data-driven approach to defining acceptable temperature ranges in buildings

Abstract Current thermal comfort standards use Predicted Mean Vote (PMV) classes as the compliance criteria despite previous critiques. The implicit assumption is that a narrower PMV range ensures higher thermal acceptability among building occupants. However, our analysis of a global database of thermal comfort field studies demonstrates that PMV classes are not appropriate design compliance criteria, and reinforces the need for a new and robust approach to thermal comfort compliance assessment. We compared two statistical methods to derive acceptable temperature ranges from occupant responses applied one to the ASHRAE Global Thermal Comfort Database II. Derived acceptable temperature ranges in real buildings (7.4K-12.2 K) using this new method are wider than the current standards mandate (2 K-6K). Our findings support the call for a relaxation of suggested temperature ranges in thermal comfort standards so as to minimize unnecessary space conditioning. The proposed data-driven statistical methods to determine temperature design compliance criteria are viewed as an important step forward in the age of continuous and pervasive monitoring and the associated large databases of building comfort measurements.

[1]  J. F. Nicol,et al.  The validity of ISO-PMV for predicting comfort votes in every-day thermal environments , 2002 .

[2]  P. O. Fanger,et al.  Thermal comfort: analysis and applications in environmental engineering, , 1972 .

[3]  Michael A. Humphreys,et al.  ADAPTIVE THERMAL COMFORT AND SUSTAINABLE THERMAL STANDARDS FOR BUILDINGS , 2002 .

[4]  Bin Cao,et al.  Human metabolic rate and thermal comfort in buildings: The problem and challenge , 2018 .

[5]  Fergus Nicol,et al.  Twentieth century standards for thermal comfort: promoting high energy buildings , 2010 .

[6]  Joyce Kim,et al.  Personal comfort models: Predicting individuals' thermal preference using occupant heating and cooling behavior and machine learning , 2018 .

[7]  F. Nicol.  Adaptive thermal comfort standards in the hot–humid tropics , 2004 .

[8]  Joyce Kim,et al.  Personal comfort models – A new paradigm in thermal comfort for occupant-centric environmental control , 2018 .

[9]  F. Alfano,et al.  The role of measurement accuracy on the thermal environment assessment by means of PMV index , 2011 .

[10]  N. Wong,et al.  Thermal comfort for naturally ventilated houses in Indonesia , 2004 .

[11]  Hui Zhang,et al.  Air temperature thresholds for indoor comfort and perceived air quality , 2011 .

[12]  Hui Zhang,et al.  Energy-efficient comfort with a heated/cooled chair: Results from human subject tests , 2015 .

[13]  Hui Zhang,et al.  A review of the corrective power of personal comfort systems in non-neutral ambient environments , 2015 .

[14]  Borong Lin,et al.  The underlying linkage between personal control and thermal comfort: Psychological or physical effects? , 2016 .

[15]  Maohui Luo,et al.  Indoor climate experience, migration, and thermal comfort expectation in buildings , 2018, Building and Environment.

[16]  Nyuk Hien Wong,et al.  Thermal comfort in classrooms in the tropics , 2003 .

[17]  Thomas Parkinson,et al.  Thermal pleasure in built environments: physiology of alliesthesia , 2015 .

[18]  Richard de Dear,et al.  Residential adaptive comfort in a humid subtropical climate—Sydney Australia , 2018 .

[19]  F. Nicol,et al.  Derivation of the adaptive equations for thermal comfort in free-running buildings in European standard EN15251 , 2010 .

[20]  Gail Brager,et al.  Operable windows, personal control and occupant comfort. , 2004 .

[21]  Michael A. Humphreys,et al.  New standards for comfort and energy use in buildings , 2009 .

[22]  Michael A. Humphreys,et al.  Field Studies of Indoor Thermal Comfort and the Progress of the Adaptive Approach , 2007 .

[23]  Thomas Parkinson,et al.  Thermal pleasure in built environments: alliesthesia in different thermoregulatory zones , 2016 .

[24]  Edward Arens,et al.  Indoor Environmental Quality ( IEQ ) Title Are ' Class A ' temperature requirements realistic or desirable ? , 2009 .

[25]  Yingxin Zhu,et al.  A field study on thermal comfort and air-conditioning energy use in an office building in Guangzhou , 2018, Energy and Buildings.

[26]  Richard de Dear,et al.  Nonlinear relationships between individual IEQ factors and overall workspace satisfaction , 2012 .

[27]  Dimitris Theodossopoulos,et al.  Does a neutral thermal sensation determine thermal comfort? , 2018 .

[28]  R. Dear,et al.  Thermal adaptation in the built environment: a literature review , 1998 .

[29]  Y Zhu,et al.  Progress in thermal comfort research over the last twenty years. , 2013, Indoor air.

[30]  Philip C.H. Yu,et al.  Energy use in commercial buildings in Hong Kong , 2001 .

[31]  B. Kingma,et al.  Beyond the classic thermoneutral zone , 2014, Temperature.

[32]  A. Hwang.  [Thermal comfort]. , 1990, Taehan kanho. The Korean nurse.

[33]  Hyojin Kim,et al.  Development of the ASHRAE Global Thermal Comfort Database II , 2018, Building and Environment.

[34]  Burcin Becerik-Gerber,et al.  A knowledge based approach for selecting energy-aware and comfort-driven HVAC temperature set points , 2014 .

[35]  van J Joost Hoof,et al.  Forty years of Fanger’s model of thermal comfort: comfort for all? , 2008 .

[36]  Maohui Luo,et al.  Thermal comfort evaluated for combinations of energy-efficient personal heating and cooling devices , 2018, Building and Environment.

[37]  Richard de Dear,et al.  Individual difference in thermal comfort: A literature review , 2018, Building and Environment.

[38]  Mateja Dovjak,et al.  Challenging the assumptions for thermal sensation scales , 2017 .

[39]  Gail Brager,et al.  A Comparison of Methods for Assessing Thermal Sensation and Acceptability in the Field , 1993 .

[40]  Gail Brager,et al.  Analysis of the accuracy on PMV – PPD model using the ASHRAE Global Thermal Comfort Database II , 2019, Building and Environment.

[41]  Standard Ashrae.  Thermal Environmental Conditions for Human Occupancy , 1992 .

[42]  Hui Zhang,et al.  EXTENDING AIR TEMPERATURE SETPOINTS: SIMULATED ENERGY SAVINGS AND DESIGN CONSIDERATIONS FOR NEW AND RETROFIT BUILDINGS , 2015 .

[43]  Won-Hwa Hong,et al.  Determination of an acceptable comfort zone for apartment occupants in South Korea: An empirical analysis of cooling operation , 2017 .

[44]  Gail Brager,et al.  Developing an adaptive model of thermal comfort and preference , 1998 .

[45]  Ingvar Holmér,et al.  Personal factors in thermal comfort assessment: clothing properties and metabolic heat production , 2002 .

[46]  Darryl Dickerhoff,et al.  Using footwarmers in offices for thermal comfort and energy savings , 2015 .

[47]  Burcin Becerik-Gerber,et al.  An online learning approach for quantifying personalized thermal comfort via adaptive stochastic modeling , 2015 .