Daylighting Performance and Potential for Electricity Savings by Using Daylighting in Commercial Buildings Located in Florianópolis, Brazil

Abstract

The objective of this paper is to evaluate the daylighting performance and the potential for
electricity savings by using daylighting in commercial buildings located in Florianópolis.
Models with different geometries and dimensions were analyzed. Two cases were
investigated: Case 1 operating with artificial lighting and air-conditioning, and Case 2
operating with daylighting integrated with artificial lighting and air-conditioning. The
potential for electricity savings were obtained by comparing the electricity consumptions of
Case 1 with those of Case 2. The daylighting performance was analyzed using Daylight
Autonomy and Useful Daylight Illuminances methods. The potential for electricity savings
reached values of up 50.5% of the total electricity consumption. The best daylighting
performances were obtained for models with geometry of 2:1 and room index of 0.8 (small
rooms). It can be concluded that daylighting use in commercial buildings located in
Florianópolis presented a good potential for electricity savings. The best daylighting
performances were obtained for small rooms.

Full text

Proceedings: The Second International Conference on Building Energy and Environment 2012
88
Topic 1. Building energy demand and energy performance of buildings, systems, and
components
Daylighting Performance and Potential for Electricity Savings by Using
Daylighting in Commercial Buildings Located in Florianópolis, Brazil
Ricardo F. Rupp1,*and Enedir Ghisi1
1Laboratory of Energy Efficiency in Buildings, Department of Civil Engineering, Federal
University of Santa Catarina, Florianópolis-SC, 88040-900, Brazil
*Corresponding email: ricardorupp@gmail.com
Keywords: Daylighting, potential for electricity savings, computer simulation
SUMMARY
The objective of this paper is to evaluate the daylighting performance and the potential for
electricity savings by using daylighting in commercial buildings located in Florianópolis.
Models with different geometries and dimensions were analyzed. Two cases were
investigated: Case 1 operating with artificial lighting and air-conditioning, and Case 2
operating with daylighting integrated with artificial lighting and air-conditioning. The
potential for electricity savings were obtained by comparing the electricity consumptions of
Case 1 with those of Case 2. The daylighting performance was analyzed using Daylight
Autonomy and Useful Daylight Illuminances methods. The potential for electricity savings
reached values of up 50.5% of the total electricity consumption. The best daylighting
performances were obtained for models with geometry of 2:1 and room index of 0.8 (small
rooms). It can be concluded that daylighting use in commercial buildings located in
Florianópolis presented a good potential for electricity savings. The best daylighting
performances were obtained for small rooms.
INTRODUCTION
Daylighting has been used as an alternative to reduce the electricity consumption in buildings.
Researches to estimate the potential for energy savings by using daylighting by integrating
daylighting with artificial lighting have been developed. Li and Lam (2000) developed a
simplified method to evaluate the potential for energy savings by using daylighting integrated
with artificial light system in a commercial building located in Hong Kong. The authors
evaluated the global electricity consumption considering the cooling and the artificial lighting
consumption. The authors concluded that the potential for energy savings reached values up to
48.4%.
Bodart and Herde (2002) compared different configurations of windows, with different types
of glass, to assess their impact on the electricity consumption of commercial buildings located
in Belgium. They used the Superlink program for daylighting simulation and TRNSYS to
complete the thermo-energetic analysis. They concluded that the use of daylighting
represented an average potential for energy savings of 39%.
Roisin et al. (2008) assessed the potential for energy savings by using daylighting in
commercial buildings located in Athens, Brussels and Stockholm. The authors used different

Proceedings: The Second International Conference on Building Energy and Environment 2012
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types of control of artificial light. The daylighting simulations were performed using the
Daysim computer program. The potential for energy savings varied between 45% for an office
with north orientation at Stockholm and 61% for an office with south orientation in Athens.
Another simplified method to evaluate the potential for energy savings by using daylighting in
commercial buildings was developed by Krarti et al. (2005). They investigated the daylighting
potential obtained with different geometries, window sizes and types of glass for four cities in
the USA (Atlanta, Chicago, Denver and Phoenix). The potential for energy savings analysis
only considered the artificial light consumption. The authors concluded that the greatest
potential for energy savings was achieved by using blue glass, varying between 13.53% and
16.29%.
Although there are many studies on the potential for energy savings by using daylighting, just
a few evaluated daylighting performance. The UDI (Useful Daylight Illuminances) and DA
(Daylight Autonomy) are dynamic measures of daylighting performance and were used by
some authors (Nabil and Mardaljevic, 2006; Reinhart et al., 2006; Reinhart and Wienold,
2011).
The objective of this paper is to determine, using Daysim and EnergyPlus programs, the
daylighting performance as well as evaluate the potential for electricity savings when there is
integration of daylighting with the artificial lighting system in commercial buildings located
in southern Brazil.
METHOD
The study is based on computer simulations using EnergyPlus 6.0 and Daysim 3.0 programs
of room models of commercial buildings located in southern Brazil. The considerations
adopted for the simulations are as follows.
The city of study
The chosen city was Florianópolis, located in the state of Santa Catarina, southern Brazil. The
latitude, longitude and altitude of Florianópolis can be seen in Table 1. The TRY (Test
Reference Year) climate file of Florianópolis (LabEEE, 2011) was used for the simulations in
both programs.
Table 1. Latitude, longitude and altitude of Florianópolis
City Latitude Longitude Altitude
Florianópolis (Brazil) -27º 36’ -48º 33’ 7 m
The room models
Commercial buildings are the focus of this work. Thereby, a room model was used for
simulations, in which the ceiling, floor and interior walls are adiabatic. The room model was
studied considering different geometries and sizes. The model sizes are based on the room
index (K), defined by Equation 1, as used in lighting manuals and in Ghisi (2002). The overall
height of the rooms was taken as 2.80m and the working surface as 0.75m above floor level.
hDW DW
K).(
.

 (1)

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where W is the overall width of the room (m), D is the overall depth of the room (m) and h is
the mounting height between the working surface and the ceiling (m).
Three geometries (Width:Depth) of 2:1, 1:1 and 1:2 were used. For each geometry, three
room sizes were studied as shown in Table 2. For each case, window areas were varied,
ranging from 0% to 100% at increments of 10%; and four solar orientations were simulated,
i.e., north, south, east and west. The window area is the total area of the façade that can be
glazed. The window is located below a 60cm beam and has the width of the façade.
Table 2. Room dimensions for each room index and geometry
K
Geometry - Width (W):Depth (D)
2:1 1:1 1:2
W (m) D (m) W (m) D (m) W (m) D (m)
0.8 4.92 2.46 3.28 3.28 2.46 4.92
2.0 12.30 6.15 8.20 8.20 6.15 12.30
5.0 30.75 15.38 20.50 20.50 15.38 30.75
Case studies
Each room model was investigated considering two cases: a reference case (Case 1), operating
with artificial lighting and air-conditioning system, and another case (Case 2) operating with
air-conditioning system and the integration of daylighting with the artificial lighting system.
For Case 1, simulations were performed using only EnergyPlus. For Case 2, daylighting
simulations were performed using Daysim and then the results were used as input data in
EnergyPlus. The Daysim was used to simulate the daylighting because some authors indicate
that the daylighting algorithm used in EnergyPlus overestimates indoor illuminances
(Loutzenhiser et al., 2007; Ramos and Ghisi, 2010).
Parameters of simulation
The internal loads used for the simulations are presented in Table 3. These loads were
considered during occupation of the building, i.e., 8am-6pm, from Monday to Friday. The
lighting power density (LPD) was estimated for each room by making a lighting design, which
was performed by using the lumen method. Fluorescent tube lamps (TL5-28W) and recessed
luminaries were used. The occupation (m2 per person) and the power density for equipment
are based on the work of Santana (2006), developed for 35 commercial buildings located in
Florianópolis. The metabolic activity value was based on ANSI/ASHRAE Standard 55 (2004).
Table 3. Internal thermal loads used for simulation
Parameter K
Geometry (Width:Depth)
2:1 1:1 1:2
LPD (W/m2)
0.8 13.9 15.6 13.9
2.0 9.6 9.2 9.6
5.0 8.1 8.0 8.1
Occupation (m2/person) 14.7
Activity (W/m2) 65.0
Equipment (W/m2) 9.7
The building components (Table 4) are also based on the work of Santana (2006), with the
exception of glass (single glass, 6mm, 88% of light transmission) that is based on the
EnergyPlus database (EnergyPlus/DataSets v.6.0, 2010).

Proceedings: The Second International Conference on Building Energy and Environment 2012
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Table 4. Properties of building components
Element Material Roughness Conductivity
(W/m.K)
Density
(kg/m3)
Specific
heat
(J/kg.K)
Thickness
(m)
Total
thickness
(m)
Walls
Plastering mortar rough 1.15 2000 1000 0.025
0.200 Ceramic 6-hole brick rough 0.90 1600 920 0.150
Plastering mortar rough 1.15 2000 1000 0.025
Floor
Concrete slab rough 1.75 2200 1000 0.150
0.185 Plastering mortar rough 1.15 2000 1000 0.025
Ceramic floor rough 0.90 1600 920 0.010
Ceiling
Ceramic floor rough 0.90 1600 920 0.010
0.185 Plastering mortar rough 1.15 2000 1000 0.025
Concrete slab rough 1.75 2200 1000 0.150
Door Wood smooth 0.15 614 2300 0.030 0.030
The air-conditioning system consists of a split hi-wall, which was modelled in EnergyPlus
considering an air change rate of 0.0075 m3/s/person and a COP (Coefficient Of Performance)
of 3.28. The setpoint temperature of air-conditioning was taken as 24ºC, during occupation.
The air-conditioning system was used for cooling only, because in Florianópolis the air-
conditioning is not used for heating (Santana, 2006).
Daylighting simulations
The daylighting simulations were performed using Daysim. The schedule of lighting control
on an hourly basis and the values of UDI (Useful Daylight Iluminances) and DA (Daylight
Autonomy) were the reports generated by Daysim that were used in this work.
In the models, the daylight sensors were kept 0.2m away from each other, creating a grid of
equidistant points. The reflectances of internal walls, ceiling and floor were defined as 80%,
50% and 30%, respectively. The lighting control of artificial light was performed by a
photosensor controlled dimmer system based on daylight illuminances, providing a minimum
illuminance of 500 lux at the workplane throughout working hours.
Potential for electricity savings
Annual electricity consumptions for each room were obtained from the simulations. The
potentials for electricity savings by using daylighting were obtained by comparing, through
Equation 2, the electricity consumptions for the reference case (Case 1) with the case using
daylighting (Case 2).
1001
1
2x
C
C
PES 






 (2)
where PES is the potential for electricity savings by using daylighting (%), C2 is the
electricity consumption of Case 2 (kWh/m2) and C1 is the electricity consumption of Case 1
(kWh/m2).
Daylighting performance
The daylighting performance was evaluated by assessing the UDI and DA for each model.
The results of UDI expresses how often (e.g. percentage of the working year, i.e., occupation
period) the daylighting provides, on the workplane, illuminances less than 100lux (fall-short
of the useful range), between 100-2000lux (useful range) and greater than 2000lux (exceed the
useful range – can cause glare). The results of DA express how often (e.g. percentage of the

Proceedings: The Second International Conference on Building Energy and Environment 2012
92
working year, i.e., occupation period) a minimum workplane illuminance threshold of 500 lux
can be maintained by the daylighting alone (Nabil and Mardaljevic, 2006). The results were
presented by plotting the UDI and DA values versus the work year (occupation period) by the
depth of the models. The daylighting performance was evaluated for each window area of
each model as a function of the potential for electricity savings achieved with the use of
daylighting and also the UDI and DA values.
RESULTS AND DISCUSSION
The electricity consumptions for the reference cases (Case 1) varied from 61.53 to 120.47
kWh/m2.yr and for the daylighting cases (Case 2), from 39.73 to 79.62 kWh/m2.yr. The
reduction of electricity consumption between Case 1 and 2 is caused by the use of
daylighting, which reduced the artificial light consumption and the internal thermal load and
consequently the air-conditioning consumption.
The maximum, minimum and average (among the ten window areas for each model)
potentials for electricity savings by using daylighting integrated with the artificial lighting
system in relation to global electricity consumption are presented in Table 5. Table 5 also
shows, between parentheses, the window area that led to the maximum and the minimum
potential for electricity savings. The potential for electricity savings reached values of up to:
(a) 93.6% in relation to artificial lighting consumption, (b) 36.0% in relation to air-
conditioning consumption and (c) 50.5% in relation to global consumption. The maximum
potentials for electricity savings were achieved for smaller models (room index equal of 0.8).
For large models (room index equal of 5.0), the potential for electricity savings showed the
lesser values – for the geometry of 1:2 there is no potential for electricity savings, because the
daylight was not enough to reduce the electricity consumption.
Table 5. Potential for electricity savings and respective window areas (in parenthesis) for
each geometry and room index when there is integration of daylighting and artificial lighting
Orientation PES
PES - Potential for electricity savings by using daylighting (%) and window
area that led to the maximum and minimum PES (in parenthesis)
Geometry of 2:1 Geometry of 1:1 Geometry of 1:2
K=0.8 K=2.0 K=5.0 K=0.8 K=2.0 K=5.0 K=0.8 K=2.0 K=5.0
North
Maximum 46.2
(20%)
34.1
(60%)
11.2
(90%)
48.6
(20%)
30.1
(80%)
4.9
(100%)
40.3
(60%)
14.2
(100%) 0.0
Minimum 34.6
(100%)
9.3
(10%)
0.0
(10%)
34.6
(10%)
4.2
(10%)
0.0
(10%)
16.0
(10%)
0.0
(10%)
Average 40.0 29.3 6.3 42.5 23.1 1.8 35.2 8.9 0.0
South
Maximum 48.7
(30%)
37.6
(70%)
10.9
(100%)
50.5
(30%)
33.0
(100%)
4.6
(100%)
49.5
(30%)
30.0
(90%)
2.3
(90%)
Minimum 38.0
(10%)
9.1
(10%)
0.0
(10%)
26.3
(10%)
1.9
(10%)
0.0
(10%)
32.4
(10%)
0.0
(10%)
0.0
(10%)
Average 45.0 31.2 5.7 46.5 21.8 1.3 45.8 20.6 0.3
East
Maximum 45.8
(20%)
34.5
(50%)
13.0
(100%)
47.1
(30%)
29.8
(100%)
7.1
(100%)
39.4
(50%)
16.3
(90%) 0.0
Minimum 33.9
(100%)
14.8
(10%)
0.9
(10%)
33.0
(10%)
6.6
(10%)
0.0
(10%)
17.3
(10%)
1.2
(10%)
Average 39.5 30.5 8.7 41.8 23.0 3.4 34.8 10.9 0.0
West
Maximum 45.5
(20%)
34.5
(50%)
12.2
(100%)
46.5
(30%)
29.1
(80%)
4.7
(100%)
38.7
(60%)
13.9
(90%) 0.0
Minimum 33.1
(100%)
8.9
(10%)
0.0
(10%)
28.5
(10%)
3.2
(10%)
0.0
(10%)
11.9
(10%)
0.0
(10%)
Average 38.7 29.0 6.4 40.5 21.7 1.5 33.0 8.2 0.0

Proceedings: The Second International Conference on Building Energy and Environment 2012
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Regarding the daylighting performance, Figure 1 shows the UDI and DA values for model
with geometry of 2:1, room index equal to 0.8, north orientation and ten window areas. The
best daylighting performances were obtained for models with geometry of 2:1 and 1:1 with
room index of 0.8 (small rooms). In these models the window area (smaller than 30%) related
to the maximum potential for electricity savings by using daylighting conducted to
percentages of work year (occupancy period, i.e., 8am-6pm, from Monday to Friday): (a)
greater than 40% in the UDI useful range and (b) greater than 80% of DA, throughout the
depth of rooms. This represents illuminances greater than 500lux and lower than 2000lux in
the most of the working year. However, window areas greater than 40% led to high
illuminance levels in the exceeding UDI range, which can cause glare to users.
On the other hand, the UDI and DA results for models with geometry of 1:2 did not show
good daylighting performances for window areas smaller than 30%. For models with room
index equal to 5.0, there were not reductions on artificial light consumptions. Window areas
greater than 30% led to high illuminance levels in the exceeding UDI range with lower DA
values in the rear of the rooms.
For the models with geometries of 2:1 and 1:1 with room indices equal to 2.0 and 5.0 the
windows areas related to the maximum potential for electricity savings led to high
illuminance levels in the exceed UDI range. However, the DA values were sufficient higher to
guarantee a reduction on artificial light consumption.
These facts should be considered in the application of the daylighting in buildings. Despite
the potential for electricity savings reached values of up to 50.5%, the high illuminance levels
obtained for most of the analyzed cases may lead to glare. Thus, the use of shading devices
(located in the interior or the exterior of the windows) is needed to control glare, which will
cause a reduction on the potential for electricity savings.
CONCLUSIONS
The potential for electricity savings by using daylighting in commercial buildings located in
Florianópolis was evaluated. In general, it can be concluded that the use of daylighting in
commercial buildings located in Florianópolis presented a potential for electricity savings up
to 50.5%, when compared to buildings using artificial lighting and air-conditioning system.
The daylighting performance analyses through UDI and DA methods showed satisfactory
results. The best daylighting performances were obtained for models with the geometry of 2:1
and 1:1, with a room index equal to 0.8. However, there were cases (large rooms) with high
illuminances levels on the workplane, which can cause glare sensation. Therefore, the use of a
shading device is needed to control glare. As a result, the potential for electricity savings can
be overestimated because the use of shading devices will lead to a reduction in illuminance
levels.

Proceedings: The Second International Conference on Building Energy and Environment 2012
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0
20
40
60
80
100
0.0 0.5 1.0 1.5 2.0 2.5
Depth (m)
Work year (%)
UDI <100 lux
100≤ UDI ≤2000 lux
UDI >2000 lux
DA ≥500 lux
(a) 10% of window area
0
20
40
60
80
100
0.0 0.5 1.0 1.5 2.0 2.5
Depth ( m)
Work year (%)
UDI <100 lux
100≤ UDI ≤2000 lux
UDI >2000 lux
DA ≥500 lux
(b) 20% of window area
0
20
40
60
80
100
0.0 0.5 1.0 1.5 2.0 2.5
Dept h (m)
Work year (%)
UDI <100 lux
100≤ UDI ≤2000 lux
UDI >2000 lux
DA ≥500 lux
(c) 30% of window area
0
20
40
60
80
100
0.0 0.5 1.0 1.5 2.0 2.5
Depth (m)
Work y ear (%)
UDI <100 lux
100≤ UDI ≤2000 lux
UDI >2000 lux
DA ≥500 lux
(d) 40% of window area
0
20
40
60
80
100
0.00.51.01.52.02.5
Depth (m)
Work y ear (%)
UDI <100 lux
100≤ UDI ≤2000 lux
UDI >2000 lux
DA ≥500 lux
(e) 50% of window area
0
20
40
60
80
100
0.0 0.5 1.0 1. 5 2.0 2 .5
Depth ( m)
Work year (%)
UDI <100 lux
100≤ UDI ≤2000 lux
UDI >2000 lux
DA ≥500 lux
(f) 60% of window area
0
20
40
60
80
100
0.0 0.5 1.0 1.5 2.0 2. 5
Depth ( m)
Work y ear (%)
UDI <100 lux
100≤ UDI ≤2000 lux
UDI >2000 lux
DA ≥500 lux
(g) 70% of window area
0
20
40
60
80
100
0.0 0.5 1.0 1.5 2.0 2.5
Depth (m)
Work y ear (%)
UDI <100 lux
100≤ UDI ≤2000 lux
UDI >2000 lux
DA ≥500 lux
(h) 80% of window area
0
20
40
60
80
100
0.00.51.01.52.02.5
Depth (m)
Work y ear (%)
UDI <100 lux
100≤ UDI ≤2000 lux
UDI >2000 lux
DA ≥500 lux
(i) 90% of window area
0
20
40
60
80
100
0.0 0.5 1.0 1.5 2.0 2. 5
Depth (m)
Work y ear (%)
UDI <100 lux
100≤ UDI ≤2000 lux
UDI >2000 lux
DA ≥500 lux
(j) 100% of window area
Figure 1. UDI and DA for model with geometry of 2:1, room index equal to 0.8, north
orientation and ten window areas.

Proceedings: The Second International Conference on Building Energy and Environment 2012
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This work reinforced the good potential for electricity savings by using daylighting in
commercial buildings, as seen in the introduction of this paper. The daylighting strategy is
recommended to be used in commercial buildings, but some considerations can be useful:
 The use of an efficient lighting control device should be used. The correct distribution
of circuits in order to promote a better use of daylighting is also a good alternative;
 The use of daylighting should consider the daylighting performance, by assessing high
illuminance levels that can cause glare;
 The use of shading devices can be needed to control glare and their use should be
evaluated carefully in order to guarantee a good potential for electricity savings.
ACKNOWLEDGEMENT
Ricardo F. Rupp would like to thank CAPES – Fundação Coordenação de Aperfeiçoamento
de Pessoal de Nível Superior, an agency of the Brazilian Government for post-graduate
education, for the scholarship that allowed him to carry out this research.
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