A new thermal comfort approach comparing adaptive and PMV

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Renewable Energy 36 (2011) 951e956
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Renewable Energy
journal homepage: www.elsevier .com/locate/renene
A new thermal comfort approach comparing adaptive and PMV models
José A. Orosa a,*, Armando C. Oliveira b
aUniversidade da Coruña, Departamento de Energía y P. M. Paseo de Ronda, n�:51, 15011. A Coruña, Spain
bUniversidade do Porto, Faculdade de Engenharia, New Energy Tec. Unit. Rua Dr Roberto Frias, 4200-465 Porto, Portugal
a r t i c l e i n f o
Article history:
Received 3 July 2009
Accepted 14 September 2010
Available online 6 October 2010
Keywords:
Neutral temperature
Thermal comfort
Energy
Passive methods
New approach
* Corresponding author. Tel.: þ34 981 167000 4320
E-mail address: jaorosa@udc.es (J.A. Orosa).
0960-1481/$ e see front matter � 2010 Elsevier Ltd.
doi:10.1016/j.renene.2010.09.013
a b s t r a c t
In buildings with heating, ventilation, and air-conditioning (HVAC), the Predicted Mean Vote index
(PMV) was successful at predicting comfort conditions, whereas in naturally ventilated buildings, only
adaptive models provide accurate predictions. On the other hand, permeable coverings can be consid-
ered as a passive control method of indoor conditions and, consequently, have implications in the
perception of indoor air quality, local thermal comfort, and energy savings. These energy savings were
measured in terms of the set point temperature established in accordance with adaptive methods.
Problems appear when the adaptive model suggests the same neutral temperature for ambiences with
the same indoor temperature but different relative humidities. In this paper, a new design of the PMV
model is described to compare the neutral temperature to real indoor conditions. Results showed that
this new PMV model tends to overestimate thermal neutralities but with a lower value than Fanger’s
PMV index. On the other hand, this new PMV model considers indoor relative humidity, showing a clear
differentiation of indoor ambiences in terms of it, unlike adaptive models. Finally, spaces with permeable
coverings present indoor conditions closer to thermal neutrality, with corresponding energy savings.
� 2010 Elsevier Ltd. All rights reserved.
1. Introduction
It is widely believed that people can acclimatise themselves to
thermal environments, and that comfort conditions vary in
different parts of the world, depending on the outdoor climate at
the relevant place. International thermal comfort standards are
almost exclusively based on theoretical analyses of human heat
exchange and data obtained in climatic chambers. On the other
hand, the ASHRAE Standard 55-2004 defines an adaptive model as
one that relates indoor design temperatures, or acceptable
temperature ranges, to outdoor climate. As a result, in current
thermal comfort research, there is a lack of agreement between
adaptive and heat balance models, when they are compared [1]. To
illustrate this point, Humphreys [2] and de Dear and Auliciems [3]
indicated in their studies conducted around the world that the
agreement between the expression of thermal comfort proposed by
ASHRAE 55-2004 [4,5] and ISO 7730 [6] and thermal sensation is
not good [7]. One possible explanation for this clear difference
could be the context, because subjects living in HVAC spaces expect
homogeneous and cool temperatures, whereas subjects living in
natural ventilation conditions have a larger thermal comfort range
than the one shown in the latest standards.
; fax: þ34 813 5292 5084.
All rights reserved.
On the other hand, recent studies [8e11] have shown that mois-
ture transfer between indoor air and moisture buffering wall mate-
rials can generally improve indoor humidity conditions [7,12,13]. In
particular, these studies showed the potential for hygroscopic
structures made of wood-based materials to moderate variations in
indoor relative humidity. Furthermore, permeable coverings can
change indoor temperature by changing heat transfer through the
walls [14,15]. This effect was recognised [16e18] as a passive control
method of indoor conditions and, consequently, has implications in
indoor air quality, local thermal comfort, and energy savings.
These energy savings are calculated with the set point temper-
ature proposed by adaptive models, that depends on outdoor
climate and, indirectly, takes into account other effects that PMV
indices do not consider [19,20]. Problems appear when internal
coverings change wall materials, moisture contents and, especially,
the relative humidity of indoor ambiences. These effects must be
taken into account in calculating set point values, while adaptive
models only consider the effect of indoor air temperature. In this
paper, a new PMV model (PMVn) was developed to determine the
real effect of internal coverings on neutral temperature and, as
a result, on possible energy savings for a new set point temperature.
2. Methodology
Themethodology followedwasbased inmeasurements of indoor
and outdoor conditions in office buildings, and the definition of
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Table 1
Thermal sensation scale.
Thermal sensation
þ3 hot
þ2 warm
þ1 slightly warm
0 neutral
�1 slightlycool
�2 cool
�3 cold
J.A. Orosa, A.C. Oliveira / Renewable Energy 36 (2011) 951e956952
a new simplified predicted mean vote PMVn for each particular
characteristics of the office buildings, like internal coverings, in
accordancewith the simplifiedmodels proposedbyASHRAE. Finally,
this new model was compared with adaptive models, when pre-
dicting the neutral temperature in each different indoor ambience.
An advantage of this new model is that it will let us easily measure
indoor thermal comfort in ambiences during long periods of time.
2.1. Buildings
The office buildings covered by this study are located in the area
of A Coruña (Spain) and are presently naturally ventilated. All of
them having the same orientation, are located in the lower floors of
the building and present the same wall structure, indoor activity
and two zones that we called workers’ and clients’ zone, respec-
tively. Workers’ zone is the area where employees serve the clients
located in the clients’ zone, with both zones separated by a safety
glass.
The offices studied have the same wall structure formed, from
outside to inside, by: an external covering, concrete, brick, air
barrier, polystyrene, brick, concrete, and internal covering. The only
difference among them is the internal covering, with very different
permeability characteristics used. For example, we can find
permeable internal coverings such as paper, plaster or wood, or
impermeable internal coverings like paints, plastic, or glass.
2.2. Indoor and outdoor conditions
The measuring equipment was composed by a thermal comfort
module and data loggers. The thermal comfort module includes
transducers of mean radiant temperature, air speed, temperature
and relative humidity, needed to calculate Fanger’s PMV index.
Tinytag Plus 2 dual channel data-loggers with thermistors and
capacitive sensors were also installed to record temperature and
relative humidity values with accuracies of �0.2 �C and �3% RH,
respectively. These data loggers recorded temperature and relative
humidity of twenty-five office buildings during the summer season,
with a sampling frequency ranging from five to ten minutes.
As adaptive comfort models use the outdoor temperature as an
input parameter, outdoor climate was obtained from meteorolog-
ical stations [21] located near the town of A Coruña. Meteorological
variables such as temperature, relative humidity, and wind speed,
among others, were recorded with a frequency of five to ten
minutes.
2.3. Thermal comfort models
This section presents the different thermal comfort models. The
first model is the one defined by ASHRAE, basedon the human
energy balance. Because this model needs many input data, it was
simplified as a function of temperature and partial vapour pressure
by some researchers. The second method proposed by most
authors is a curve fit of a survey. The last method is an adaptive
model, that is based in outdoor and indoor conditions.
2.3.1. ISO PMV model
To define the indoor PMV index a thermal comfort datalogger
INNOVA 1221 is frequently applied. This module records the vari-
ables in accordance with ISO 7730 specifications. If we need to
simultaneously measure indoor thermal comfort in ambiences
during long intervals of time, a new model must be identified. This
model must give us simultaneous PMV indices in different build-
ings as a function of two variables, such as temperature and relative
humidity, that could be measured with data loggers.
Themodel selectedwas shown by ASHRAE [22] from the studies
by Rohles and Nevins (1971) and Rohles (1973) on 1600 college
students. A statistical correlation between comfort levels, temper-
ature, humidity, sex, and length of exposure was shown. In that
study, a thermal sensation regression was performed to obtain an
equation able to predict thermal sensation from air temperature
and water vapour pressure, for men and women in different
exposure periods. The thermal sensation scale used in these
equations is referred to as the ASHRAE and PMV scale, as shown in
Table 1. Examples of models proposed by ASHRAE [4,23] are shown
in Eq. (1) and Table 2.
PMV ¼ �6:802þ 0:243$t þ 0:278$pn (1)
where
t is the dry bulb indoor temperature (�C) for a 3 h average.
pv is the indoor partial vapour pressure (kPa) for a 3 h average.
Y values in Table 2 refer to the ASHRAE thermal sensation scale
for young adult subjects with sedentary activity, wearing clothing
with a thermal resistance of approximately 0.5 clo and air velocities
lower than 0.2 m/s.
To adjust thesemodels to our type of building, PMV indices were
recorded by the comfort module in offices with permeable-,
impermeable-, and semi-permeable coverings, with a sample
frequency of five minutes over a period of five hours. The thermal
comfort module was set for an indoor activity of 1.2met and 0.8 clo,
to take into account the chair thermal insulation effect.
2.3.2. Survey
Concurrently with the thermal comfort assessment, a survey
was conducted. The survey included the traditional scales of
thermal sensation and thermal preference. The thermal sensation
scale was the ASHRAE seven-point scale ranging from cold (�3) to
hot (þ3) with neutral (0) in the middle. The clo value was compiled
from the extensive lists published in ISO and metabolic rates
assessed in ASHRAE Standard 55-2004 [4].
After obtaining the PMV and PPD indices, a 3D curve fit of
sampled PMV indices, in accordance with ISO 7730, was performed
with respect to temperature and partial vapour pressure. This curve
fit is in accordance with the model shown by ASHRAE for indoor
ambiences.
This model was employed to define the neutral temperature in
three groups of ambiences, and in one office that presents the same
mean temperature as the impermeable group but a different rela-
tive humidity, in order to determine the relative humidity effect on
neutral temperature, in accordance with different models.
On the other hand, a linear curve fit of surveyed values will show
the neutral temperature for the corresponding thermal sensation
(Tsens).
2.3.3. Adaptive models
Over the last few years, adaptive models have been applied to
define neutral temperature as a function of outdoor, indoor, or both
temperatures. Some of them present a higher accuracy in certain
Table 2
PMV models proposed by ASHRAE.
Exposure period (h) Equation
1 h Y ¼ 0:245,t þ 0:248,pv � 6:475
2 h Y ¼ 0:252,t þ 0:240,pv � 6:859
3 h Y ¼ 0:243,t þ 0:278,pv � 6:802
0
5
10
15
20
25
30
1 2 3 4 5 6 7 8 9 10 11 12
Month
T
e
m
p
e
r
a
t
u
r
e
 
(
º
C
)
Fig. 2. Outdoor minimum, maximum and mean temperature (�C).
J.A. Orosa, A.C. Oliveira / Renewable Energy 36 (2011) 951e956 953
conditions and, as a result, the main models were employed for this
study.
Nicol and Roaf [11] recommended the model of Eq. (2) for
occupants of naturally ventilated buildings. Many other adaptive
models have also been proposed. For example, Humphreys [14]
developed two models for neutral temperature, as given by Eqs.
(3) and (4), and Auliciems and de Dear developed relations for
predicting group neutralities based on mean indoor and outdoor
temperatures, as shown in Eqs. (5), 6 and 7, which were employed
by ASHRAE [4] in Eq. (8).
Tn;o ¼ 17þ 0:38To (2)
Tn;1 ¼ 2:6þ 0:831Ti (3)
Tn;o ¼ 11:9þ 0:534To (4)
Tn;i ¼ 5:41þ 0:731Ti (5)
Tn;o ¼ 17:6þ 0:31To (6)
Tn;i;o ¼ 9:22þ 0:48Ti þ 0:14To (7)
Tc ¼ 17:8þ 0:31To (8)
where Tc is the comfort temperature, To is the outdoor air
temperature, Ti is the mean indoor air temperature, Tn,i is the
neutral temperature based on mean indoor air temperature, and
Tn,o is the neutral temperature based on mean outdoor air
temperature.
Fig. 1. 3D curve adjustment for PMVn as a function of dry bulb temperature and vapour
pressure.
Before applying these models, we must remember that occu-
pants must be engaged in near-sedentary activity (1e1.3 met) and
must be able to freely adapt their clothing. Furthermore, neither
a heating system nor a mechanical cooling system can be in oper-
ation, although non-conditioned mechanical ventilation can be
present. Despite this, windows must be the main method of
controlling thermal conditions.
3. Results
In accordancewith themethodology, Fig.1 shows the curve fit of
recorded PMV indices with respect to indoor temperatures and
partial vapour pressures, following a linear modele see Eq. (9). The
fit, with a correlation coefficient of 0.956, is expressed by:
PMVn ¼ �5:151þ 0:202$t þ 0:553$pn (9)
where t is the dry bulb temperature (�C) and pv is the partial vapour
pressure (kPa).
Eq. (9) is limited to dry bulb temperatures below 25 �C and
presents a validity range of temperature from 20.2 �C to 24.7 �C,
partial vapour pressure from 1.0 to 1.8 kPa, and PMVn from �0.4 to
0.8. Furthermore, this model is adequate for young adult subjects
with sedentary activity, wearing clothing with a thermal resistance
of approximately 0.5 clo and air velocities lower than 0.2 m/s,
which are commonly found in this type of building in the summer
season.
The outdoor climate data are illustrated in Fig. 2 and the indoor
temperature in each group of office buildings and their neutral
temperature are represented in Tables 3 and 4, respectively.
Furthermore, to obtain the neutral temperature a linear regression
of temperature in terms of PMVn was performed in Figs. 3,4, and 5.
When we compare the model obtained with that proposed by
ASHRAE, a clear similarity between temperature constants is
visible. On the other hand, the partial vapour pressure constant
presents a higher value, reflecting themarked importance of indoor
relative humidity.
To define the neutral temperature, the model was applied to
determine the indoor thermal comfort conditions in some of the
Table 3
Mean outdoor and indoor temperature (Tmean) in all office groups during the whole
measuring period and difference to neutral temperature from the thermal sensation
model (Tnsens).
Group Mean temperature Tmean (�C) (Tmean-Tnsens)
Impermeable 24.5 þ2.1
Semi-permeable 23.6 þ1.2
Permeable 22.8 þ0.4
All offices 23.7 þ1.3
Outdoor 19.5
Table 4
Neutral temperature proposed by each model and its error in all office groups relatively to the neutral temperature from the thermal sensation model (Tnsens).
Model Neutral temperature Tn (�C) Error (Tn-Tnsens)
Adaptive models Nicol and Roaf (Tn,o) 24.43 (Eq. (2)) þ2.03
Auliciems and de Dear (Tn,o) 23.66 (Eq. (6)) þ1.26
Humphreys (Tn,o) 22.34 (Eq. (4)) �0.06
Auliciems and de Dear (Tn,i) 22.73 (Eq. (5)) þ0.33
Humphreys (Tn,i) 22.29 (Eq. (3)) �0.11
Auliciems and de Dear (Tn,i,o) 20.98 (Eq. (7)) �1.42
PMVn model 21.63 �0.77
Thermal sensation (Tnsens) 22.40 0.00
J.A. Orosa,A.C. Oliveira / Renewable Energy 36 (2011) 951e956954
twenty-five office buildings during the summer season. These
offices were classified from a previous study [18] on their internal
covering permeability considerations and, from them, the four
offices with the most impermeable coverings (glass, paint etc.)
were selected, a further four with the most permeable coverings
(good, paper) and the last four with semi-permeable coverings.
After obtaining their PMV indices by means of the developed PMVn
model, a linear regression between indoor temperature and PMVn
was performed for each group of offices, as shown in Figs. 3,4 and 5.
These three regressions led to coefficients of determination of
r ¼ 0.97, 0.96 and 0.99 for permeable, semi-permeable, and
impermeable coverings, respectively. If we now analyse its neutral
temperature, we can conclude that it will be 21.8, 21.2, and 21.0 �C
for permeable, semi-permeable, and impermeable coverings. These
values are all summarized in Table 5, to be compared with the
neutral temperature proposed by the other models and the thermal
sensation.
To calculate neutral temperature in the adaptive models, the
mean indoor temperatures of all groups of offices (Tmean) are
calculated and shown in Table 3. Another parameter needed to
apply these models is the outdoor temperature, obtained from
climatic conditions. A Coruña presents the highest yearly outdoor
temperature in August, reaching minimum andmaximumvalues of
13.5, and 25.6 �C, respectively, as shown in Fig. 2. This is the most
interesting month to study the summer neutral temperature. The
meanmonthly outdoor air temperature is defined as the arithmetic
average of the mean daily minimum and mean daily maximum
outdoor (dry bulb) temperatures for the month in question. The
value obtained appears in Table 3 and the adaptive neutral
temperatures in Tables 4 and 5.
To calculate the real neutral temperature for these ambiences,
the thermal sensation was related to the indoor temperatures, as
shown in Fig. 6. This figure allows us to deduce that the neutral
temperature will be at 22.4 �C, as shown in Table 4. From this it was
deduced that the actual mean temperatures for all the offices are
slightly higher than the optimal, and correspond to a thermal
sensationofþ0.7.Despite this, the indoor ambiencepresents natural
ventilation limit conditions that still do not require a cooling system.
y = 4,4238x + 21,06
R2 = 0,9841
20
21
22
23
24
25
26
27
28
-0,5 0 0,5 1 1,5
PMV
n
I
n
d
o
o
r
 
t
e
m
p
e
r
a
t
u
r
e
 
(
º
C
)
Fig. 3. Linear adjustment of internal temperature in terms of PMVn in offices with
impermeable coverings.
4. Discussion
Once the real thermal sensation was obtained by the survey
(Tnsens), the differences in the adaptive and thermal sensation
models to define the neutral temperature will be estimated, as
shown in the last column of Table 4.
There, we can see that Humphrey models, based on outdoor
temperature (Tn,o), and specially that based on indoor temperature
(Tn,i), present a lower difference (error) than that based on indoor
and outdoor temperatures, and that with PMVn indices. Results
confirm that the models by Nicol and Roaf and Humphreys (based
on outdoor temperature) provide an accurate prediction and that
adaptive models based on both mean indoor and outdoor
temperatures predict neutral temperature with a slight margin of
error, as expected [24]. The PMVn index showed a lower error than
expected, with a noticeable tendency to overestimate thermal
neutralities. Despite this, the result of þ0.77 �C (equivalent to
PMV ¼ þ0.1 at t ¼ 22.4) is lower than the PMV values found by
Memon [10] and Busch [24] of þ1.3 and þ0.5, respectively. As
a result, the PMVn index obtained is a good tool for this study.
One possible explanation of why the PMV index overestimates
the sensation of warmth in non-air-conditioned buildings, is that
opening windows in naturally ventilated buildings should provide
a higher level of personal control than in air-conditioned buildings.
Another explanation for the difference lies in the occupants’
expectations [25]. This may be expressed by an expectancy factor, e,
to be multiplied by PMV to reach the mean thermal sensation vote
of the occupants. In fact, the effects of behavioural, physiological,
and psychological adjustments appear to have been overlooked
when subjects were casting Tnsens votes. This may explain differ-
ences between observed and predicted values, which are attributed
to a subject’s long-term behaviour (open windows or fan), physi-
ology (metabolism, clothing), and psychology that may not be
accounted for, in the short-term, based on observation, so Tnsens
vote’s invariability with temperature was much more remarkable
than PMV [7]. In particular, there is an error in the estimation of the
activity and a systematic omission of the thermal effect depending
on whether chairs have their occupants [1]. Furthermore, clo
y = 3,7975x + 21,867
R2 = 0,9485
20
21
22
23
24
25
26
27
28
-0,5 0 0,5 1 1,5
PMV
n
I
n
d
o
o
r
 
t
e
m
p
e
r
a
t
u
r
e
 
(
º
C
)
Fig. 4. Linear adjustment of internal temperature in terms of PMVn in offices with
permeable coverings.
y = 1,36x + 22,398
R = 0,5228
20
21
22
23
24
25
26
27
28
-0,5 0 0,5 1 1,5 2
Thermal sensation
I
n
d
o
o
r
 
t
e
m
p
e
r
a
t
u
r
e
 
(
º
C
)
Fig. 6. Indoor temperature in terms of thermal sensation.
y = 4,1696x + 21,274
R = 0,9313
20
21
22
23
24
25
26
27
28
-0,5 0 0,5 1 1,5
PMV
n
I
n
d
o
o
r
 
t
e
m
p
e
r
a
t
u
r
e
 
(
º
C
)
Fig. 5. Linear adjustment of internal temperature in terms of PMVn in offices with
semi-permeable coverings.
J.A. Orosa, A.C. Oliveira / Renewable Energy 36 (2011) 951e956 955
estimation differs by as much as 20%, depending on the source of
tables and algorithms.
Deep analyses arise when we classify the indoor ambiences in
terms of their internal coverings. Over the past few years, porous
wall materials have proved to be possible passive systems to buffer
indoor climate humidity variations. With normal occupant behav-
iour, with daily cycles of high-low humidity, only the inner surface
layer of a material interacts with the indoor air. The main param-
eters that decide the amount of water vapour absorbed bymaterials
are: the surface structure, the porosity and the moisture content of
the surrounding air. In particular, when we notice the real effect of
internal coverings on indoor environment in an occupied office
building, a state of equilibrium between the air humidity and the
building materials is achieved. Such equilibrium depends on the
occupant behaviour, the air tightness, as well as the external
climate and the coverings.
Permeable coverings present a mean temperature closer to the
neutral thermal sensation and, as a result, the lower energy
consumption to reach those conditions in the first hours of occu-
pation, as shown in the second column of Table 3. On the other
hand, impermeable coverings present more than 2 �C over the
general neutral temperature, with a corresponding energy
consumption, if a cooling system is working.
This lower indoor mean temperature could be related to the
internal coverings. In this sense, recent studies [3e11] have shown
that moisture transfer between indoor air and porous wall mate-
rials can generally improve indoor humidity conditions [7]. In
particular, these studies show the potential for hygroscopic struc-
tures made of wood-based materials in moderating variations in
indoor air relative humidity. Furthermore, Gaur [14] and Hall et al.
[15] showed that the humidity present in ambient and indoor air
affects indoor temperature by 2e3 �C due to the effect of moisture
Table 5
Neutral temperature proposed and its difference to neutral temperature from the
thermal sensation model (Tnsens).
Model Neutral temperature
Tn (�C)
Error (Tn-Tnsens)
Adaptive models Auliciems and
de Dear (Tn,i)
Impermeable 23.36 þ0.96
Semi-permeable 22.72 þ0.32
Permeable 22.12 �0.28
Humphreys (Tn,i) Impermeable23.00 þ0.60
Semi-permeable 22.80 þ0.40
Permeable 21.59 �0.81
Auliciems and
de Dear (Tn,i,o)
Impermeable 23.74 þ1.34
Semi-permeable 23.32 þ0.92
Permeable 22.93 þ0.53
PMVn model Impermeable 21.06 �1.34
Semi-permeable 21.27 �1.13
Permeable 21.86 �0.54
on conduction and diffusion of vapour and heat transfer fromwalls.
This effect could be related to these better indoor conditions.
Prediction of the neutral temperature by covering type is shown
in Table 5, where an evident change in model behaviour was found.
For example, Auliciems and De Dear models present the maximum
accuracy in terms of indoor conditions, while Humphreys’ model
presents a slightly higher error. The PMV and adaptive models
based on indoor and outdoor temperatures, present the worst
accuracy. As expected, the PMVn tendency is to predict a higher
thermal sensation and the Humphreys’ model tends to predict
a lower thermal sensation; as a result, thesemodels suggest a lower
and higher neutral temperature, respectively.
Another conclusion that we can reach from the last column of
Table 5, is that a higher mean indoor temperature, in adaptive
models, induces a higher neutral temperature, while PMVn index
was not fully modified. For example, by applying the PMVn index,
the partial vapour pressure induced a lower neutral temperature in
offices with a higher mean temperature due to impermeable
coverings. In this case, permeable coverings lead to a better
ambience because of their indoor partial vapour pressure, which
was not taken into account in the other models. Furthermore, if we
now compare the two ambiences with the same indoor tempera-
ture and different relative humidities (partial vapour pressures),
adaptive models will propose the same indoor temperature, while
the PMVn model will suggest a different set point temperature for
each one. For example, whenwe select one office building with the
same mean temperature (24.5 �C) but different partial vapour
pressures (1.736 kPa) from the group of impermeable offices
(1.774 kPa), another neutral temperature will be proposed, as we
can see in Fig. 7. This new neutral temperature is 21.28 �C, as
opposed to 21.0 �C proposed for the group of impermeable offices,
and 23.0 �C proposed by adaptive models for both environments.
From these results, we can deduce that, for the same indoor
temperature, a higher relative humidity is related to a lower neutral
y = 4,26x + 21,282
R = 0,9339
20
21
22
23
24
25
26
27
28
0 0,5 1 1,5
PMV
n
I
n
d
o
o
r
 
t
e
m
p
e
r
a
t
u
r
e
 
(
º
C
)
Fig. 7. Linear adjustment of internal temperature in terms PMVn for an office building
with the same temperature and different relative humidities.
J.A. Orosa, A.C. Oliveira / Renewable Energy 36 (2011) 951e956956
temperature (�0.2 �C), despite the fact that adaptive models fail to
consider these indoor changes.
5. Future work
Further studies about the implementation of PMV to approach
adaptive models must be conducted. For example, a study could be
conducted taking another variable such as outdoor temperature
when the model is adjusted. Possible applications of these new
models are the design stage of a new building, or the operation and
evaluation of an existing building; the interior temperatures might
be allowed to float withinmore energy-efficient acceptability limits
and, when the temperatures reach the maximum limits, then the
air conditioning could be turned on, in a limited way, to ensure that
temperatures stay within limits.
Another application is the use of a model for regional climate
analysis, as a way of investigating the feasibility of using natural
ventilation, and the potential energy savings that might result. In
this sense, to employ this methodology to define a PMVn index for each
specific local climate, it is only necessary to adjust the PMV model
constants to each particular region, after adequate sampling of indoor
ambiences in enough buildings. Furthermore, this procedure lets us
define the neutral temperature considering the indoor relative
humidity of each region and not only outdoor climatic data, as recently
employed for a climatic analysis in arid regions [26]. As a consequence,
more adequate results are expected in future research works.
6. Conclusions
This work supports the notion that climatic differences affect
comfort perception, achieving a good level of agreement between
the thermal sensation and adaptive models. On the other hand,
neutral temperatures obtained from the newly developed PMVn
model are lower than those obtained from surveys.
The difference between models is mainly attributed to the
thermal adaptation of humans. In fact, people usually adapt to the
thermal environment by adjusting other parameters in their heat
balance, such as clothing, windows, and fans. However, this is not
the only difference; other parameters such as met and clo estima-
tion could be sources of error.
Besides this, the model obtained is an interesting instrument to
combine the PMV index with adaptive models, because it lets us
consider indoor temperatures and relative humidity with neutral
temperature and, as a result, consider the effect of coverings. For
example, this newmodel classifies indoor ambiences in accordance
with its indoor relative humidity, and, as a result, suggests different
neutral temperatures in adaptive models. This advantage could be
applied to obtain energy savings, because it entails a difference
higher than 1 �C between indoor conditions. Furthermore, these
new thermal comfort conditions could involve a decision of
whether or not to apply a cooling system.
On the other hand, offices with permeable coverings present
a mean temperature nearer the thermal sensation, with better
thermal comfort conditions and possible energy savings, if a cool-
ing system is working or expected to work. Further studies on
a comparison between PMV and adaptive models must be
conducted.
Acknowledgements
We would like to show our appreciation for our sponsor, the
University of A Coruña, for their support through research project
9880541A481.08.
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	A new thermal comfort approach comparing adaptive and PMV models
	Introduction
	Methodology
	Buildings
	Indoor and outdoor conditions
	Thermal comfort models
	ISO PMV model
	Survey
	Adaptive models
	Results
	Discussion
	Future work
	Conclusions
	Acknowledgements
	References