A STUDY INTO THE THERMAL
PERFORMANCE OF LOW-RISE OFFICE
BUILDINGS IN GHANA
Christian KORANTENG1,2
1
Department of Architecture
Kwame Nkrumah University of Science and Technology
Kumasi, Ghana
E-Mail: christiankoranteng@yahoo.co.uk
Tel: +233 244858961
Ardeshir MAHDAVI2
2 Department
of Building Physics and Building
Ecology
Vienna University of Technology
Austria
OVERVIEW

INTRODUCTION




APPROACH
RESULTS & DISCUSSION





Motivation
Background
Indoor thermal conditions
Active case scenario
Passive case scenario
Energy use, retrofitting and CO2
emission evaluation
CONCLUSION
2
INTRODUCTION
MOTIVATION
 Increase in housing stock (42%) and growth in commercial
buildings (100%) since 2000.
 Building designs not supported by scientific approach.
 Design decision making not supported by energy-efficient
building design methods and technologies.
3
INTRODUCTION
OBJECTIVES
 Long-term monitoring of the thermal conditions.
 The effective prediction of the buildings’ performance
based on calibrated models.
 Simulation-based
exploration
to
reduce
cooling
requirements.
 Assessment of carbon dioxide (CO2) emissions and
retrofitting evaluation.
4
INTRODUCTION
BACKGROUND
.
Energy use and conservation
 setting of environmental standards
 environmental control installations
 renewable energy alternatives
 building form and fabric
Szokolay (2004)
Thermal comfort and scales
Olgyay (1953)
Brooks (1963)
Königsberger et al. (1974)
Szokolay (2004)
Mahdavi et al. (2007)
Orientation and building form
Salmon (1999)
Szokolay (2004)
Lauber (2005)
5
APPROACH
BUILDINGS
Selection of low-rise buildings: Schematic plans
Building ANG
Building CAP
Building ROY
Building DCD
Building KCR
6
APPROACH
Monitored environmental data
(Temperature and relative humidity recordings)
Indoor thermal conditions
(plots on psychrometric charts)
Calibration of the simulation
application
Parametric study – Active case
(air-conditioning – reducing energy use)
Parametric study – Passive case
(no air-conditioning - reducing overheating in the buildings)
Energy use, CO2 evaluation
and retrofitting estimation
7
RESULTS AND DISCUSSION
Monitored environmental data
Comparison of mean outdoor temperature measurements at office
locations (DL) with Kumasi
weather station data (MET)
Mean Outdoor Temperature
30
Temperature [°C]
29
28
27
26
25
24
JAN
FEB MAR APR MAY JUN
MET
JUL
AUG SEP OCT NOV DEC
DL
Results show a good agreement
8
RESULTS AND DISCUSSION
essure: 99535.9479 Pa
12
0
13
0
11
0
Indoor thermal
conditions:
10
0
10
12
0
-10
C
Humidity ratio, g/kg(a)
Sep
Aug Nov Oct
Jun
Jul
Dec
May
Mar
Apr
Feb
%
60
40
0
20
80
80
%
60
10
%
20%
Jan
0
Jan
10
40
%
10
Comfort
zone
20%
-10
0
-2010
-1020
0 30
Dry bulb temperature, deg C
0
0
12
0
11
0
 Measured indoor
eg
nt
%
Sa
tur
ati
o
on
t
ati
Sa
tur
Comfort
zone
10
13
20
em
Nov
th 5
0
En
Sep
Jul
Oct
Aug
40 May
20 Jun
Mar
Apr
Dec
30
Feb
20
,d
ure
60
rat
k
p
al
pe
em
pe
rat
ur
y,
J/
(
kg
%
eg
C
70
a)
e,
d
70
13
0
30
Mean daily
temperature
and relative90 humidity30values
90
(averaged
over all days in a month)
in CAP (left) and
80
80
KCR (right) building
)
(a
60
0
10 40
20 50
30
Dry bulb temperature, deg C
60
13
0
temperature and relative
12
0
humidity point to20deficient
indoor thermal conditions.
11
Humidity ratio, g/kg(a)
11
0
10
Responsible
factors include:
0
0
 Inefficient building
90
90
10
systems (windows,
fans,
shades, air-conditioners,
80
80
etc)
 Behaviour of occupants
70
70
 Unsustainable design
principles (form and
40
50
60
orientation)
10
9
RESULTS AND DISCUSSION
Calibration: Weather file versus
measured data
Calibration: Comparison of
measurements and simulation
Measured versus simulation indoor air
temperatures (for instance) in CAP
36
34
34
32
32
Temperature [°C]
36
30
28
26
30
28
26
24
22
22
20
20
DL
WF
00
:0
03 0
:0
0
06
:0
0
09
:0
0
12
:0
0
15
:0
0
18
:0
0
21
:0
0
00
:0
0
03
:0
0
06
:0
0
09
:0
0
12
:0
0
15
:0
0
18
:0
0
21
:0
0
00
:0
0
03
:0
0
06
:0
0
24
00
:0
03 0
:0
0
06
:0
0
09
:0
0
12
:0
0
15
:0
0
18
:0
0
21
:0
0
00
:0
0
03
:0
0
06
:0
0
09
:0
0
12
:0
0
15
:0
0
18
:0
0
21
:0
0
00
:0
0
Temperature [°C]
Outdoor air temperature segments
(WF) as against measurements (DL) at
building location (KCR)
Measured
Simulated
Measurements and simulation plots show a relatively good agreement
10
RESULTS AND DISCUSSION
Parametric Study: Active case
Simulated cooling loads for combined
improvement scenarios.
Total
cooling load
(%)
Reduction
(%)
CAP
78.5
21.5
KCR
65.8
34.2
ANG
74.7
25.3
ROY
71.1
28.9
DCD
80.3
19.7
 Efficient Windows
 Attic Floor Insulation (on Ceiling)
 Natural Ventilation
 Efficient Electric Lighting
Efficient and combined improvement scenarios (such as better windows,
natural ventilation, and efficient electrical lighting) appear to have a
synergistic effect on cooling loads (20 to 35% reductions).
11
RESULTS AND DISCUSSION
Parametric Study: Passive case
Mean overheating (OHm in K) and fraction of time (FOT in %) with indoor
conditions within the comfort zone (from 8 am to 5 pm, assumed indoor air
speed 1.0 m.s-1) (BC: Base case, PC: Passive case-improvements)
Building
CAP
KCR
ANG
ROY
DCD
BC
FOT [%]
25
30
20
12
43
PC
OHm [K]
4.4
4.2
5.1
6.0
3.8
FOT [%]
77
73
65
72
68
OHm [K]
1.8
2.0
2.4
2.0
2.1
 Mean overheating could be reduced from ca. 5 down



to ca. 2 K.
A FOT of 65 to 77% was calculated (for 1.0 m.s-1).
Fan induced ventilation of 1.0 m.s-1 (awareness) would
probably be needed in free-running office buildings in
Kumasi.
More stringent performance objectives would require
mechanical cooling.
12
RESULTS AND DISCUSSION
Parametric Study: Passive case
PMV (predicted mean vote) and PPD (predicted persons dissatisfied)(in %) for
all buildings (BC: Base case, PC: Passive case-improvements)
Building
CAP
KCR
ANG
ROY
DCD
BC
PMV
2.8
2.8
3.1
3.3
2.6
PC
PPD
93.5
91.6
95.0
97.1
87.5
PMV
1.6
1.6
1.8
1.6
1.7
PPD
55.5
54.5
64.3
56.3
58.2
 Combined measures (particularly the use of natural ventilation) could


significantly reduce PPD.
The results are however very high (55 to 65% PPD).
Estimated PMV and PPD values show improvements by adapting the PC
scenario
13
RESULTS AND DISCUSSION
Energy use, CO2 reduction and retrofitting estimate (payback time):
All based on the comparison of the BC and CI scenarios.
Assumptions made: unit cost of electricity in Ghana = 0.12 € per kWh, system
efficiency for the split air-conditioning units = 2.6, CO2 emission = 0.238 kg.kWh-1
Building
CAP
KCR
ANG
ROY
DCD
Total
Building
CAP
KCR
ANG
ROY
DCD
Energy cost
saving [€]
7,937
13,076
4,760
19,815
2,865
48,454
Energy saving
[kWh]
66,144
108,966
39,668
165,126
23,878
403,783
Retrofit expenses [€]
43,239
41,465
14,554
233,706
20,876
CO2
reduction [kg]
15,742
25,934
9,441
39,300
5,683
96,100
Payback time (years)
5.4
3.2
3.1
11.8
7.3
14
RESULTS AND DISCUSSION
Energy use, CO2 reduction and retrofitting estimate (payback time):
 Efficient and combined improvement scenarios (better windows, natural
ventilation, and efficient electrical lighting) again led to reductions in the
energy use of the buildings (in average 27% and 3,000 to 20,000€ annual
energy savings)
 CO2 emissions could be reduced by about 6 to 40 tons per building (in all ca
100 tons) through more energy efficient building performance.
 Mean CO2 reductions of 27%.
 CO2 voucher value rather small (ca. € 17 per tons of CO2).
 The payback times calculated for the amortization of building retrofit costs can
be considered reasonable (3 – 12 years).
15
CONCLUSION
.
 The measured temperature and relative humidity values in the offices point to
deficient thermal comfort conditions. However, occupants' adaptation capability
may have been underestimated.
 Combinations of better windows, natural ventilation, and efficient electrical
lighting have a synergistic effect on cooling loads, energy use and CO2
emissions (20 to 35%).
 The payback times calculated for the amortization of building retrofit costs can
be considered reasonable (3 –12 years).
 The use of natural ventilation (1.0 m.s-1) could increase the fraction of time
(FOT) in which thermal indoor conditions are in the comfort zone (65 – 77%).
These positive measures, when implemented, have the potential to
contribute positively to the energy situation in Ghana.
16
THANK YOU
17