Transcript Precision and thermal comfort Fergus Nicol London Metropolitan University and Oxford Brookes University.

Precision and thermal comfort
Fergus Nicol
London Metropolitan University and
Oxford Brookes University
Thermal comfort standards
Type of
Clothing
Activity Category Operative Temperature Mean Air Velocity
Building/
Cooling
Heating
Cooling
Heating
Cooling
Heating
Space
Season
Season
season
Season
season
season
(summer)
(winter)
°C
°C
ms-1
ms-1
A
24.5 ± 0.5
22.0 ± 1.0
0.18
0.15
B
24.5 ± 1.5
22.0 ± 2.0
0.22
0.18
C
24.5 ± 2.5
22.0 ± 3.0
0.25
0.21
A
23.5 ± 1.0
20.0 ± 1.0
0.16
0.13
B
23.5 ± 2.0
20.0 ± 2.5
0.20
0.16
C
23.5 ± 2.5
20.0 ± 3.5
0.24
0.19
A
23.0 ± 1.0
19.0 ± 1.5
0.16
0.13
B
23.0 ± 2.0
19.0 ± 3.0
0.20
0.15
C
23.0 ± 3.0
19.0 ± 4.0
0.23
0.18
(summer) (winter)
Office
Cafeteria/
Clo
Clo
met
0.5
1.0
1.2
0.5
1.0
1.4
Restaurant
Department
Store
0.5
1.0
1.6
(summer) (winter)
From Olesen and Parsons, Energy and Buildings 34(6)
Summer in Saidu Sharif, Pakistan (photo M Humpheys)
Winter in Saidu Sharif, Pakistan (photo M Humpheys)
Changing ourselves
• As the temperature changes so the level of
clothing, the air movement (which can cool
the body by convection and/or evaporation
of sweat) and the moisture of the skin will
change.
• It is also probable that people are less active
in the heat, but because metabolic rate is
measured by ‘activity’ this is not clear
Personal variables
1.6
1.4
1.2
Clothing insulation
Air velocity
Metabolic rate
Skin moisture
1
0.8
0.6
0.4
0.2
0
10
15
20
25
30
35
40
Indoor temperature
Data from Pakistan
Proportion of subjects comfortable
The result of these actions is shown in this graph of
the level of discomfort at different indoor
temperatures among office workers in Pakistan
1
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
Little discomfort
12
14
16
18
20
22
24
26
28
30
32
34
36
38
Mean indoor temperature oC
Nicol, Raja, Allauddin & Jamy (1999) Energy and Buildings 30(3)
Use of fans as a function of outdoor temperature in Pakistan
100%
% running
80%
60%
40%
20%
0%
5
10
15
20
25
30
35
Mean outdoor temperature
Fans are available in almost all Pakistani offices this graph
shows the proportion in use a different temperatures
40
Use of fans as a function of outdoor temperature in Pakistan
100%
Probability control is in use
is given by:
p = e(a+bTo)/(1+e(a+bTo))
a and b are determined by
regression analysis
% running
80%
60%
40%
20%
0%
5
10
15
20
25
30
35
Mean outdoor temperature
A curve of p on To can then be drawn to show
the probability that a control is being used
40
Use of
Fansfans
100%
% running
80%
60%
UK
Europe
Pakistan
40%
20%
0%
0
10
20
30
40
Mean outdoor temperature
Details: Nicol, J.F. (2001) 7th international IBPSA conference, Rio
Use ofWindows
windows
100%
% open
80%
60%
UK
Europe
Pakistan
40%
20%
0%
0
10
20
Mean outdoor temperature
30
40
Use ofBlinds
blinds/curtains
or curtains
100%
% drawn
80%
60%
UK
Europe
40%
20%
0%
0
10
20
mean outdoor temperature
30
40
The use of curtains is better related to
the external illuminance:
Blinds in use vs illuminance
Proportion of blinds drawn
100.0%
80.0%
60.0%
Actual P
predicted P
40.0%
20.0%
0.0%
1.5
2
2.5
3
3.5
4
4.5
5
Log (base 10) of external illuminance
From data of Yannick Sutter, ENTPE, Lyons
5.5
Use ofHeating
heating
100%
% on
80%
60%
UK
Europe
Pakistan
40%
20%
0%
0
10
20
mean outdoor temperature
30
40
AC on (mixed-mode buildings only)
100%
Proportion running
80%
Europe
Pakistan
Europe (actual)
Pakistan (actual)
60%
40%
20%
0%
0
5
10
15
20
25
Outdoor temperature oC
30
35
40
Comfort is achieved by
the occupants adapting to
the building
Occupant
Building
Or by the occupants
adapting the building to
suit them
This has to be done within the climatic, social, economic
and cultural context of the whole system
Cautionary note:
• Whilst essentially a negative feed-back
system aimed at avoiding discomfort, the
behaviour resulting from discomfort can
lead to a positive feed-back in energy use:
Air-conditioning
Global warming
Energy use
New approaches
Comfort is achieved by
the occupants adapting to
the building
Occupant Empirical
simulation results
Building
simulation
Or by the occupants
adapting the building to
suit them
This has to be done within the climatic, social, economic
and cultural context of the whole system
E.N. – Electricidade do Norte offices,
Porto, Portugal
40
30
TG
20
10
0
TOI
10
20
30
40
• The temperatures were measured during
office hours during a thermal comfort
survey.
• It will be noticed that there is a tendency for
the indoor temperature to be above the
outdoor temperature in cold weather and
often below it in warmer weather.
• There is also structure in the distribution of
indoor temperatures at any given outdoor
temperature
TOIRND:
2.00
300
250
200
150
100
Std. Dev = 1.86
50
Mean = 19.1
N = 28.00
0
15.0 17.0 19.0 21.0 23.0 25.0 27.0 29.0 31.0 33.0 35.0
16.0 18.0 20.0 22.0 24.0 26.0 28.0 30.0 32.0 34.0
TG
TOIRND:
4.00
300
250
200
150
100
Std. Dev = 2.74
50
Mean = 18.5
N = 60.00
0
15.0 17.0 19.0 21.0 23.0 25.0 27.0 29.0 31.0 33.0 35.0
16.0 18.0 20.0 22.0 24.0 26.0 28.0 30.0 32.0 34.0
TG
TOIRND:
6.00
300
250
200
150
100
Std. Dev = 2.53
50
Mean = 19.3
N = 101.00
0
15.0 17.0 19.0 21.0 23.0 25.0 27.0 29.0 31.0 33.0 35.0
16.0 18.0 20.0 22.0 24.0 26.0 28.0 30.0 32.0 34.0
TG
TOIRND:
8.00
300
250
200
150
100
Std. Dev = 2.72
50
Mean = 20.09
N = 207.00
0
0
.0
35
0
.0
33
0
.0
31
0
.0
29
0
.0
27
0
.0
25
0
.0
23
0
.0
21
0
.0
19
0
.0
17
0
.0
15
TG
TOIRND:
10.00
300
250
200
150
100
Std. Dev = 2.50
50
Mean = 20.83
N = 456.00
0
0
.0
35
0
.0
33
0
.0
31
0
.0
29
0
.0
27
0
.0
25
0
.0
23
0
.0
21
0
.0
19
0
.0
17
0
.0
15
TG
TOIRND:
12.00
300
250
200
150
100
Std. Dev = 2.44
50
Mean = 21.51
N = 807.00
0
0
.0
35
0
.0
33
0
.0
31
0
.0
29
0
.0
27
0
.0
25
0
.0
23
0
.0
21
0
.0
19
0
.0
17
0
.0
15
TG
TOIRND:
14.00
300
250
200
150
100
Std. Dev = 2.04
50
Mean = 22.31
N = 974.00
0
0
.0
35
0
.0
33
0
.0
31
0
.0
29
0
.0
27
0
.0
25
0
.0
23
0
.0
21
0
.0
19
0
.0
17
0
.0
15
TG
TOIRND:
16.00
300
250
200
150
100
Std. Dev = 1.95
50
Mean = 23.22
N = 985.00
0
0
.0
35
0
.0
33
0
.0
31
0
.0
29
0
.0
27
0
.0
25
0
.0
23
0
.0
21
0
.0
19
0
.0
17
0
.0
15
TG
TOIRND:
18.00
300
250
200
150
100
Std. Dev = 1.81
50
Mean = 24.31
N = 849.00
0
0
.0
35
0
.0
33
0
.0
31
0
.0
29
0
.0
27
0
.0
25
0
.0
23
0
.0
21
0
.0
19
0
.0
17
0
.0
15
TG
TOIRND:
20.00
300
250
200
150
100
Std. Dev = 1.88
50
Mean = 24.86
N = 575.00
0
0
.0
35
0
.0
33
0
.0
31
0
.0
29
0
.0
27
0
.0
25
0
.0
23
0
.0
21
0
.0
19
0
.0
17
0
.0
15
TG
TOIRND:
22.00
300
250
200
150
100
Std. Dev = 1.85
50
Mean = 25.29
N = 468.00
0
0
.0
35
0
.0
33
0
.0
31
0
.0
29
0
.0
27
0
.0
25
0
.0
23
0
.0
21
0
.0
19
0
.0
17
0
.0
15
TG
Std. Dev = 1.75
50
N = 257.00
0
0
.0
35 00
.
34 00
.
33 00
.
32 00
.
31 00
.
30 00
.
29 00
.
28 00
.
27 00
.
26 00
.
25 00
.
24 00
.
23 00
.
22 00
.
21 00
.
20 00
.
19 00
.
18 00
.
17 00
.
16 00
.
15
TG
24.00
TOIRND:
300
250
200
150
100
Mean = 25.92
Std. Dev = 1.60
50
N = 103.00
0
0
.0
35 00
.
34 00
.
33 00
.
32 00
.
31 00
.
30 00
.
29 00
.
28 00
.
27 00
.
26 00
.
25 00
.
24 00
.
23 00
.
22 00
.
21 00
.
20 00
.
19 00
.
18 00
.
17 00
.
16 00
.
15
TG
26.00
TOIRND:
300
250
200
150
100
Mean = 26.28
TOIRND:
28.00
300
250
200
150
100
Std. Dev = 1.86
50
Mean = 26.3
N = 67.00
0
15.0
17.0 19.0
16.0
TG
21.0 23.0
18.0 20.0 22.0
25.0 27.0 29.0
24.0 26.0
31.0 33.0
28.0 30.0 32.0
35.0
34.0
Std. Dev = 1.44
50
N = 16.00
0
0
.0
35 00
.
34 00
.
33 00
.
32 00
.
31 00
.
30 00
.
29 00
.
28 00
.
27 00
.
26 00
.
25 00
.
24 00
.
23 00
.
22 00
.
21 00
.
20 00
.
19 00
.
18 00
.
17 00
.
16 00
.
15
TG
30.00
TOIRND:
300
250
200
150
100
Mean = 26.60
Comfort and preference
• How do you feel?
•
•
•
•
•
•
Cold
Cool
Slightly cool
Neutral
Slightly warm
Warm
• Hot
How would you prefer to feel?
Much warmer
A bit warmer
No change
A bit cooler
Much cooler
% of occupants wanting no change
100
80
60
All
Poly. (All)
40
20
0
19
21
23
25
Indoor temperature
Most occupants want no change in indoor temperature
27
Mean
outdoor
temp.
% of occupants wanting no change
100
80
11.2
15.6
20.7
All
Poly. (11.2)
Poly. (20.7)
Poly. (15.6)
Poly. (All)
60
40
20
0
19
21
23
25
Indoor temperature
The effect of separating the outdoor temperatures
27
Conclusions
• Comfort is a psychological, not a
physiological one
• Buildings must enable occupants to be
comfortable
• AC is one way to do this but it is expensive
in equipment and energy
• Buildings behave stochastically and not
precisely, particularly when occupied
• Sustainable solutions need risk assessment
not comfort prescriptions