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Semi-transparent PV windows: A study for office buildings in Brazil
Energy and Buildings 67 (2013) 136–142
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Semi-transparent PV windows: A study for office buildings in Brazil Evelise Leite Didoné ∗ , Andreas Wagner Karlsruhe Institute of Technology (KIT) – Building Science Group (fbta), Englerstraße 7, 76131 Karlsruhe, Germany1
a r t i c l e
i n f o
Article history: Received 5 February 2013 Received in revised form 29 July 2013 Accepted 3 August 2013 Keywords: Energy efficiency Semi-transparent photovoltaic window Building simulation
a b s t r a c t This research aims to develop a methodology for the evaluation of the potential energy saving and energy generation of semi-transparent PV windows in Brazilian office buildings. The evaluation is based on computer simulations: a daylighting simulation for the investigation of the available annual daylight with different window systems using Daysim/Radiance program and the simulation of the energetic performance using the program EnergyPlus. The simulations were accomplished for two cities in two different climatic zones of Brazil and compared to a German city. The results show that it is possible to reduce the energy consumption for artificial lighting and air-conditioning using appropriate control systems and furthermore to generate energy using semi-transparent photovoltaic panels in windows. Though only one building geometry was analyzed the results suggest that the potential of this technology is high in Brazil. © 2013 Elsevier B.V. All rights reserved.
1. Introduction The growing consumption of energy in developed and developing countries is becoming an important issue to be faced by the economies of these countries. The percentage of energy consumption of buildings relative to the overall energy use has grown in the last years due to the increasing amount of electrical devices. In Brazil, 48% of the produced electricity is consumed within buildings. This consumption is distributed among the residential, commercial and public buildings. In the case of commercial and public buildings, HVAC (47%) and artificial light (22%) are the main loads [1]. In recent years, semi-transparent BIPV modules have been used as part of the facade for energy efficiency and esthetic considerations. The use of BIPV influences the energy demand for heating, cooling and lighting as well as the thermal and visual comfort inside the building. A BIPV system can replace traditional building materials when integrated into the building envelope and it does not require extra installation space. Some studies have been conducted on semi-transparent PV modules as windows [2–9]. For a building in Tokyo one of the studies showed that energy savings of 54% are possible using semi-transparent PV modules in windows [6]. PV and BIPV are widely used in countries such as Germany, Japan, Spain and the United States. In Brazil they are rarely used up to now [10]. However, due to the large amount of incident solar
∗ Corresponding author. Tel.: +49 72160842178; fax: +49 72160846092. E-mail addresses: [email protected], [email protected] (E. Leite Didoné), [email protected] (A. Wagner). 1 http://fbta.arch.kit.edu 0378-7788/$ – see front matter © 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.enbuild.2013.08.002
radiation, PV systems are very well suited for energy generation in Brazil and they will probably play a significant role in the future energy generation of this country [11–14]. This work evaluates the potential for saving and generating energy in office buildings by the use of semi-transparent photovoltaic panels in windows. Except the presenting the energetic behavior of the semi-transparent PV windows they are compared to other window types used in Brazil to determine the optimal window type for a given climate and orientation. 2. Methodology 2.1. Building model A representative model for Brazilian office buildings was chosen. The building characteristics, materials and internal heat loads were obtained from previous studies [15]. For the simulations a room with a base area of 8 m × 11 m and a height of 2.7 m was used (Figs. 1 and 2). Table 1 presents the summary with the fix variables of the building. An optional automatic dimming system to control artificial lighting was used in some of the simulations. The system turned artificial lighting on or off when daylight reached 500 lx, according to NBR 5413 [16]. Simulations were made for models with different window to wall ratios (WWR) of the main facade: case M1 with WWR < 50%, which represents the most common window size in Brazilian office buildings and case M2 with WWR > 50%, which represents office buildings with large windows (Figs. 1 and 2). For each group five different window systems were analyzed. One is a single glass window with 6 mm thickness that represents
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Fig. 1. Scheme of the model geometry for M1 with WWR < 50% (window area = 8 m2 ). Fig. 3. Schematic of the PV window.
regarded the building as detached and the surrounding was not considered.
Fig. 2. Scheme of the model geometry for M2 with WWR > 50% (window area = 16 m2 ). Table 1 Summary with fix variables [15]. Thermal transmittance [W/m2 K]
Wall Roof
2.47 2.42
Thermal capacity [kJ/(m2 K)]
Wall Roof
200 187
Absorptance
Wall Roof
0.65 0.70
Average occupancy [m2 /person]
14.7
Internal gains [W/m ]
Lighting Equipment
8.0 9.7
Occupation [h]
Occupancy Lighting Equipment
8 am to 6 pm 8 am to 6 pm Schedule
HVAC
Type Set point Cooling capacity [BTU/h] COP [W/W]
Window unit 18–24 ◦ C Autosize 2.8
2
the most common window used in Brazilian office buildings. The other models use a double glazing insulated window (IGU) with different glazing properties (Table 2). All windows have a vinyl frame with a U-value of 1.70 W/(m2 K). For the reference model (base) the single glass window was used. The artificial lighting system was switched on throughout the whole occupation period, no photoelectric sensor or dimming system and no PV window was used. The models were evaluated for the four cardinal orientations: North (0◦ ), East (90◦ ), South (180◦ ) and West (270◦ ). The simulation
2.1.1. Semi-transparent PV window The used semi-transparent PV window consists of a double glazed window with an encapsulated solar cell layer between the glass panes. The window is composed of two glass layers with a thickness of 3 mm separated by an air filled 12 mm wide gap. The PV cell is placed at the inner side of the exterior glass. To increase the photovoltaic performance a low iron solar glass was used for the outside pane. For the interior glazing a low-E coated glass was used to prevent the heat generated by the PV from entering the building (Fig. 3). Two windows with different PV solar cell types were evaluated. One organic solar cell with a cell efficiency of 3% and transmittance of 30% [D] [19] and a Schott ASI® thru solar cell with an efficiency of 5% and a transmittance of 8% [E] [20] (Table 3). The encapsulated PV cell was modeled and applied to the outer glass pane as a thin film within the Optics 6 program. For this purpose the PV was modeled as an applied film. For the modeling of the film itself a file was made with the spectral data of the PV containing the transmittance, front reflectance and back reflectance for different wavelengths. Then, the file was imported into Optics 6 where the thin film could be added to the low iron glass. Finally, the glass with thin film was imported into the WINDOW 7 program where the window system could be modeled and simulated. Both programs are a publicly available computer programs for calculating optical and thermal performance indices of windows systems [17,18]. 2.2. Building locations The simulations were carried out for two Brazilian capital cities, Fortaleza/CE and Florianopolis/SC and compared with the Germany city Frankfurt. These cities were selected based on their geographic location and climatic differences (Table 4). The weather data for the cities were obtained from the website of the U.S. Department of Energy [21]. A study about the temperature and the solar radiation incident on the facades facing the four cardinal orientations (East, North, West and South) was performed to compare the weather characteristics of the three cities [21].
Table 2 Windows’ properties [17,18]. Window
Configuration
U-Factor [W/(m2 K)]
VT
SHGC
[A] Single glass [B] Double glazing [C] Low-E double glazing [D] Organic PV [E] A-SI Thru PV
Clear 6 mm Clear 3 mm/air 12 mm/clear 3 mm Low-E 2# 3 mm/air 12 mm/clear 3 mm Low iron 3 mm/organic PV/air 12 mm/low-E 3# 3 mm Low iron 3 mm/A-SI Thru PV/Air 12 mm/low-E 3# 3 mm
5.82 2.73 1.68 1.67 1.67
0.88 0.81 0.70 0.23 0.09
0.82 0.76 0.40 0.22 0.13
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Table 3 Semi-transparent PV windows layers properties [17–20]. Layer
Thickness [mm]
Conductivity [W/(m K)]
Reflectance (ˇ) [%]
Absorption (ε) [%]
Transmittance () [%]
Efficiency [%]
Glass outside Air gap Glass inside Organic A-SI Thru
3 12 3 0.05 2
1.114 0.024069 1.114 0.24 0.19
8.1 – 42.2 10.0 12.5
1.2 – 16.6 60.0 79.5
90.7 – 41.2 30.0 8.0
– – – 3.0 5.2
Table 4 Geographical positions of the cities. City
Latitude
Longitude
Altitude (m)
Region/country
Fortaleza/CE Florianopolis/SC Frankfurt (Main)
3◦ 78 (S) 27◦ 67 (S) 50◦ 05 (N)
38◦ 53 (W) 48◦ 55 (W) 8◦ 60 (E)
25 5 113
Northeast/Brazil South/Brazil Germany
As the Brazilian cities Fortaleza and Florianopolis are located in the southern hemisphere the winter months are between June and August. In contrast, for the German city Frankfurt, which is located in the northern hemisphere, the winter months are between December and February. Florianopolis, on the southern coast of Brazil, presents temperatures along the year around 20 ◦ C. In the winter months (June–August) the temperatures can be as low as 5 ◦ C. The second city, Fortaleza, is located on the northeast coast. It shows a higher annual average temperature of around 25 ◦ C. Frankfurt, in Germany, presents the largest temperature range of the three cities, ranging from 33 ◦ C in summer to −9 ◦ C in winter. It is interesting to note that the maximum temperatures for the three cities are quite similar. They range only between 30 ◦ C and 35 ◦ C. As shown in Fig. 4, the solar radiation level changes according to the facade orientation. Florianopolis and Fortaleza which are located in the southern hemisphere show a similar behavior but with different radiation levels for the same facade. Frankfurt presents considerably different radiation intensities compared to the Brazilian cities. The West and East facades show similar radiation levels for the three cities, though the annual change is highest in Frankfurt. In Fortaleza the highest radiation values are attained for the West facade, in Florianopolis for the North facade and in Frankfurt for the South facade. In Fig. 4 are shown some exemplary temperature and radiation curves for the three cities. According to Fig. 4, the facades with the highest solar radiation levels and therefore the best orientations for windows with integrated semi-transparent PV are: North in Florianopolis, East and West in Fortaleza and South in Frankfurt. 2.3. Building analyses For the overall energy performance of the building different window system were investigated. The analysis of the building
with integrated PV window was divided into two parts: energy consumption and electricity generation. A scheme of the building energy performance analysis can be seen in Fig. 5. The energy benefits of BIPV systems are based on three effects, electricity saving of the artificial lighting system and the HVAC system and electricity generation from the PV.
2.3.1. Energy consumption For all models the thermal simulations were performed with EnergyPlus which also calculates all electrical consumptions i.e. cooling, heating, equipment and lighting. For the models using an artificial lighting control system the data of Daysim/RADIANCE was used as input for the thermal simulation. This is possible due to the use of the report provided by Daysim/RADIANCE, which provides data for assessing daylight and thus delivers hourly data for the activation of the artificial lighting through an automatic control. In order to determine the daylight present in the work plane, the internal environment was divided into small rectangular, equally sized areas in which the averaged intensity is measured centrally. The so formed grid of measurement points is located on a horizontal surface located 0.75 m above the floor. The measurement points have a spacing of 1.00 m apart from each other and 0.50 m distant from the wall. To determine the incident lighting intensity a photoelectric sensor was placed at all points of the measurement grid. The lighting control system of Daysim/RADIANCE contains a dimming control using a photoelectric sensor. It adjusts the intensity of the artificial lighting system, according to the available daylight, and keeps the lighting level in the environment constant. The lighting is activated by a single on/off switch near the door and the photocell consumes 2 W in standby.
2.3.2. Electricity generation As it is not possible to directly model a semi-transparent PV window in EnergyPlus it was necessary to calculate the electricity generation of the PV cells as well as the total energy consumption separately. Another drawback of EnergyPlus is that there is no possibility to obtain temperatures inside a window. This is important, as for a correct calculation of the generated electricity the PV cell temperature
Fig. 4. Annual behavior of temperature and solar radiation for the three cities.
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Fig. 5. Flowchart for the determination of the building performance.
must be known. Hence some external heat transfer calculations were necessary to determine the PV cell temperature. These were done using the following simplifications. I.e. the window frame and temperature conduction through the window frame are not considered, neither is the heat stored inside. The glass temperature and the temperatures inside the window system are calculated for each time step of the building simulation assuming non-transient conditions for that instant of time. As in EnergyPlus the available daylight as well as the thermal balance should be calculated correctly the window model was adapted. A semi-transparent PV window transmits light, generates heat and electricity. But as it is not possible in EnergyPlus to consider energy with a window the amount of electricity generated from the incident light must be either transformed into a heat gain, transmitted light or reflected light. Transforming it into transmitted light would cause an overestimation of the available daylight inside. Increasing the absorption by the amount of the generated electricity would cause an extra heating up of the window and thus lead to an overestimation of the required cooling energy. Therefore the generated electricity was considered as an additional reflectance of the front surface of the outside glass. Consequently the reflection of the outside glass, as it is used within EnergyPlus is calculated by: EP = + (1 − − ˛)PV
Fig. 6. Detailed scheme for solar radiation balance.
(1)
With EP is reflectance used in EnergyPlus; ˛, glass absorption; PV , solar cell efficiency; and is glass reflection. The reason therefore is: (1 − − ˛) is the normalized fraction of light that reaches the PV and which is partly converted into electricity. The major part of the solar energy is transformed into heat only about 3% will generate electricity for organic solar cell and 5.2% for A-SI Thru – and this fraction is added as additional reflection. As the EnergyPlus simulation fully integrates the heat gains caused by the PV window and gives as output variables the surface temperature of the window (see also Section 2.1.1), the convective heat transfer to the outside and the radiation heat loss to the outside, the calculation of the PV temperature is uncomplicated. Only the heat fluxes and temperatures inside the window system have to be calculated and it is only necessary to calculate the heat fluxes from one direction to the PV as the surface temperature of the outside glass already includes absorptions and heat transfers inside the window. Fig. 6 shows details of the model where the incident solar radiation on the external surface is partially reflected (), transmitted () and absorbed (˛) by the outside glass pane and PV layer. In Fig. 7 the locations where temperatures were calculated and the incoming and outgoing heat transfers used in the equations are shown.
Fig. 7. Detailed scheme for heat transfer.
To calculate the temperature of the PV layer, the temperature inside the outer glass pane has to be calculated by solving the heat balance equations below [8]. From the heat balance of the outside glass surface, given in Eq. (2), the heat transfer into the glass pane, q˙ cond1 , can be calculated. q˙ conv0 + q˙ rad0 + q˙ cond1 = 0
(2)
With the heat transfer out of Eq. (2) the core temperature of the outside glass pane, ϑG , is calculated using Eq. (3), readily rewritten in Eq. (4). q˙ cond1 =
1 (ϑG − ϑs ) R(1/2)glass
(3)
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Fig. 9. PV temperature for window with organic PV. Fig. 8. Energy generated.
ϑG = q˙ cond1 R(1/2)glass + ϑS
(4)
The heat transfer between the outside glass pane and the encapsulated PV, node ϑPV , is determined from the heat balance of the outside glass pane Eq. (5). To solve Eq. (5), for the temperature of the PV layer, the absorbed solar energy in the first glass pane must be calculated using Eq. (6). For the calculation of the absorbed energy the reflection and absorption coefficients of the glass are used. −q˙ cond1 + q˙ cond2 + q˙ abs1 = 0
(5)
q˙ abs1 = q˙ sol (1 − )˛
(6)
Finally the searched PV temperature is calculated by Eq. (7) reformulated in Eq. (8). q˙ cond2 =
1 R(1/2)glass,(1/2)PV
(ϑPV − ϑG )
(7)
ϑPV = R(1/2)glass,(1/2)PV (q˙ cond1 − q˙ abs1 ) + ϑG
(8)
With q˙ conv , is convective heat [W/m2 ]; q˙ rad , radiated heat [W/m2 ]; q˙ cond , heat conduction [W/m2 ]; q˙ abs , absorbed heat [W/m2 ]; ϑS , outside glass surface temperature [◦ C]; ϑG outside glass temperature [◦ C]; ϑPV , solar cell temperature [◦ C]; and R is thermal resistance [(m2 K)/W]. The generated electricity [22] can then be calculated by multiplying the result of (9) by the window area. The temperature coefficient of maximum power output, K, was obtained from the PV manufacturer. The value for organic PV is +0.05%/◦ C and for A-SI Thru is – 0.2%/◦ C [23,24]: q˙ el = q˙ sol (1 − ˛)(1 − )PV [1 + K(ϑPV − 25)]
(9)
[W/m2 ];
q˙ sol , solar radiation With q˙ el is generated electricity [W/m2 ]; ϑPV , solar cell temperature [◦ C]; PV , solar cell efficiency; ˛, glass absorption; , glass reflection; and K is temperature coefficient of maximum power output.
this PV window. In Florianopolis the north facade yields the highest energy generation with 750.3 kWh/year and in Frankfurt the south facade with 591.8 kWh/year, both with the ASI Thru window. In all cases the generated electricity of the M1 office model (window with 8 m2 ) is almost the half as for M2 model (window with 16 m2 ). Fig. 9 shows the annual course of the maximum temperature of the PV window in comparison with Low-E window and the outside temperature. The graphics is for a West facade in Fortaleza where the highest PV temperature with organic PV was obtained. The PV temperature can reach about 69 ◦ C in summer months, which is 35% more than the low-E window temperature and 54% more than the maximal outside temperature of 32 ◦ C. 3.2. Building consumption Figs. 10 and 11 show the energy consumption and savings for the four facades for all models. The five window models were compared with the [base] model in order to compare the used and generated energy. The energy consumption of the installed electrical equipment is not presented in the graphics since the value is 3638.04 kWh/year in all cases. A heating system was integrated in the simulation but it remained unused. In Fortaleza only cooling is required due to the climatic conditions and in Florianopolis the internal gains of the electrical equipment and occupancy were sufficient to heat up the room in winter months. The use of photoelectric sensors and a dimming system to control artificial lighting according to daylight availability resulted in a decrease of the consumed electricity and consequently reduced the HVAC load in all cases compared to the base model. The Brazilian cities presented different total energy consumptions according to the facade orientation. In Florianopolis, the south
3. Results and discussion 3.1. PV energy generation The energy generated by the semi-transparent PV window for the M2 office model is presented in Fig. 8. For all orientations the Brazilian cities show more potential to generate energy with PV windows than the German city. Fortaleza achieves the highest value with both PV window types: 798.6 kWh/year with the ASI Thru PV and 493.6 kWh/year with organic PV. As expected regarding the climatic data, east and west facades present the highest levels of energy generation. According to the higher cell efficiency of the ASI Thru PV in the others cities the highest energy generation was also achieved with
Fig. 10. Energy consumption and savings for the model M2 in Florianopolis.
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Table 5 Classification of the windows’ performance by city and orientation. City
Orientation
Window [A] Single glazing window
[B] Double glazing window
[C] Low-E window
[D] Organic PV window
[E] ASI Thru window
Florianopolis
North East South West
1–2 2 5 2
1–2 1 2 1
3 3 4 3–4
4 4 1 3–4
5 5 3 5
Fortaleza
North East South West
1 1 1 1
3 2 2 2
5 3–4 3–4 3
2 3–4 3–4 4
4 5 5 5
facade showed the lowest final energy consumption although the consumption caused by lighting was highest. This agrees with the expectations as it is the orientation that receives least sunlight due to its geographical location. In Fortaleza, the orientation with the lowest consumption values is north. In general, Fortaleza shows higher total energy consumption than Florianopolis and more electricity is generated by the PV window. But Florianopolis showed a higher percentage of energy saving considering the energy generated and consumed. The window systems caused a different energy consumption behavior of the building. The use of a PV window can save up to 43% of energy. In some cases, the use of a low-E window saves more energy than a PV window, as for the North facade in Fortaleza with an energy saving of 37% against 29%. In others cases the lowE window achieved values similar to the organic PV window [D]. The single glass [A] and double glass [B] windows presented similar energy saving values in most cases. The use of semi-transparent PV windows resulted in an energy saving for HVAC, since the window has a solar transmittance of only 30% and 8%, respectively for [D] and [E] cases. Consequently, less solar radiation enters the building and less cooling energy is required. However, due to the reduced visible transmission the energy consumption for artificial lighting increases. This could be partly compensated using the lighting control system. Fig. 12 shows the influence of the window size on the overall energy consumption for the M1 and M2 case for the North facade in Florianopolis. The window with a WWR < 50% has a higher consumption for lighting since less daylight enters the building, compared to a WWR > 50%. In contrast the bigger window causes a higher consumption for HVAC as more heat reaches the inside. In summary, the windows without PV and a WWR < 50% showed a lower total energy consumption than the ones with a WWR > 50%. Whilst the PV windows with a WWR > 50% lead to a lower overall energy consumption, since the energy generated by PV was two times higher.
Fig. 11. Energy consumption and savings for the model M2 in Fortaleza.
Fig. 12. Energy consumption for the M1 and M2 cases for the North facade in Florianopolis.
A summary classification of the windows performance is presented in Table 5. For the classification, the number 5 represents the best performance and number 1 the worst performance. 4. Conclusion The present work examined the potential of different window systems for energy reductions including daylighting control for office buildings for two Brazilian cities with different climate. Though only one building geometry was analyzed the results suggest that it exists a high potential for this technology in Brazil. The EnergyPlus program is a useful tool for building energy performance analysis in combination with BIPV installations. As semi-transparent photovoltaic windows cannot be simulated directly the generated electrical energy has to be calculated using a spreadsheet program. Finally the combination of EnergyPlus and Daysim/RADIANCE allows an integrated simulation including daylighting analysis by calculating the annual energy consumption with EnergyPlus, using the data created by Daysim. The results demonstrate a considerable potential for solar energy generation in the two Brazilian cities. In Fortaleza more energy was generated than in Florianopolis. But the total energy saving in Florianopolis is with 43% higher than in Fortaleza with 39%. Adapting the building typology and materials according to the climatic characteristics of the building site can reduce energy consumption for lighting and HVAC. Finally, the evaluated window systems show different results according to the facade and the city. The single glass window, which is the most commonly used window type in Brazilian office buildings, showed similar values as the double glass window. The low-E window presented the overall best performance for the South facade in Florianopolis and the North facade in Fortaleza, which are the facades that receive less solar radiation. For the other facades the PV window presented overall best energetic performance.
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Acknowledgement We would like to acknowledge the Research Funding Institution, CAPES, for providing financial support to accomplish this project. References [1] MME, Balanc¸o Energético Nacional (BEN 2010), 2011, Disponível em: http://www.mme.gov.br (acesso em 02.06.11). [2] T.T. Chow, K.F. Fong, H. HE, Z. Lin, A.L.S. Chan, Performance evaluation of a PV ventilated window applying to office building of Hong Kong, Energy and Buildings 39 (2007) 643–650. [3] T.T. Chow, G. Pei, L.S. Chan, Z. Lin, K.F. Fong, A comparative study of PV glazing performance in warm climate, Indoor and Built Environment 18 (2009) 32–40. [4] T.T. Chow, C. Li, Z. Lin, Innovative solar window for cooling-demand climate, Solar Energy Materials & Solar Cells 94 (2010) 212–220. [5] T.Y.Y. Fung, H. Yang, Study on thermal performance of semi-transparent building-integrated photovoltaic glazings, Energy and Buildings 40 (3) (2008) 341–350. [6] T. Miyazaki, A. Akisawa, T. Kashiwagi, Energy savings of office buildings by the use of semi-transparent solar cells for Windows, Renewable Energy 30 (2005) 281–304. [7] J.H. Song, Y.S. An, S.G. Kim, S.J. Lee, J.H. Yoon, Y.K. Choung, Power output analysis of transparent thin-film module in building integrated photovoltaic system (BIPV), Energy and Buildings 40 (2008) 2067–2075. [8] W.P. Wah, Y. Shimoda, M. Nonaka, M. Inoue, M. Mizuno, Field study and modeling of semi-transparent PV in power, thermal and optical aspects, Journal of Asian Architecture and Building Engineering (November) (2005) 556. [9] W.P. Wah, Y. Shimoda, M. Nonaka, M. Inoue, M. Mizuno, Semi-transparent PV: thermal performance, power generation, daylight modelling and energy saving potential in a residential application, Renewable Energy 33 (2008) 1024–1036. [10] S.H.F. Oliveira, Gerac¸ão Distribuída de Eletricidade: inserc¸ão de edificac¸ões fotovoltaicas conectadas à rede no estado de São Paulo. São Paulo, 2002.
[11] M. Ordenes, D.L. Marinoski, P. Braum, R. Rüther, The impact of buildingintegrated photovoltaics on the energy demand of multi-family dwellings in Brazil, Energy and Buildings 39 (2007) 629–642. [12] C. Jardim, R. Rüther, I.T. Salamoni, T.S. Viana, S.H. Rebechi, P.J. Knob, The strategic siting and the roofing area requirements of building-integrated photovoltaic solar energy generators in urban areas in Brazil, Energy and Buildings 40 (2008) 365–370. [13] I.P. Santos, R. Rüther, The potential of building-integrated (BIPV) and buildingapplied photovoltaics (BAPV) in single-family, urban residences at low latitudes in Brazil, Energy and Buildings 50 (2012) 290–297. [14] R. Rüther, Photovoltaics Solar Buildings, Labsolar, Florianópolis, 2004, 114p. (in Portuguese). [15] M.V. Santana, Influence of constructive parameters on energy consumption of office buildings located in Florianopolis-SC. Dissertation, Federal University of Santa Catarina, Florianopolis, 2006, 181p. (in Portuguese). [16] ABNT, NBR-5413 Iluminância de Interiores, Associac¸ão Brasileira de Normas Técnicas, Rio de Janeiro, 1992, 13p. [17] WINDOW 7, LBNL Windows & Daylighting Software, National Fenestration Rating Council (NFRC), 2011. [18] OPTICS 6, LBNL Windows & Daylighting Software, National Fenestration Rating Council (NFRC), 2011. [19] Lichttechnisches Institut – LTI, Karlsruhe University, Personal Information, Germany, 2012. [20] Glassdbase, Schott Solar ASI Thru Laminated, 2012, http://glassdbase.unibas.ch (accessed April 2012). [21] U.S. Department of Energy, Energy Efficiency & Renewable Energy. Weather Data, 2011, http://apps1.eere.energy.gov (accessed December 2011). [22] E. Skoplaki, J.A. Palyvos, On the temperature dependence of photovoltaic module electrical performance: a review of efficiency/power correlations, Solar Energy 83 (2009) 614–624. [23] PolymerSun, Flexible Solar Technology, 2011, http://www.polymeursun.com (accessed November 2011). [24] SCHOTT, ASI Glass with 2 Sub-modules. Technical Data Sheet http://www. schott.com/architecture (accessed November 2011).
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Semi-transparent PV windows: A study for office buildings in Brazil Evelise Leite Didoné ∗ , Andreas Wagner Karlsruhe Institute of Technology (KIT) – Building Science Group (fbta), Englerstraße 7, 76131 Karlsruhe, Germany1
a r t i c l e
i n f o
Article history: Received 5 February 2013 Received in revised form 29 July 2013 Accepted 3 August 2013 Keywords: Energy efficiency Semi-transparent photovoltaic window Building simulation
a b s t r a c t This research aims to develop a methodology for the evaluation of the potential energy saving and energy generation of semi-transparent PV windows in Brazilian office buildings. The evaluation is based on computer simulations: a daylighting simulation for the investigation of the available annual daylight with different window systems using Daysim/Radiance program and the simulation of the energetic performance using the program EnergyPlus. The simulations were accomplished for two cities in two different climatic zones of Brazil and compared to a German city. The results show that it is possible to reduce the energy consumption for artificial lighting and air-conditioning using appropriate control systems and furthermore to generate energy using semi-transparent photovoltaic panels in windows. Though only one building geometry was analyzed the results suggest that the potential of this technology is high in Brazil. © 2013 Elsevier B.V. All rights reserved.
1. Introduction The growing consumption of energy in developed and developing countries is becoming an important issue to be faced by the economies of these countries. The percentage of energy consumption of buildings relative to the overall energy use has grown in the last years due to the increasing amount of electrical devices. In Brazil, 48% of the produced electricity is consumed within buildings. This consumption is distributed among the residential, commercial and public buildings. In the case of commercial and public buildings, HVAC (47%) and artificial light (22%) are the main loads [1]. In recent years, semi-transparent BIPV modules have been used as part of the facade for energy efficiency and esthetic considerations. The use of BIPV influences the energy demand for heating, cooling and lighting as well as the thermal and visual comfort inside the building. A BIPV system can replace traditional building materials when integrated into the building envelope and it does not require extra installation space. Some studies have been conducted on semi-transparent PV modules as windows [2–9]. For a building in Tokyo one of the studies showed that energy savings of 54% are possible using semi-transparent PV modules in windows [6]. PV and BIPV are widely used in countries such as Germany, Japan, Spain and the United States. In Brazil they are rarely used up to now [10]. However, due to the large amount of incident solar
∗ Corresponding author. Tel.: +49 72160842178; fax: +49 72160846092. E-mail addresses: [email protected], [email protected] (E. Leite Didoné), [email protected] (A. Wagner). 1 http://fbta.arch.kit.edu 0378-7788/$ – see front matter © 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.enbuild.2013.08.002
radiation, PV systems are very well suited for energy generation in Brazil and they will probably play a significant role in the future energy generation of this country [11–14]. This work evaluates the potential for saving and generating energy in office buildings by the use of semi-transparent photovoltaic panels in windows. Except the presenting the energetic behavior of the semi-transparent PV windows they are compared to other window types used in Brazil to determine the optimal window type for a given climate and orientation. 2. Methodology 2.1. Building model A representative model for Brazilian office buildings was chosen. The building characteristics, materials and internal heat loads were obtained from previous studies [15]. For the simulations a room with a base area of 8 m × 11 m and a height of 2.7 m was used (Figs. 1 and 2). Table 1 presents the summary with the fix variables of the building. An optional automatic dimming system to control artificial lighting was used in some of the simulations. The system turned artificial lighting on or off when daylight reached 500 lx, according to NBR 5413 [16]. Simulations were made for models with different window to wall ratios (WWR) of the main facade: case M1 with WWR < 50%, which represents the most common window size in Brazilian office buildings and case M2 with WWR > 50%, which represents office buildings with large windows (Figs. 1 and 2). For each group five different window systems were analyzed. One is a single glass window with 6 mm thickness that represents
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Fig. 1. Scheme of the model geometry for M1 with WWR < 50% (window area = 8 m2 ). Fig. 3. Schematic of the PV window.
regarded the building as detached and the surrounding was not considered.
Fig. 2. Scheme of the model geometry for M2 with WWR > 50% (window area = 16 m2 ). Table 1 Summary with fix variables [15]. Thermal transmittance [W/m2 K]
Wall Roof
2.47 2.42
Thermal capacity [kJ/(m2 K)]
Wall Roof
200 187
Absorptance
Wall Roof
0.65 0.70
Average occupancy [m2 /person]
14.7
Internal gains [W/m ]
Lighting Equipment
8.0 9.7
Occupation [h]
Occupancy Lighting Equipment
8 am to 6 pm 8 am to 6 pm Schedule
HVAC
Type Set point Cooling capacity [BTU/h] COP [W/W]
Window unit 18–24 ◦ C Autosize 2.8
2
the most common window used in Brazilian office buildings. The other models use a double glazing insulated window (IGU) with different glazing properties (Table 2). All windows have a vinyl frame with a U-value of 1.70 W/(m2 K). For the reference model (base) the single glass window was used. The artificial lighting system was switched on throughout the whole occupation period, no photoelectric sensor or dimming system and no PV window was used. The models were evaluated for the four cardinal orientations: North (0◦ ), East (90◦ ), South (180◦ ) and West (270◦ ). The simulation
2.1.1. Semi-transparent PV window The used semi-transparent PV window consists of a double glazed window with an encapsulated solar cell layer between the glass panes. The window is composed of two glass layers with a thickness of 3 mm separated by an air filled 12 mm wide gap. The PV cell is placed at the inner side of the exterior glass. To increase the photovoltaic performance a low iron solar glass was used for the outside pane. For the interior glazing a low-E coated glass was used to prevent the heat generated by the PV from entering the building (Fig. 3). Two windows with different PV solar cell types were evaluated. One organic solar cell with a cell efficiency of 3% and transmittance of 30% [D] [19] and a Schott ASI® thru solar cell with an efficiency of 5% and a transmittance of 8% [E] [20] (Table 3). The encapsulated PV cell was modeled and applied to the outer glass pane as a thin film within the Optics 6 program. For this purpose the PV was modeled as an applied film. For the modeling of the film itself a file was made with the spectral data of the PV containing the transmittance, front reflectance and back reflectance for different wavelengths. Then, the file was imported into Optics 6 where the thin film could be added to the low iron glass. Finally, the glass with thin film was imported into the WINDOW 7 program where the window system could be modeled and simulated. Both programs are a publicly available computer programs for calculating optical and thermal performance indices of windows systems [17,18]. 2.2. Building locations The simulations were carried out for two Brazilian capital cities, Fortaleza/CE and Florianopolis/SC and compared with the Germany city Frankfurt. These cities were selected based on their geographic location and climatic differences (Table 4). The weather data for the cities were obtained from the website of the U.S. Department of Energy [21]. A study about the temperature and the solar radiation incident on the facades facing the four cardinal orientations (East, North, West and South) was performed to compare the weather characteristics of the three cities [21].
Table 2 Windows’ properties [17,18]. Window
Configuration
U-Factor [W/(m2 K)]
VT
SHGC
[A] Single glass [B] Double glazing [C] Low-E double glazing [D] Organic PV [E] A-SI Thru PV
Clear 6 mm Clear 3 mm/air 12 mm/clear 3 mm Low-E 2# 3 mm/air 12 mm/clear 3 mm Low iron 3 mm/organic PV/air 12 mm/low-E 3# 3 mm Low iron 3 mm/A-SI Thru PV/Air 12 mm/low-E 3# 3 mm
5.82 2.73 1.68 1.67 1.67
0.88 0.81 0.70 0.23 0.09
0.82 0.76 0.40 0.22 0.13
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Table 3 Semi-transparent PV windows layers properties [17–20]. Layer
Thickness [mm]
Conductivity [W/(m K)]
Reflectance (ˇ) [%]
Absorption (ε) [%]
Transmittance () [%]
Efficiency [%]
Glass outside Air gap Glass inside Organic A-SI Thru
3 12 3 0.05 2
1.114 0.024069 1.114 0.24 0.19
8.1 – 42.2 10.0 12.5
1.2 – 16.6 60.0 79.5
90.7 – 41.2 30.0 8.0
– – – 3.0 5.2
Table 4 Geographical positions of the cities. City
Latitude
Longitude
Altitude (m)
Region/country
Fortaleza/CE Florianopolis/SC Frankfurt (Main)
3◦ 78 (S) 27◦ 67 (S) 50◦ 05 (N)
38◦ 53 (W) 48◦ 55 (W) 8◦ 60 (E)
25 5 113
Northeast/Brazil South/Brazil Germany
As the Brazilian cities Fortaleza and Florianopolis are located in the southern hemisphere the winter months are between June and August. In contrast, for the German city Frankfurt, which is located in the northern hemisphere, the winter months are between December and February. Florianopolis, on the southern coast of Brazil, presents temperatures along the year around 20 ◦ C. In the winter months (June–August) the temperatures can be as low as 5 ◦ C. The second city, Fortaleza, is located on the northeast coast. It shows a higher annual average temperature of around 25 ◦ C. Frankfurt, in Germany, presents the largest temperature range of the three cities, ranging from 33 ◦ C in summer to −9 ◦ C in winter. It is interesting to note that the maximum temperatures for the three cities are quite similar. They range only between 30 ◦ C and 35 ◦ C. As shown in Fig. 4, the solar radiation level changes according to the facade orientation. Florianopolis and Fortaleza which are located in the southern hemisphere show a similar behavior but with different radiation levels for the same facade. Frankfurt presents considerably different radiation intensities compared to the Brazilian cities. The West and East facades show similar radiation levels for the three cities, though the annual change is highest in Frankfurt. In Fortaleza the highest radiation values are attained for the West facade, in Florianopolis for the North facade and in Frankfurt for the South facade. In Fig. 4 are shown some exemplary temperature and radiation curves for the three cities. According to Fig. 4, the facades with the highest solar radiation levels and therefore the best orientations for windows with integrated semi-transparent PV are: North in Florianopolis, East and West in Fortaleza and South in Frankfurt. 2.3. Building analyses For the overall energy performance of the building different window system were investigated. The analysis of the building
with integrated PV window was divided into two parts: energy consumption and electricity generation. A scheme of the building energy performance analysis can be seen in Fig. 5. The energy benefits of BIPV systems are based on three effects, electricity saving of the artificial lighting system and the HVAC system and electricity generation from the PV.
2.3.1. Energy consumption For all models the thermal simulations were performed with EnergyPlus which also calculates all electrical consumptions i.e. cooling, heating, equipment and lighting. For the models using an artificial lighting control system the data of Daysim/RADIANCE was used as input for the thermal simulation. This is possible due to the use of the report provided by Daysim/RADIANCE, which provides data for assessing daylight and thus delivers hourly data for the activation of the artificial lighting through an automatic control. In order to determine the daylight present in the work plane, the internal environment was divided into small rectangular, equally sized areas in which the averaged intensity is measured centrally. The so formed grid of measurement points is located on a horizontal surface located 0.75 m above the floor. The measurement points have a spacing of 1.00 m apart from each other and 0.50 m distant from the wall. To determine the incident lighting intensity a photoelectric sensor was placed at all points of the measurement grid. The lighting control system of Daysim/RADIANCE contains a dimming control using a photoelectric sensor. It adjusts the intensity of the artificial lighting system, according to the available daylight, and keeps the lighting level in the environment constant. The lighting is activated by a single on/off switch near the door and the photocell consumes 2 W in standby.
2.3.2. Electricity generation As it is not possible to directly model a semi-transparent PV window in EnergyPlus it was necessary to calculate the electricity generation of the PV cells as well as the total energy consumption separately. Another drawback of EnergyPlus is that there is no possibility to obtain temperatures inside a window. This is important, as for a correct calculation of the generated electricity the PV cell temperature
Fig. 4. Annual behavior of temperature and solar radiation for the three cities.
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Fig. 5. Flowchart for the determination of the building performance.
must be known. Hence some external heat transfer calculations were necessary to determine the PV cell temperature. These were done using the following simplifications. I.e. the window frame and temperature conduction through the window frame are not considered, neither is the heat stored inside. The glass temperature and the temperatures inside the window system are calculated for each time step of the building simulation assuming non-transient conditions for that instant of time. As in EnergyPlus the available daylight as well as the thermal balance should be calculated correctly the window model was adapted. A semi-transparent PV window transmits light, generates heat and electricity. But as it is not possible in EnergyPlus to consider energy with a window the amount of electricity generated from the incident light must be either transformed into a heat gain, transmitted light or reflected light. Transforming it into transmitted light would cause an overestimation of the available daylight inside. Increasing the absorption by the amount of the generated electricity would cause an extra heating up of the window and thus lead to an overestimation of the required cooling energy. Therefore the generated electricity was considered as an additional reflectance of the front surface of the outside glass. Consequently the reflection of the outside glass, as it is used within EnergyPlus is calculated by: EP = + (1 − − ˛)PV
Fig. 6. Detailed scheme for solar radiation balance.
(1)
With EP is reflectance used in EnergyPlus; ˛, glass absorption; PV , solar cell efficiency; and is glass reflection. The reason therefore is: (1 − − ˛) is the normalized fraction of light that reaches the PV and which is partly converted into electricity. The major part of the solar energy is transformed into heat only about 3% will generate electricity for organic solar cell and 5.2% for A-SI Thru – and this fraction is added as additional reflection. As the EnergyPlus simulation fully integrates the heat gains caused by the PV window and gives as output variables the surface temperature of the window (see also Section 2.1.1), the convective heat transfer to the outside and the radiation heat loss to the outside, the calculation of the PV temperature is uncomplicated. Only the heat fluxes and temperatures inside the window system have to be calculated and it is only necessary to calculate the heat fluxes from one direction to the PV as the surface temperature of the outside glass already includes absorptions and heat transfers inside the window. Fig. 6 shows details of the model where the incident solar radiation on the external surface is partially reflected (), transmitted () and absorbed (˛) by the outside glass pane and PV layer. In Fig. 7 the locations where temperatures were calculated and the incoming and outgoing heat transfers used in the equations are shown.
Fig. 7. Detailed scheme for heat transfer.
To calculate the temperature of the PV layer, the temperature inside the outer glass pane has to be calculated by solving the heat balance equations below [8]. From the heat balance of the outside glass surface, given in Eq. (2), the heat transfer into the glass pane, q˙ cond1 , can be calculated. q˙ conv0 + q˙ rad0 + q˙ cond1 = 0
(2)
With the heat transfer out of Eq. (2) the core temperature of the outside glass pane, ϑG , is calculated using Eq. (3), readily rewritten in Eq. (4). q˙ cond1 =
1 (ϑG − ϑs ) R(1/2)glass
(3)
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Fig. 9. PV temperature for window with organic PV. Fig. 8. Energy generated.
ϑG = q˙ cond1 R(1/2)glass + ϑS
(4)
The heat transfer between the outside glass pane and the encapsulated PV, node ϑPV , is determined from the heat balance of the outside glass pane Eq. (5). To solve Eq. (5), for the temperature of the PV layer, the absorbed solar energy in the first glass pane must be calculated using Eq. (6). For the calculation of the absorbed energy the reflection and absorption coefficients of the glass are used. −q˙ cond1 + q˙ cond2 + q˙ abs1 = 0
(5)
q˙ abs1 = q˙ sol (1 − )˛
(6)
Finally the searched PV temperature is calculated by Eq. (7) reformulated in Eq. (8). q˙ cond2 =
1 R(1/2)glass,(1/2)PV
(ϑPV − ϑG )
(7)
ϑPV = R(1/2)glass,(1/2)PV (q˙ cond1 − q˙ abs1 ) + ϑG
(8)
With q˙ conv , is convective heat [W/m2 ]; q˙ rad , radiated heat [W/m2 ]; q˙ cond , heat conduction [W/m2 ]; q˙ abs , absorbed heat [W/m2 ]; ϑS , outside glass surface temperature [◦ C]; ϑG outside glass temperature [◦ C]; ϑPV , solar cell temperature [◦ C]; and R is thermal resistance [(m2 K)/W]. The generated electricity [22] can then be calculated by multiplying the result of (9) by the window area. The temperature coefficient of maximum power output, K, was obtained from the PV manufacturer. The value for organic PV is +0.05%/◦ C and for A-SI Thru is – 0.2%/◦ C [23,24]: q˙ el = q˙ sol (1 − ˛)(1 − )PV [1 + K(ϑPV − 25)]
(9)
[W/m2 ];
q˙ sol , solar radiation With q˙ el is generated electricity [W/m2 ]; ϑPV , solar cell temperature [◦ C]; PV , solar cell efficiency; ˛, glass absorption; , glass reflection; and K is temperature coefficient of maximum power output.
this PV window. In Florianopolis the north facade yields the highest energy generation with 750.3 kWh/year and in Frankfurt the south facade with 591.8 kWh/year, both with the ASI Thru window. In all cases the generated electricity of the M1 office model (window with 8 m2 ) is almost the half as for M2 model (window with 16 m2 ). Fig. 9 shows the annual course of the maximum temperature of the PV window in comparison with Low-E window and the outside temperature. The graphics is for a West facade in Fortaleza where the highest PV temperature with organic PV was obtained. The PV temperature can reach about 69 ◦ C in summer months, which is 35% more than the low-E window temperature and 54% more than the maximal outside temperature of 32 ◦ C. 3.2. Building consumption Figs. 10 and 11 show the energy consumption and savings for the four facades for all models. The five window models were compared with the [base] model in order to compare the used and generated energy. The energy consumption of the installed electrical equipment is not presented in the graphics since the value is 3638.04 kWh/year in all cases. A heating system was integrated in the simulation but it remained unused. In Fortaleza only cooling is required due to the climatic conditions and in Florianopolis the internal gains of the electrical equipment and occupancy were sufficient to heat up the room in winter months. The use of photoelectric sensors and a dimming system to control artificial lighting according to daylight availability resulted in a decrease of the consumed electricity and consequently reduced the HVAC load in all cases compared to the base model. The Brazilian cities presented different total energy consumptions according to the facade orientation. In Florianopolis, the south
3. Results and discussion 3.1. PV energy generation The energy generated by the semi-transparent PV window for the M2 office model is presented in Fig. 8. For all orientations the Brazilian cities show more potential to generate energy with PV windows than the German city. Fortaleza achieves the highest value with both PV window types: 798.6 kWh/year with the ASI Thru PV and 493.6 kWh/year with organic PV. As expected regarding the climatic data, east and west facades present the highest levels of energy generation. According to the higher cell efficiency of the ASI Thru PV in the others cities the highest energy generation was also achieved with
Fig. 10. Energy consumption and savings for the model M2 in Florianopolis.
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Table 5 Classification of the windows’ performance by city and orientation. City
Orientation
Window [A] Single glazing window
[B] Double glazing window
[C] Low-E window
[D] Organic PV window
[E] ASI Thru window
Florianopolis
North East South West
1–2 2 5 2
1–2 1 2 1
3 3 4 3–4
4 4 1 3–4
5 5 3 5
Fortaleza
North East South West
1 1 1 1
3 2 2 2
5 3–4 3–4 3
2 3–4 3–4 4
4 5 5 5
facade showed the lowest final energy consumption although the consumption caused by lighting was highest. This agrees with the expectations as it is the orientation that receives least sunlight due to its geographical location. In Fortaleza, the orientation with the lowest consumption values is north. In general, Fortaleza shows higher total energy consumption than Florianopolis and more electricity is generated by the PV window. But Florianopolis showed a higher percentage of energy saving considering the energy generated and consumed. The window systems caused a different energy consumption behavior of the building. The use of a PV window can save up to 43% of energy. In some cases, the use of a low-E window saves more energy than a PV window, as for the North facade in Fortaleza with an energy saving of 37% against 29%. In others cases the lowE window achieved values similar to the organic PV window [D]. The single glass [A] and double glass [B] windows presented similar energy saving values in most cases. The use of semi-transparent PV windows resulted in an energy saving for HVAC, since the window has a solar transmittance of only 30% and 8%, respectively for [D] and [E] cases. Consequently, less solar radiation enters the building and less cooling energy is required. However, due to the reduced visible transmission the energy consumption for artificial lighting increases. This could be partly compensated using the lighting control system. Fig. 12 shows the influence of the window size on the overall energy consumption for the M1 and M2 case for the North facade in Florianopolis. The window with a WWR < 50% has a higher consumption for lighting since less daylight enters the building, compared to a WWR > 50%. In contrast the bigger window causes a higher consumption for HVAC as more heat reaches the inside. In summary, the windows without PV and a WWR < 50% showed a lower total energy consumption than the ones with a WWR > 50%. Whilst the PV windows with a WWR > 50% lead to a lower overall energy consumption, since the energy generated by PV was two times higher.
Fig. 11. Energy consumption and savings for the model M2 in Fortaleza.
Fig. 12. Energy consumption for the M1 and M2 cases for the North facade in Florianopolis.
A summary classification of the windows performance is presented in Table 5. For the classification, the number 5 represents the best performance and number 1 the worst performance. 4. Conclusion The present work examined the potential of different window systems for energy reductions including daylighting control for office buildings for two Brazilian cities with different climate. Though only one building geometry was analyzed the results suggest that it exists a high potential for this technology in Brazil. The EnergyPlus program is a useful tool for building energy performance analysis in combination with BIPV installations. As semi-transparent photovoltaic windows cannot be simulated directly the generated electrical energy has to be calculated using a spreadsheet program. Finally the combination of EnergyPlus and Daysim/RADIANCE allows an integrated simulation including daylighting analysis by calculating the annual energy consumption with EnergyPlus, using the data created by Daysim. The results demonstrate a considerable potential for solar energy generation in the two Brazilian cities. In Fortaleza more energy was generated than in Florianopolis. But the total energy saving in Florianopolis is with 43% higher than in Fortaleza with 39%. Adapting the building typology and materials according to the climatic characteristics of the building site can reduce energy consumption for lighting and HVAC. Finally, the evaluated window systems show different results according to the facade and the city. The single glass window, which is the most commonly used window type in Brazilian office buildings, showed similar values as the double glass window. The low-E window presented the overall best performance for the South facade in Florianopolis and the North facade in Fortaleza, which are the facades that receive less solar radiation. For the other facades the PV window presented overall best energetic performance.
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