EnergyPlus Thermal Comfort

The integration of a sophisticated building thermal analysis tool with thermal comfort models will allow us to perform an energy analysis on a zone and simultaneously determine if the environmental control strategy will be sufficient for the occupants to be thermally comfortable. This chapter is intended to provide background on thermal comfort, present an overview of state of the art thermal comfort models and present the mathematical models that have been incorporated into Energy Plus.

Background on Thermal Comfort Models

Throughout the last few decades, researchers have been exploring the thermal, physiological and psychological response of people in their environment in order to develop mathematical models to predict these responses. Researchers have empirically debated building occupants' thermal responses to the combined thermal effect of the personal, environmental and physiological variables that influence the condition of thermal comfort.

There are two personal variables that influence the condition of thermal comfort: the thermal resistance of the clothing (Icl), and the metabolic rate (H/ADu). The thermal resistance of the clothing (Icl) is measured in units of "clo." The 1985 ASHRAE Handbook of Fundamentals (3) suggests multiplying the summation of the individual clothing items clo value by a factor of 0.82 for clothing ensembles.


The environmental variables that influence the conditions of thermal comfort include:


  1. Air Temperature (Ta),

  2. Mean Radiant Temperature (Tr),

  3. Relative air velocity (v),

  4. Water vapor pressure in ambient air (Pa)


The Air Temperature (Ta), a direct environmental index, is the dry-bulb temperature of the environment. The Mean Radiant Temperature (Tr) is a rationally derived environmental index defined as the uniform black-body temperature that would result in the same radiant energy exchange as in the actual environment. The Relative air velocity (v) a direct environmental index is a measure of the air motion obtainable via a hot wire or vane anemometers. The Water vapor pressure in ambient air (Pa) is a direct environmental index.


The physiological variables that influence the conditions of thermal comfort include:


  1. Skin Temperature (Tsk),

  2. Core or Internal Temperature (Tcr),

  3. Sweat Rate,

  4. Skin Wettedness (w),

  5. Thermal Conductance (K) between the core and skin.


Where the Skin Temperature (Tsk), the Core Temperature (Tcr) and the Sweat Rate are physiological indices. The Skin Wettedness (w) is a rationally derived physiological index defined as the ratio of the actual sweating rate to the maximum rate of sweating that would occur if the skin were completely wet. One more consideration is important in dealing with thermal comfort - the effect of asymmetrical heating or cooling. This could occur when there is a draft or when there is a radiant flux incident on a person (which is what is of primary interest to us here). Fanger (5) noted that the human regulatory system is quite tolerant of asymmetrical radiant flux. A reasonable upper limit on the difference in mean radiant temperature (Tr) from one direction to the opposing direction is 15_ (1). This limit is lower if there is a high air velocity in the


Mathematical Models for Predicting Thermal Comfort

Many researchers have been exploring ways to predict the thermal sensation of people in their environment based on the personal, environmental and physiological variables that influence thermal comfort. From the research done, some mathematical models that simulate occupants' thermal response to their environment have been developed. Most thermal comfort prediction models use a seven or nine point thermal sensation scale, as in the following tables.


Seven point Thermal Sensation Scale:


3 hot

2 warm

1 slightly warm

0 neutral

-1 slightly cool

-2 cool

-3 cold


Nine point Thermal Sensation Scale:


4 very hot

3 hot

2 warm

1 slightly warm

0 neutral

-1 slightly cool

-2 cool

-3 cold

-4 very cold


The most notable models have been developed by P.O. Fanger (the Fanger Comfort Model), the J. B. Pierce Foundation (the Pierce Two-Node Model), and researchers at Kansas State University (the KSU Two-Node Model). Berglund (6) presents a detailed description of the theory behind these three models.


Note: for all Thermal Comfort reporting: Though the published values for thermal comfort “vote” have a discrete scale (e.g. –3 to +3 or –4 to +4), the calculations in EnergyPlus are carried out on a continuous scale and, thus, reporting may be “off the scale” with specific conditions encountered in the space. This is not necessarily an error in EnergyPlus – rather a different approach that does not take the “limits” of the discrete scale values into account.


The main similarity of the three models is that all three apply an energy balance to a person and use the energy exchange mechanisms along with experimentally derived physiological parameters to predict the thermal sensation and the physiological response of a person due to their environment. The models differ somewhat in the physiological models that represent the human passive system (heat transfer through and from the body) and the human control system (the neural control of shivering, sweating and skin blood flow). The models also differ in the criteria used to predict thermal sensation.

Fanger comfort Model

Fanger's Comfort model was the first one developed. It was published first in 1967 (7) and then in 1972 (2), and helped set the stage for the other two models. The mathematical model developed by P.O. Fanger is probably the most well known of the three models and is the easiest to use because it has been put in both chart and graph form.

Description of the model and algorithm


Fanger developed the model based on the research he performed at Kansas State University and the Technical University of Denmark. Fanger used the seven-point form of a thermal sensation scale along with numerous experiments involving human subjects in various environments. He related the subjects in response to the variables, which influence the condition of thermal comfort. Fanger's model is based upon an energy analysis that takes into account all the modes of energy loss (L) from the body, including: the convection and radiant heat loss from the outer surface of the clothing, the heat loss by water vapor diffusion through the skin, the heat loss by evaporation of sweat from the skin surface, the latent and dry respiration heat loss and the heat transfer from the skin to the outer surface of the clothing. The model assumes that the person is thermally at steady state with his environment.


By determining the skin temperature and evaporative sweat rate that a thermally comfortable person would have in a given set of conditions, the model calculates the energy loss (L). Then, using the thermal sensation votes from subjects at KSU and Denmark, a Predicted Mean Vote (PMV) thermal sensation scale is based on how the energy loss (L) deviates from the metabolic rate (M) in the following form:

Pierce Two-Node Model

The Pierce Two-Node model was developed at the John B. Pierce Foundation at Yale University. The model has been continually expanding since its first publication in 1970 (8). The most recent version on the model appears in the 1986 ASHRAE Transactions (9).


The Pierce model thermally lumps the human body as two isothermal, concentric compartments, one representing the internal section or core (where all the metabolic heat is assumed to be generated and the skin comprising the other compartment). This allows the passive heat conduction from the core compartment to the skin to be accounted for. The boundary line between two compartments changes with respect to skin blood flow rate per unit skin surface area (SKBF in L/h•m2) and is described by alpha – the fraction of total body mass attributed to the skin compartment (13).

Furthermore, the model takes into account the deviations of the core, skin, and mean body temperature weighted by alpha from their respective set points. Thermoregulatory effector mechanisms (Regulatory sweating, skin blood flow, and shivering) are defined in terms of thermal signals from the core, skin and body (13).


The latest version of the Pierce model (15) discusses the concepts of SET* and ET*. The Pierce model converts the actual environment into a "standard environment" at a Standard Effective Temperature, SET*. SET* is the dry-bulb temperature of a hypothetical environment at 50% relative humidity for subjects wearing clothing that would be standard for the given activity in the real environment. Furthermore, in this standard  environment, the same physiological strain, i.e. the same skin temperature and skin wettedness and heat loss to the environment, would exist as in the real environment. The Pierce model also converts the

actual environment into a environment at an Effective Temperature, ET*, that is the dry-bulb temperature of a hypothetical environment at 50% relative humidity and uniform temperature (Ta = MRT) where the subjects would experience the same physiological strain as in the real environment.


In the latest version of the model it is suggested that the classical Fanged PMV be modified by using ET* or SET* instead of the operative temperature. This gives a new index PMV* which is proposed for dry or humid environments. It is also suggested that PMV* is very responsive to the changes in vapor permeation efficiency of the occupants clothing.

Besides PMV*, the Pierce Two Node Model uses the indices TSENS and DISC as predictors of thermal comfort. Where TSENS is the classical index used by the Pierce foundation, and is a function of the mean body temperature. DISC is defined as the relative thermoregulatory strain that is needed to bring about a state of comfort and thermal equilibrium. DISC is a function of the heat stress and heat strain in hot environments and equal to TSENS in cold environments. In summary, the Pierce Model, for our purposes, uses four thermal comfort indices; PMVET-a function of ET*, PMVSET- a function of SET*, TSENS and DISC.

KSU Two-Node Model

The KSU two-node model, developed at Kansas State University, was published in 1977 (10). The KSU model is quite similar to that of the Pierce Foundation. The main difference between the two models is that the KSU model predicts thermal sensation (TSV) differently for warm and cold environment.


The KSU two-node model is based on the changes that occur in the thermal conductance between the core and the skin temperature in cold environments, and in warm environments it is based on changes in the skin wettedness. In this model metabolic heat production is generated in the core which exchanges energy with the environment by respiration and the skin exchanges energy by convection and radiation. In addition, body heat is dissipated through evaporation of sweat and/or water vapor diffusion through the skin. These principles are used in following passive system equations.

Here, control signals, based on set point temperatures in the skin and core, are introduced into passive system equations and these equations are integrated numerically for small time increments or small increments in core and skin temperature. The control signals modulate the thermoregulatory mechanism and regulate the peripheral blood flow, the sweat rate, and the increase of metabolic heat by active muscle shivering. The development of the controlling functions of skin conductance (KS), sweat rate (Esw), and shivering (Mshiv) is based on their correlation with the deviations in skin and core temperatures from their set points.

The KSU model's TSV was developed from experimental conditions in all temperature ranges and from clo levels between .05 clo to 0.7 clo and from activities levels of 1 to 6 mets (6).


  1. ASHRAE, “High Intensity Infrared Radiant Heating”, 1984 system Handbook, American Society of Heating, Refrigerating and Air Conditioning Engineers, Atlanta, GA, Chapter 18, 1984.

  2. Fanger, P.O., Thermal Comfort-Analysis and Applications in Environmental Engineering, Danish Technical Press, Copenhagen, 1970.

  3. ASHRAE, “Physiological Principles for Comfort and Health,” 1985 Fundamental Handbook, American Society of Heating, Refrigerating and Air Conditioning Engineers, Atlanta, GA, Chapter 8, 1985.

  4. Du Bois, D. and E.F., “A Formula to Estimate Approximate Surface Area, if Height and Weight are Known”, Archives of internal Medicine, Vol.17, 1916.

  5. Fanger, P.O., “Radiation and Discomfort”, ASHRAE Journal. February 1986.

  6. Berglund, Larry, “Mathematical Models for Predicting the Thermal Comfort Response of Building Occupants”, ASHRAE Trans., Vol.84, 1978.

  7. Fanger P.O., “Calculation of Thermal Comfort: Introduction of a Basic Comfort Equation”, ASHRE Trans., Vol.73, Pt 2, 1967.

  8. Gagge, A.P., Stolwijk, J. A. J., Nishi, Y., “An Effective Temperature Scale Based on a Simple Model of Human Physiological Regulatory Response”, ASHRAE Trans., Vol.70, Pt 1, 1970.

  9. Gagge, A.P., Fobelets, A.P., Berglund, L. G., “A Standard Predictive Index of Human Response to the Thermal Environment”, ASHRAE Trans., Vol.92, Pt 2, 1986.

  10. Azer, N.Z., Hsu, S., “The prediction of Thermal Sensation from Simple model of Human Physiological Regulatory Response”, ASHRAE Trans., Vol.83, Pt 1, 1977.

  11. Hsu, S., “A Thermoregulatory Model for Heat Acclimation and Some of its Application”, Ph. D. Dissertation, Kansas State University, 1977.

  12. ISO., “Determination of the PMV and PPD Indices and Specification of the Conditions for Thermal Comfort”, DIS 7730, Moderate Thermal Environment, 1983.

  13. Doherty, T.J., Arens, E., “Evaluation of the Physiological Bases of Thermal Comfort Models”, ASHRAE Trans., Vol.94, Pt 1, 1988.

  14. ASHRAE, “Physiological Principles and Thermal Comfort”, 1993 ASHRAE Handbook- Fundamentals, American Society of Heating, Refrigerating and Air Conditioning Engineers, Atlanta, GA, Chapter 8, 1993.

  15. Fountain, Marc.E., Huizenga, Charlie, “A Thermal Sensation Prediction Tool for Use by the Profession”, ASHRAE Trans., Vol.103, Pt 2, 1997.

  16. Int-Hout, D., “Thermal Comfort Calculation / A Computer Model”, ASHRAE Trans., Vol.96, Pt