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Experimental and numerical investigation on the performance of amorphous silicon photovoltaics window in East China
Building and Environment 46 (2011) 363e369
Contents lists available at ScienceDirect
Building and Environment journal homepage: www.elsevier.com/locate/buildenv
Experimental and numerical investigation on the performance of amorphous silicon photovoltaics window in East China Wei He*, Y.X. Zhang, Wei Sun, J.X. Hou, Q.Y. Jiang, Jie Ji Dept. of Thermal Science and Energy Engineering, University of Science and Technology of China, Hefei 230026, China
a r t i c l e i n f o
a b s t r a c t
Article history: Received 29 April 2010 Received in revised form 20 July 2010 Accepted 30 July 2010
Experiments in a comparable hot-box have been carried out for the study of the thermal performance and power generation of a double-glazing window system integrated with amorphous silicon (a-Si) photovoltaic (PV) cells in Hefei, east region of China. Compared to PV single-glazing window, the indoor heat gain of PV double-glazing window is reduced to 46.5% based on experiment data. The electric efficiencies are both about 3.65% with packing factor 0.8 of PV single-glazing window and PV doubleglazing window. The numerical simulation with computational fluid dynamics (CFD) method has been performed for the prediction of air flow and thermal performance of PV double-glass window. The temperature distribution and thermal performance predicted by the CFD model are in good agreement with the experimental data. Compared between the experimental and numerical results, temperature differences of PV modules are only 1.7% and 1.1% for PV double-glazing and PV single-glazing window, respectively. Because of the much lower inner surface temperature of PV double-glazing window compared with that of PV single-glazing window, the predicted mean vote (PMV) of the office work stage area with PV double-glazing window is well improved. Ó 2010 Elsevier Ltd. All rights reserved.
Keywords: Photovoltaic double-glazing window Thermal and electrical performance Predicted mean vote East China
1. Introduction The application of Photovoltaic technology in buildings has attracted worldwide attention for energy savings and environmental side-effect reductions. Y. Etzion and E. Erell proposed a reversible glazing system that can control transmission of solar radiation into indoor spaces [1]. Brinkworth, B.J. and Cross, B.M. et al. [2] indicated that a ventilated air duct behind a PV panel can decrease temperature of PV cell. CFD package was used to simulate the air flow behind the PV panel and good results were obtained. T.T chow [3] investigated the performance of a PV ventilated window applied to office building of Hong Kong by numerical simulations. With the transmittance of PV window in the range of 0.45e0.55, the electricity consumption was found reduced by 55% compared to the single-glazed window without lighting control. Various numerical investigations of PV ventilated windows with different structures had been carried out to evaluate the thermal loads, daylight contribution and electricity production by Remi C, Geun Y.N [4,5], and so on. Gan and Riffat [6] showed that CFD was a useful tool to optimize ventilation systems for comfortable indoor environment and effective cooling of PV. By studying the factors affecting the local
* Corresponding author. Tel.: þ86 0551 3601641. E-mail address: [email protected] (W. He). 0360-1323/$ e see front matter Ó 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.buildenv.2010.07.030
and average heat transfer coefficients along the vertical surfaces of a see-through glazing system with PV cells, Jun Han [7] did some research on the convective flow strength and heat transfer variation in the ventilation duct. However, there was little report about the performance and PMV analyses of PV window in mainland China. In this paper, the experiment with a comparable hot-box has been carried out in Hefei (N31.8 , E117.3 , east region of China), to study the thermal performance and electrical generation of a double-glazing window system integrated with amorphous silicon cells. Hefei city locates in subtropical climate region, and the annual horizontal solar radiation is about 5000 MJ/m2. The numerical investigation of the performance of PV window system has also been carried out by computational fluid dynamics (CFD) method. 2. Comparable hot-box and experiments 2.1. Comparable hot-box and a-Si PV windows The PV single-glazing window, as shown in Fig. 1b, is just a window which consists of single amorphous silicon (a-Si) PV glazing. And the PV double-glazing window system, as shown in Figs. 1a and 4, consists of an amorphous silicon (a-Si) PV panel and a clear backing glazing. There are ventilated openings at the top and bottom of the semi-transparent a-Si PV glazing, and the PV glazing
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Fig. 1. Schematic structure diagram of the office rooms integrated with a PV double-glass window system. (a) PV double-glazing window, (b) PV single-glazing window.
provides shading and electricity for the room. In summer, with the semi-transparent a-Si PV glazing facing outward, the PV glazing absorbs solar radiation and reduces the penetration of solar radiation into the office room. Part of solar energy absorbed is converted into electrical energy, the other is converted into thermal energy and heats the air in the ventilation gap behind the PV panel. No mechanical ventilated system is provided for the window system. The upward air flow is driven by thermal buoyancy, and a temperature gradient is along the height of the air gap. This window system also has one advantage that the scenery outside can be seen from the inside while it could not be seen from the outside, as showed in Fig. 3. The plan view of the test rig with the window systems is shown in Fig. 2. The dimensions of both rooms are 2.80 m (height) 3.00 m (width) 3.00 m (length). The thickness of room walls is 0.10 m. One of the offices has a double-glazing window integrated semi-transparent a-Si PV cells, and the other has a PV singleglazing window. The two PV windows are both fixed on the south wall. The air-conditioning system inside the comparable hot-box keeps temperature of the corridor and the test office rooms at a constant as 25 0.5 C. Fig. 3 is the photo of the test rig of hot-box integrated a-Si PV window systems. The two PV windows both have a width of 1.2 m and a height of 1.15 m. The thickness of semi-transparent a-Si PV panel and clear glazing is 7 mm and 6 mm, respectively. The air gap in the PV double-glazing window is of 20 mm. The ventilated openings
have a width of 120 mm and a height of 6 mm. As seen in Fig. 3, the PV panel is comprised of three PV modules with size of 1110mm 333 mm, which are manufactured by one company of China. The packing factor of PV cells on the semi-transparent PV modules is of 0.8. The characteristics of the PV module are shown in Table 1. Because of packing factor of 0.8, the electrical efficiency is 3.65% and is lower than that of standard production of 5.5%. 2.2. Experiments The two office rooms were tested at the same time under good weather conditions. Eleven thermocouples were fixed on the glazing surfaces of two PV windows to analyze the temperature distribution and the variation of heat transfer. Two thermocouples are arranged at the openings of PV double-glazing window to measure the inlet and outlet temperature. There were a pyranometer and a thermocouple outdoor used to measure irradiance normal to the plane of the PV cell and outdoor ambient temperature, respectively. The room temperatures of two office rooms were monitored by two thermocouples. All the thermocouples were connected to Data Acquisition/Switch Unit 34901A to record the data. All the experiments were performed from 9:00 am to 17:00 pm which conformed to the office hours in China in summer. PV efficiency (hpv) is an important index to evaluate the performance of PV cells, as
Fig. 2. Schematic planform of environmental hot-box.
W. He et al. / Building and Environment 46 (2011) 363e369
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Fig. 3. Double-glazing window system integrated with semi-transparent amorphous silicon (a-Si) PV modules.
hpv ¼
U$I G$Ac
(1)
Where U is voltage of PV modules, voltage; I is current of PV modules, ampere; G is vertical irradiance to the south, W/m2; Ac is area of PV modules, m2. The PV window system plays an important role in modifying solar radiation and heat transmission to the inside of the building. , Meanwhile, the total heat gain from window system (Q) has a great impact on the indoor thermal comfort and cooling load. In summer, the cooling load also increases and the indoor thermal comfort decreases, as a result of the increasing heat gain from window system. , Q ¼ G$A$s þ hr;gw þ hc;gi AðT Ta Þ
(2)
Where A is area of window system, m2; s is effective transmittance of window system; T and Ta are interior surface temperature of window system and indoor air temperature of office room respectively, C; hc,gi is convective heat transfer coefficient between glazing and indoor air, W/m2K; hr,gw is radiative heat transfer coefficient between glazing and interior wall, W/m2K. The temperature difference between window and interior walls leads to asymmetrical thermal radiation and variety thermal comfort level. The index termed predicted mean vote (PMV) is used to evaluate the indoor thermal comfort level, and it is expressed by [8]:
n PMV ¼ 0:303e0:036M þ 0:028 ðM WÞ 3:05 103 ½5733 6:99ðM WÞ pa 0:42½ðM WÞ 58:15 1:7 105 Mð5867 pa Þ 0:0014Mð34 ta Þ 3:96 h o 4 i 108 fcl ðtcl þ 273Þ4 t r þ 273 fcl hc ðtcl ta Þ ð3Þ Table 1 Characteristics of a PV module. Open circuit voltage 41.98 V Short circuit current 0.553 A Power efficiency 3.65% in standard condition
PV packing factor 0.8 Power rating 10.8 W Temperature coefficient 0.1%
Where M is rate of metabolic heat production, W; W is rate of mechanical work accomplished, W; ta is indoor temperature, C; pa is water vapor pressure of indoor air, Pa; tcl is surface temperature of clothing, C; fcl is clothing area factor; t r is weighted surface radiant temperature, C; hc is convective heat transfer coefficient between body and indoor air, W/m2; The expressions of tcl, hc, fcl, t r are given in Appendix. 3. Numerical simulation 3.1. Simulation program The computational fluid dynamics (CFD) was employed to study the performance of PV windows. A general-purpose commercial CFD software FLUENT was applied to calculate the air flow and temperature distribution of the office rooms. The pre-processor software GAMBIT was adopted in the simulate work. The physical, vertical irradiance and temperature date obtained from the experiment of PV window system were used as input parameters into the simulation. 3.2. CFD modelling The FLUENT package was used in modelling the ventilation by solving the conservation equations for mass, momentum and energy with the finite volume method. Previous studies have suggested that the renormalization group (RNG) k-epsilon turbulence model [9] performs better than other turbulence model in the prediction of indoor air flow [10]. Therefore, the RNG k-epsilon turbulence model was adopted to simulate the effect of turbulence of air flow as air flow in PV double-glazing window system. In order to simulate the effect of buoyancy, the Boussinesq model, in which the fluid density was taken as a function of temperature, was used. The discrete transfer radiation model [11] was used to evaluate the radiative heat transfer of the office interior surfaces, which were assumed to be gray. To simplify the simulation of PV windows, it was assumed that fresh air flowed into office room from an inlet opening in the ceiling and out of office room via an outlet opening in the north wall. The inlet opening of 0.2 m width was located at the center of the ceilings, 1.4 m to the
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north wall, and the extract opening of 0.15 m high was located near top of the north wall. All the boundaries of the two office rooms were modeled as adiabatic no-slip wall boundaries, except the ventilation openings. When a-Si PV modules operated, most of the solar irradiation absorbed by them was converted into heat energy, so the temperature of PV modules increased. As a result of the low temperature coefficient of a-Si PV module, the energy that solar irradiation was converted into heat was almost the same as what it used to be. Therefore, the semi-transparent a-Si PV modules could be assumed as a constant heat source. Because of the symmetry of the office, a two-dimensional model was used to simplify the simulation of the office’s ventilation and thermal performance to reduce computational time. This would imply no air flow or heat transfer through the side walls. The air flow inside PV double-glazing window system is affected by heat conduction, convective and radiative heat transfer. The first-order upwind discretization scheme was used in the simulation modelling. A nonuniform computational grid was used for the prediction of two-dimensional flow in the office rooms. Convergence was considered to have been reached when the residuals of energy equation were less than 1e-6, and the residuals of other equations were by less than 103. 4. Performance evaluation The experiment was conducted in the summer of 2009, and lasted for more than one month. The experimental data of September 22 was selected as a typical sample to analyze the performance of PV window systems. Fig. 4 shows the ambient temperature and incident irradiation on south façade from 9:00 am and 17:00 pm in September 22. They were used in computer simulation as the boundary conditions. 4.1. Heat gain and energy saving Figs. 5 and 6 show second heat gain and total heat gain from PV double-glazing window and PV single-glazing window from 9:00 am to 17:00 pm respectively. The total heat gain can be divided into second heat gain and direct heat gain from solar irradiation. The second heat gain is the combination of the convective and infrared radiative heat transfer between glazing and the indoor space, which is represented by the second right item in Eq. (2). The direct heat gain is the solar radiation transmitted from the window system, which is represented by the first right item in Eq. (2).
Fig. 4. Ambient temperature and vertical irradiation of south façade.
Fig. 5. Second heat gain from the two windows. solid quadrel: Second heat gain from PV double-glazing window (exp); open quadrel: Second heat gain from PV doubleglazing window (num); solid circle: Second heat gain from PV single-glazing window (exp); open circle: Second heat gain from PV single-glazing window (num); cross symbol line: solar irradiation.
As is shown in Figs. 5 and 6, the trend of total heat gain is basically the same as that of second heat gain. The direct heat gain of PV single-glazing window is 20% higher than that of PV doubleglazing window. But the direct heat gain from solar irradiation only occupies a small part of total heat gain. Therefore, second heat gains from window systems have a decisive impact on total heat gains. The predicted mean second and total heat gains are close to the measured values. In the morning, the predicted mean values are a little more than the measured ones, while they are a little less than the measured ones in the afternoon. The difference between experiment and numerical simulation could due to the twodimensional flow simulation to three-dimensional flow in fact. The average heat gain and temperature of PV modules from 9:00 to 17:00 from experiments and numerical simulation are given in Table 2. The average measured heat gains are all a little larger than predicted. The average measured second heat gain from double-
Fig. 6. Total heat gain from the two windows. solid quadrel: total heat gain from PV double-glazing window (exp); open quadrel: total heat gain from PV double-glazing window (num); solid circle: total heat gain from PV single-glazing window (exp); open circle: total heat gain from PV single-glazing window (num); cross symbol line: solar irradiation.
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Table 2 Average indoor heat gain and temperature of PV modules (9:00e17:00 h). Construction
Second heat gain (W) Total heat gain (W) Temperature of PV modules ( C)
PV double-glazing window
PV single-glazing window
Experimental
Numerical
Difference
Experimental
Numerical
Difference
51.8 78.3 36.1
46 70.2 36.7
12.6% 11.5% 1.7%
113.2 146.3 37.1
112.1 142.3 36.7
1.0% 2.7% 1.1%
glazing window is about 51.8 W, and it is 12.6% larger than the average predicted value which is 46 W. The average measured total heat gain from double-glazing window is 78.3 W, and is 11.5% larger than the predicted. For the single-glazing window, the difference of second heat gain between experimental and numerical data is 1.0% and that of total heat gain is 2.8%. According to the experimental data, second and total heat gain of PV double-glazing window are 45.8% and 53.5% of that of PV single-glazing window, respectively, and the values are 41.0% and 49.3% respectively from simulation results. It indicates that PV double-glazing window can effectively reduce indoor heat gain and air-conditioning load, compared with PV single-glazing window. The better thermal performance of PV double-glazing window is due to its ventilated openings at the top and bottom, which improves the thermal resistance of PV window significantly. As seen from Figs. 5 and 6, the second heat gain and total heat gain were affected by incident solar irradiation and ambient temperature significantly. There is a time lag of the effect of solar irradiation on second and total heat gains. When the incident irradiation reaches the peak at about 12:00, second, total heat gains are still in the upswing. On the other hand, the downward trend of second and total heat gains is not as sharp as that of incident solar irradiation in the afternoon, due to the impact of ambient temperature.
Fig. 7 gives the temperature distributions of different glazing at 12:00 from the simulation and experiment. The temperatures of
experiment and simulation are close to each other except that of the bottom. At the bottom of clear glazing of PV double-glazing window, the difference between experimental and calculated temperature is about 3 C. This could be due to the relative low Rayleigh numbers in the air gap of PV double-glazing window, according to the RNG -epsilon turbulence model. Fig. 8 shows the variety of glazing temperature from 9:00 to 17:00. Experimental data and numerical simulation data of glazing temperature are basically consistent. The experimental PV temperature of single-glazing window keeps a little higher than that of PV double-glazing, and this could be due to the enhanced heat transfer coefficient in the ventilation construction. The increasing of PV cells temperature has a negative influence on the performance of electrical power. Therefore, PV double-glazing window is better for the operation of PV modules. The position at 0.75 m from floor level, 1 m from window and 1.5 m from nearby side wall is chosen as the reference one normally where the office work stage zone is. And indoor relative humidity is assumed to be 40%, M is 58.15 W/m2, Icl is 0.6, Fg and Fwall are both 0.5. Then the daily variation of PMV of the office work stage zone with PV single-glazing window and PV double-glazing window based on experimental data are showed in Fig. 9. The PMV of the office work stage zone with PV single-glazing window varies between 1.4 and 2.6, and this index means that the thermal sensation of person is warm or even hot. As the inner surface temperature of clear glass is much lower than that of PV single-glazing, the PMV of the office work stage area with PV double-glazing window varies between 0.9 and 1.7, i.e. the thermal sensation of person is mostly kept in the band between neutral and slightly warm.
Fig. 7. Glazing temperature distribution of different glazing at 12:00. solid circle: PV models of PV single-glazing window (num); open circle: PV models of PV singleglazing window (exp); solid triangle: PV models of PV double-glazing window (num); open quadrel: PV models of PV double-glazing window (exp); solid square: clear glass of PV double-glazing window (num); open square: clear glass of PV double-glazing window (exp).
Fig. 8. Glazing temperature of different glazing. solid circle: PV models of PV singleglazing window (num); open circle: PV models of PV single-glazing window (exp); solid triangle: PV models of PV double-glazing window (num); open quadrel: PV models of PV double-glazing window (exp); solid square: clear glass of PV doubleglazing window (num); open square: clear glass of PV double-glazing window (exp).
4.2. Temperature and PMV
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reported in this paper. Results show that the PV double-glazing window can reduce indoor heat gain and cooling load significantly by setting up an air gap behind PV modules, and because of the much lower inner surface temperature of PV double-glazing window compared with that of PV single-glazing window, the PMV of the office work stage zone is improved obviously compared with PV single-glazing window. So the PV double-glazing window has the large potential application in office building with the cost decreasing and efficiency increasing. The work also demonstrates that the CFD package Fluent can be used in simulate and optimizing the performance of PV window system with acceptable error, so CFD package Fluent can be used to help HVAC engineers to predict the cooling load before design of a building with PV window.
Acknowledgment
Fig. 9. PMV. solid circle: PV single-glazing window; solid square: PV double-glazing window.
The work described in this paper was supported by the grants from the National Key Technology R&D Program in the 11th Five year Plan of china (Project No. 2006BAA04B04) and the National Nature Science Fund of China (Project No. 50876098).
Appendix
t r ¼ Tg Fg þ Twall Fwall tcl ¼ ðhcl ts þ fcl ðhr þ hc Þta Þ=ðhcl þ fcl ðhr þ hc ÞÞ hr ¼ 4:6 1 þ 0:01t r hc ¼ 2:38ðtcl ta Þ0:25 hcl ¼ 1:0=0:155Icl
Fig. 10. Pv Power and efficiency in the testing period. solid square: power of PV double-glazing window; solid circle: efficiency of PV double-glazing window; open square: power of PV single-glazing window; open circle: efficiency of PV single-glazing window.
4.3. PV power output and efficiency The electrical power output and efficiency of PV cells are important parameters to evaluate the performance of PV modules. Compared to mono-silicon cells, the efficiency of semi-transparent a-Si models with packing factor 0.8 is just 3.65% under standard conditions, but the semi-transparent a-Si models has better vision landscape and lower temperature coefficient. These were reported a few years ago [12,13]. Fig. 10 shows the PV power output and efficiency in the testing period. It is found that the variation of PV powerfully traces the variation of solar radiation. The PV temperatures of the two window systems in the testing period are very close to each other and the electrical efficiencies of the two windows both keep at about 2.5%, although the PV temperature varies greatly in the testing period.
5. Conclusions Experimental and numerical analysis of two kinds of PV windows in East China, which are PV double-glazing window and PV single-glazing window integrated with a-Si PV panel, have been
fcl ¼ 1:05 þ 0:1Icl Where hr is radiative heat transfer coefficient between body and interior walls, W/m2; hcl is heat transfer coefficient between the skin surface and clothing, W/m2; Icl is thermal resistance of the clothing; Tg is temperature of the inner surface of the glazing, C; Twall is temperature of the interior wall, C; Fg is view factor between reference point and the glazing; Fwall is view factor between reference point and the interior wall, tcl is surface temperature of clothing, C; fcl is clothing area factor. References [1] Etzion Y, Erell E. Controlling the transmission of radiant energy through window: a novel ventilated reversible glazing system. Building and Environment 2000;35(5):433e44. [2] Brinkworth BJ, Cross BM, Marshall RH, Yang H. Thermal regulation of photovoltaic cladding. Solar Energy 1997;61(3):169e78. [3] Chow TT, Fong KF, He W, Lin Z, Chan ALS. Performance evaluation of a PV ventilated window applying to office building of Hong Kong. Energy and Buildings 2007;39(6):643e50. [4] Renmi C, Andreas K, Athienitis. Optimization of the performance of doublefacades with integrated photovoltaic panel and motorized blinds. Solar Energy 2006;80(5):482e91. [5] Geun YY, Mike M, Koen S. Design and overall energy performance of a ventilated photovoltaic façade. Solar Energy 2007;81(3):383e94. [6] Gan G, Riffat SB. CFD modelling of air flow and thermal performance of an atrium integrated with photovoltaics. Building and Environment 2004;39: 735e48. [7] Han Jun, Lu Lin, Yang Hongxing. Thermal behavior of a novel type see-sight glazing system with integrated PV cells. Building and Environment 2009;44: 2129e36.
W. He et al. / Building and Environment 46 (2011) 363e369 [8] ISO 7730. Moderate thermal environments e determination of the PMV and PPD indices and specification of the conditions for the thermal comfort. 2nd ed. Geneva: International Standards Organisation; 1994. [9] Yakhot V, Qrszag SA, Thangham S, Garski TB. Development of turbulence models for shear flows by a double-expansion technique. Physics of Fluids A-Fluid Dynamics 1992;4(7):1510e20. [10] Ji Y, Cook MJ, Hanby V. CFD modelling of natural dispalacement ventilation in an enclosure connected to an atrium. Building and Environment 2007;42:1158e72.
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[11] Gebhart B. A new method for calculating radiant exchanges. ASHRAE Trans 1959;65:321e3. [12] Takeoka A, Kouzunma S, Tanaka H, Inoue H, Murata K, Morizane M, et al. Development and application of see-through a-Si solar cells. Solar Energy Materials and Solar Cells 1993;29(3):234e52. [13] Miyazaki T, Akisawa A, Kashiwagi T. Energy saving of office buildings by the use of semi-transparent solar cells for window. Renewable Energy 2005;30 (3):281e304.
Contents lists available at ScienceDirect
Building and Environment journal homepage: www.elsevier.com/locate/buildenv
Experimental and numerical investigation on the performance of amorphous silicon photovoltaics window in East China Wei He*, Y.X. Zhang, Wei Sun, J.X. Hou, Q.Y. Jiang, Jie Ji Dept. of Thermal Science and Energy Engineering, University of Science and Technology of China, Hefei 230026, China
a r t i c l e i n f o
a b s t r a c t
Article history: Received 29 April 2010 Received in revised form 20 July 2010 Accepted 30 July 2010
Experiments in a comparable hot-box have been carried out for the study of the thermal performance and power generation of a double-glazing window system integrated with amorphous silicon (a-Si) photovoltaic (PV) cells in Hefei, east region of China. Compared to PV single-glazing window, the indoor heat gain of PV double-glazing window is reduced to 46.5% based on experiment data. The electric efficiencies are both about 3.65% with packing factor 0.8 of PV single-glazing window and PV doubleglazing window. The numerical simulation with computational fluid dynamics (CFD) method has been performed for the prediction of air flow and thermal performance of PV double-glass window. The temperature distribution and thermal performance predicted by the CFD model are in good agreement with the experimental data. Compared between the experimental and numerical results, temperature differences of PV modules are only 1.7% and 1.1% for PV double-glazing and PV single-glazing window, respectively. Because of the much lower inner surface temperature of PV double-glazing window compared with that of PV single-glazing window, the predicted mean vote (PMV) of the office work stage area with PV double-glazing window is well improved. Ó 2010 Elsevier Ltd. All rights reserved.
Keywords: Photovoltaic double-glazing window Thermal and electrical performance Predicted mean vote East China
1. Introduction The application of Photovoltaic technology in buildings has attracted worldwide attention for energy savings and environmental side-effect reductions. Y. Etzion and E. Erell proposed a reversible glazing system that can control transmission of solar radiation into indoor spaces [1]. Brinkworth, B.J. and Cross, B.M. et al. [2] indicated that a ventilated air duct behind a PV panel can decrease temperature of PV cell. CFD package was used to simulate the air flow behind the PV panel and good results were obtained. T.T chow [3] investigated the performance of a PV ventilated window applied to office building of Hong Kong by numerical simulations. With the transmittance of PV window in the range of 0.45e0.55, the electricity consumption was found reduced by 55% compared to the single-glazed window without lighting control. Various numerical investigations of PV ventilated windows with different structures had been carried out to evaluate the thermal loads, daylight contribution and electricity production by Remi C, Geun Y.N [4,5], and so on. Gan and Riffat [6] showed that CFD was a useful tool to optimize ventilation systems for comfortable indoor environment and effective cooling of PV. By studying the factors affecting the local
* Corresponding author. Tel.: þ86 0551 3601641. E-mail address: [email protected] (W. He). 0360-1323/$ e see front matter Ó 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.buildenv.2010.07.030
and average heat transfer coefficients along the vertical surfaces of a see-through glazing system with PV cells, Jun Han [7] did some research on the convective flow strength and heat transfer variation in the ventilation duct. However, there was little report about the performance and PMV analyses of PV window in mainland China. In this paper, the experiment with a comparable hot-box has been carried out in Hefei (N31.8 , E117.3 , east region of China), to study the thermal performance and electrical generation of a double-glazing window system integrated with amorphous silicon cells. Hefei city locates in subtropical climate region, and the annual horizontal solar radiation is about 5000 MJ/m2. The numerical investigation of the performance of PV window system has also been carried out by computational fluid dynamics (CFD) method. 2. Comparable hot-box and experiments 2.1. Comparable hot-box and a-Si PV windows The PV single-glazing window, as shown in Fig. 1b, is just a window which consists of single amorphous silicon (a-Si) PV glazing. And the PV double-glazing window system, as shown in Figs. 1a and 4, consists of an amorphous silicon (a-Si) PV panel and a clear backing glazing. There are ventilated openings at the top and bottom of the semi-transparent a-Si PV glazing, and the PV glazing
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Fig. 1. Schematic structure diagram of the office rooms integrated with a PV double-glass window system. (a) PV double-glazing window, (b) PV single-glazing window.
provides shading and electricity for the room. In summer, with the semi-transparent a-Si PV glazing facing outward, the PV glazing absorbs solar radiation and reduces the penetration of solar radiation into the office room. Part of solar energy absorbed is converted into electrical energy, the other is converted into thermal energy and heats the air in the ventilation gap behind the PV panel. No mechanical ventilated system is provided for the window system. The upward air flow is driven by thermal buoyancy, and a temperature gradient is along the height of the air gap. This window system also has one advantage that the scenery outside can be seen from the inside while it could not be seen from the outside, as showed in Fig. 3. The plan view of the test rig with the window systems is shown in Fig. 2. The dimensions of both rooms are 2.80 m (height) 3.00 m (width) 3.00 m (length). The thickness of room walls is 0.10 m. One of the offices has a double-glazing window integrated semi-transparent a-Si PV cells, and the other has a PV singleglazing window. The two PV windows are both fixed on the south wall. The air-conditioning system inside the comparable hot-box keeps temperature of the corridor and the test office rooms at a constant as 25 0.5 C. Fig. 3 is the photo of the test rig of hot-box integrated a-Si PV window systems. The two PV windows both have a width of 1.2 m and a height of 1.15 m. The thickness of semi-transparent a-Si PV panel and clear glazing is 7 mm and 6 mm, respectively. The air gap in the PV double-glazing window is of 20 mm. The ventilated openings
have a width of 120 mm and a height of 6 mm. As seen in Fig. 3, the PV panel is comprised of three PV modules with size of 1110mm 333 mm, which are manufactured by one company of China. The packing factor of PV cells on the semi-transparent PV modules is of 0.8. The characteristics of the PV module are shown in Table 1. Because of packing factor of 0.8, the electrical efficiency is 3.65% and is lower than that of standard production of 5.5%. 2.2. Experiments The two office rooms were tested at the same time under good weather conditions. Eleven thermocouples were fixed on the glazing surfaces of two PV windows to analyze the temperature distribution and the variation of heat transfer. Two thermocouples are arranged at the openings of PV double-glazing window to measure the inlet and outlet temperature. There were a pyranometer and a thermocouple outdoor used to measure irradiance normal to the plane of the PV cell and outdoor ambient temperature, respectively. The room temperatures of two office rooms were monitored by two thermocouples. All the thermocouples were connected to Data Acquisition/Switch Unit 34901A to record the data. All the experiments were performed from 9:00 am to 17:00 pm which conformed to the office hours in China in summer. PV efficiency (hpv) is an important index to evaluate the performance of PV cells, as
Fig. 2. Schematic planform of environmental hot-box.
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Fig. 3. Double-glazing window system integrated with semi-transparent amorphous silicon (a-Si) PV modules.
hpv ¼
U$I G$Ac
(1)
Where U is voltage of PV modules, voltage; I is current of PV modules, ampere; G is vertical irradiance to the south, W/m2; Ac is area of PV modules, m2. The PV window system plays an important role in modifying solar radiation and heat transmission to the inside of the building. , Meanwhile, the total heat gain from window system (Q) has a great impact on the indoor thermal comfort and cooling load. In summer, the cooling load also increases and the indoor thermal comfort decreases, as a result of the increasing heat gain from window system. , Q ¼ G$A$s þ hr;gw þ hc;gi AðT Ta Þ
(2)
Where A is area of window system, m2; s is effective transmittance of window system; T and Ta are interior surface temperature of window system and indoor air temperature of office room respectively, C; hc,gi is convective heat transfer coefficient between glazing and indoor air, W/m2K; hr,gw is radiative heat transfer coefficient between glazing and interior wall, W/m2K. The temperature difference between window and interior walls leads to asymmetrical thermal radiation and variety thermal comfort level. The index termed predicted mean vote (PMV) is used to evaluate the indoor thermal comfort level, and it is expressed by [8]:
n PMV ¼ 0:303e0:036M þ 0:028 ðM WÞ 3:05 103 ½5733 6:99ðM WÞ pa 0:42½ðM WÞ 58:15 1:7 105 Mð5867 pa Þ 0:0014Mð34 ta Þ 3:96 h o 4 i 108 fcl ðtcl þ 273Þ4 t r þ 273 fcl hc ðtcl ta Þ ð3Þ Table 1 Characteristics of a PV module. Open circuit voltage 41.98 V Short circuit current 0.553 A Power efficiency 3.65% in standard condition
PV packing factor 0.8 Power rating 10.8 W Temperature coefficient 0.1%
Where M is rate of metabolic heat production, W; W is rate of mechanical work accomplished, W; ta is indoor temperature, C; pa is water vapor pressure of indoor air, Pa; tcl is surface temperature of clothing, C; fcl is clothing area factor; t r is weighted surface radiant temperature, C; hc is convective heat transfer coefficient between body and indoor air, W/m2; The expressions of tcl, hc, fcl, t r are given in Appendix. 3. Numerical simulation 3.1. Simulation program The computational fluid dynamics (CFD) was employed to study the performance of PV windows. A general-purpose commercial CFD software FLUENT was applied to calculate the air flow and temperature distribution of the office rooms. The pre-processor software GAMBIT was adopted in the simulate work. The physical, vertical irradiance and temperature date obtained from the experiment of PV window system were used as input parameters into the simulation. 3.2. CFD modelling The FLUENT package was used in modelling the ventilation by solving the conservation equations for mass, momentum and energy with the finite volume method. Previous studies have suggested that the renormalization group (RNG) k-epsilon turbulence model [9] performs better than other turbulence model in the prediction of indoor air flow [10]. Therefore, the RNG k-epsilon turbulence model was adopted to simulate the effect of turbulence of air flow as air flow in PV double-glazing window system. In order to simulate the effect of buoyancy, the Boussinesq model, in which the fluid density was taken as a function of temperature, was used. The discrete transfer radiation model [11] was used to evaluate the radiative heat transfer of the office interior surfaces, which were assumed to be gray. To simplify the simulation of PV windows, it was assumed that fresh air flowed into office room from an inlet opening in the ceiling and out of office room via an outlet opening in the north wall. The inlet opening of 0.2 m width was located at the center of the ceilings, 1.4 m to the
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north wall, and the extract opening of 0.15 m high was located near top of the north wall. All the boundaries of the two office rooms were modeled as adiabatic no-slip wall boundaries, except the ventilation openings. When a-Si PV modules operated, most of the solar irradiation absorbed by them was converted into heat energy, so the temperature of PV modules increased. As a result of the low temperature coefficient of a-Si PV module, the energy that solar irradiation was converted into heat was almost the same as what it used to be. Therefore, the semi-transparent a-Si PV modules could be assumed as a constant heat source. Because of the symmetry of the office, a two-dimensional model was used to simplify the simulation of the office’s ventilation and thermal performance to reduce computational time. This would imply no air flow or heat transfer through the side walls. The air flow inside PV double-glazing window system is affected by heat conduction, convective and radiative heat transfer. The first-order upwind discretization scheme was used in the simulation modelling. A nonuniform computational grid was used for the prediction of two-dimensional flow in the office rooms. Convergence was considered to have been reached when the residuals of energy equation were less than 1e-6, and the residuals of other equations were by less than 103. 4. Performance evaluation The experiment was conducted in the summer of 2009, and lasted for more than one month. The experimental data of September 22 was selected as a typical sample to analyze the performance of PV window systems. Fig. 4 shows the ambient temperature and incident irradiation on south façade from 9:00 am and 17:00 pm in September 22. They were used in computer simulation as the boundary conditions. 4.1. Heat gain and energy saving Figs. 5 and 6 show second heat gain and total heat gain from PV double-glazing window and PV single-glazing window from 9:00 am to 17:00 pm respectively. The total heat gain can be divided into second heat gain and direct heat gain from solar irradiation. The second heat gain is the combination of the convective and infrared radiative heat transfer between glazing and the indoor space, which is represented by the second right item in Eq. (2). The direct heat gain is the solar radiation transmitted from the window system, which is represented by the first right item in Eq. (2).
Fig. 4. Ambient temperature and vertical irradiation of south façade.
Fig. 5. Second heat gain from the two windows. solid quadrel: Second heat gain from PV double-glazing window (exp); open quadrel: Second heat gain from PV doubleglazing window (num); solid circle: Second heat gain from PV single-glazing window (exp); open circle: Second heat gain from PV single-glazing window (num); cross symbol line: solar irradiation.
As is shown in Figs. 5 and 6, the trend of total heat gain is basically the same as that of second heat gain. The direct heat gain of PV single-glazing window is 20% higher than that of PV doubleglazing window. But the direct heat gain from solar irradiation only occupies a small part of total heat gain. Therefore, second heat gains from window systems have a decisive impact on total heat gains. The predicted mean second and total heat gains are close to the measured values. In the morning, the predicted mean values are a little more than the measured ones, while they are a little less than the measured ones in the afternoon. The difference between experiment and numerical simulation could due to the twodimensional flow simulation to three-dimensional flow in fact. The average heat gain and temperature of PV modules from 9:00 to 17:00 from experiments and numerical simulation are given in Table 2. The average measured heat gains are all a little larger than predicted. The average measured second heat gain from double-
Fig. 6. Total heat gain from the two windows. solid quadrel: total heat gain from PV double-glazing window (exp); open quadrel: total heat gain from PV double-glazing window (num); solid circle: total heat gain from PV single-glazing window (exp); open circle: total heat gain from PV single-glazing window (num); cross symbol line: solar irradiation.
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Table 2 Average indoor heat gain and temperature of PV modules (9:00e17:00 h). Construction
Second heat gain (W) Total heat gain (W) Temperature of PV modules ( C)
PV double-glazing window
PV single-glazing window
Experimental
Numerical
Difference
Experimental
Numerical
Difference
51.8 78.3 36.1
46 70.2 36.7
12.6% 11.5% 1.7%
113.2 146.3 37.1
112.1 142.3 36.7
1.0% 2.7% 1.1%
glazing window is about 51.8 W, and it is 12.6% larger than the average predicted value which is 46 W. The average measured total heat gain from double-glazing window is 78.3 W, and is 11.5% larger than the predicted. For the single-glazing window, the difference of second heat gain between experimental and numerical data is 1.0% and that of total heat gain is 2.8%. According to the experimental data, second and total heat gain of PV double-glazing window are 45.8% and 53.5% of that of PV single-glazing window, respectively, and the values are 41.0% and 49.3% respectively from simulation results. It indicates that PV double-glazing window can effectively reduce indoor heat gain and air-conditioning load, compared with PV single-glazing window. The better thermal performance of PV double-glazing window is due to its ventilated openings at the top and bottom, which improves the thermal resistance of PV window significantly. As seen from Figs. 5 and 6, the second heat gain and total heat gain were affected by incident solar irradiation and ambient temperature significantly. There is a time lag of the effect of solar irradiation on second and total heat gains. When the incident irradiation reaches the peak at about 12:00, second, total heat gains are still in the upswing. On the other hand, the downward trend of second and total heat gains is not as sharp as that of incident solar irradiation in the afternoon, due to the impact of ambient temperature.
Fig. 7 gives the temperature distributions of different glazing at 12:00 from the simulation and experiment. The temperatures of
experiment and simulation are close to each other except that of the bottom. At the bottom of clear glazing of PV double-glazing window, the difference between experimental and calculated temperature is about 3 C. This could be due to the relative low Rayleigh numbers in the air gap of PV double-glazing window, according to the RNG -epsilon turbulence model. Fig. 8 shows the variety of glazing temperature from 9:00 to 17:00. Experimental data and numerical simulation data of glazing temperature are basically consistent. The experimental PV temperature of single-glazing window keeps a little higher than that of PV double-glazing, and this could be due to the enhanced heat transfer coefficient in the ventilation construction. The increasing of PV cells temperature has a negative influence on the performance of electrical power. Therefore, PV double-glazing window is better for the operation of PV modules. The position at 0.75 m from floor level, 1 m from window and 1.5 m from nearby side wall is chosen as the reference one normally where the office work stage zone is. And indoor relative humidity is assumed to be 40%, M is 58.15 W/m2, Icl is 0.6, Fg and Fwall are both 0.5. Then the daily variation of PMV of the office work stage zone with PV single-glazing window and PV double-glazing window based on experimental data are showed in Fig. 9. The PMV of the office work stage zone with PV single-glazing window varies between 1.4 and 2.6, and this index means that the thermal sensation of person is warm or even hot. As the inner surface temperature of clear glass is much lower than that of PV single-glazing, the PMV of the office work stage area with PV double-glazing window varies between 0.9 and 1.7, i.e. the thermal sensation of person is mostly kept in the band between neutral and slightly warm.
Fig. 7. Glazing temperature distribution of different glazing at 12:00. solid circle: PV models of PV single-glazing window (num); open circle: PV models of PV singleglazing window (exp); solid triangle: PV models of PV double-glazing window (num); open quadrel: PV models of PV double-glazing window (exp); solid square: clear glass of PV double-glazing window (num); open square: clear glass of PV double-glazing window (exp).
Fig. 8. Glazing temperature of different glazing. solid circle: PV models of PV singleglazing window (num); open circle: PV models of PV single-glazing window (exp); solid triangle: PV models of PV double-glazing window (num); open quadrel: PV models of PV double-glazing window (exp); solid square: clear glass of PV doubleglazing window (num); open square: clear glass of PV double-glazing window (exp).
4.2. Temperature and PMV
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reported in this paper. Results show that the PV double-glazing window can reduce indoor heat gain and cooling load significantly by setting up an air gap behind PV modules, and because of the much lower inner surface temperature of PV double-glazing window compared with that of PV single-glazing window, the PMV of the office work stage zone is improved obviously compared with PV single-glazing window. So the PV double-glazing window has the large potential application in office building with the cost decreasing and efficiency increasing. The work also demonstrates that the CFD package Fluent can be used in simulate and optimizing the performance of PV window system with acceptable error, so CFD package Fluent can be used to help HVAC engineers to predict the cooling load before design of a building with PV window.
Acknowledgment
Fig. 9. PMV. solid circle: PV single-glazing window; solid square: PV double-glazing window.
The work described in this paper was supported by the grants from the National Key Technology R&D Program in the 11th Five year Plan of china (Project No. 2006BAA04B04) and the National Nature Science Fund of China (Project No. 50876098).
Appendix
t r ¼ Tg Fg þ Twall Fwall tcl ¼ ðhcl ts þ fcl ðhr þ hc Þta Þ=ðhcl þ fcl ðhr þ hc ÞÞ hr ¼ 4:6 1 þ 0:01t r hc ¼ 2:38ðtcl ta Þ0:25 hcl ¼ 1:0=0:155Icl
Fig. 10. Pv Power and efficiency in the testing period. solid square: power of PV double-glazing window; solid circle: efficiency of PV double-glazing window; open square: power of PV single-glazing window; open circle: efficiency of PV single-glazing window.
4.3. PV power output and efficiency The electrical power output and efficiency of PV cells are important parameters to evaluate the performance of PV modules. Compared to mono-silicon cells, the efficiency of semi-transparent a-Si models with packing factor 0.8 is just 3.65% under standard conditions, but the semi-transparent a-Si models has better vision landscape and lower temperature coefficient. These were reported a few years ago [12,13]. Fig. 10 shows the PV power output and efficiency in the testing period. It is found that the variation of PV powerfully traces the variation of solar radiation. The PV temperatures of the two window systems in the testing period are very close to each other and the electrical efficiencies of the two windows both keep at about 2.5%, although the PV temperature varies greatly in the testing period.
5. Conclusions Experimental and numerical analysis of two kinds of PV windows in East China, which are PV double-glazing window and PV single-glazing window integrated with a-Si PV panel, have been
fcl ¼ 1:05 þ 0:1Icl Where hr is radiative heat transfer coefficient between body and interior walls, W/m2; hcl is heat transfer coefficient between the skin surface and clothing, W/m2; Icl is thermal resistance of the clothing; Tg is temperature of the inner surface of the glazing, C; Twall is temperature of the interior wall, C; Fg is view factor between reference point and the glazing; Fwall is view factor between reference point and the interior wall, tcl is surface temperature of clothing, C; fcl is clothing area factor. References [1] Etzion Y, Erell E. Controlling the transmission of radiant energy through window: a novel ventilated reversible glazing system. Building and Environment 2000;35(5):433e44. [2] Brinkworth BJ, Cross BM, Marshall RH, Yang H. Thermal regulation of photovoltaic cladding. Solar Energy 1997;61(3):169e78. [3] Chow TT, Fong KF, He W, Lin Z, Chan ALS. Performance evaluation of a PV ventilated window applying to office building of Hong Kong. Energy and Buildings 2007;39(6):643e50. [4] Renmi C, Andreas K, Athienitis. Optimization of the performance of doublefacades with integrated photovoltaic panel and motorized blinds. Solar Energy 2006;80(5):482e91. [5] Geun YY, Mike M, Koen S. Design and overall energy performance of a ventilated photovoltaic façade. Solar Energy 2007;81(3):383e94. [6] Gan G, Riffat SB. CFD modelling of air flow and thermal performance of an atrium integrated with photovoltaics. Building and Environment 2004;39: 735e48. [7] Han Jun, Lu Lin, Yang Hongxing. Thermal behavior of a novel type see-sight glazing system with integrated PV cells. Building and Environment 2009;44: 2129e36.
W. He et al. / Building and Environment 46 (2011) 363e369 [8] ISO 7730. Moderate thermal environments e determination of the PMV and PPD indices and specification of the conditions for the thermal comfort. 2nd ed. Geneva: International Standards Organisation; 1994. [9] Yakhot V, Qrszag SA, Thangham S, Garski TB. Development of turbulence models for shear flows by a double-expansion technique. Physics of Fluids A-Fluid Dynamics 1992;4(7):1510e20. [10] Ji Y, Cook MJ, Hanby V. CFD modelling of natural dispalacement ventilation in an enclosure connected to an atrium. Building and Environment 2007;42:1158e72.
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