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Experimental and numerical evaluation of the crystalline silicon PV window under the climatic conditions in southwest China
Energy 183 (2019) 584e598
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Energy journal homepage: www.elsevier.com/locate/energy
Experimental and numerical evaluation of the crystalline silicon PV window under the climatic conditions in southwest China Mo Chen a, Wei Zhang a, *, Lingzhi Xie b, Zhichun Ni c, Qingzhu Wei c, Wei Wang a, Hao Tian a a b c
College of Architecture and Environment, Sichuan University, Chengdu, 610065, China Institute of New Energy and Low-carbon Technology, Sichuan University, Chengdu, 610065, China Suzhou Talesun Solar Technologies Co., Ltd, Suzhou, 215542, China
a r t i c l e i n f o
a b s t r a c t
Article history: Received 29 December 2018 Received in revised form 30 May 2019 Accepted 23 June 2019 Available online 26 June 2019
Windows integrated with PV can provide electrical energy and control the energy flow (heat and light) through the windows. With the objective of evaluate the potential application of window integrated PV in southwest China, the performance of silicon PV windows was comprehensively studied. A test unit was developed to monitor the performance of window integrated PV, then a validated comprehensive approach integrated with heat transfer, optical, electrical and building simulation model was used to comprehensively evaluate the performance of the window integrated PV under various climatic conditions in southwest China. The effects of the air gap on window thermal performance, window orientation, different window-to-wall ratio and coverage ratio of PV cells are evaluated. It was found that a maximum energy saving could be achieved, when the PV window is installed on the south facing façade with a PV cell coverage ratio of 0,87, air gap of 9 mm between the two glazing panes. It was found that a maximum energy saving of 983 kWh was achieved in Lhasa. A highest energy saving ratio of 83% was found in Kunming. The window integrated PV shows good energy saving potential under different climatic conditions in Southwest China. © 2019 Elsevier Ltd. All rights reserved.
Keywords: c-Si PV window BIPV Light-heat-electricity Energy consumption Southwest China
1. Introduction Building integrated photovoltaics (BIPV) converts solar energy into electrical energy and has the potential to meet building energy consumption. Significant research has been carried out to evaluate the performance of BIPV [1]. Photovoltaic windows, one type of BIPV, can provide buildings with renewable electricity while meeting the architectural aesthetic design, and reduce the energy consumption of the building [2]. In Southwest China, solar energy application is being encouraged to develop at a rapid pace owing to an abundant availability of solar radiation and sparsely populated land [3]. The use of PV windows in Southwest China is promising. However, the climatic conditions of the region are more complicated. China can be divided into five climatic zones, and southwest China houses three of them, which are Hot Summer Cold Winter Zone, Cold Zone and Temperate Zone. The solar energy resources in the southwest China
* Corresponding author. E-mail address: [email protected] (W. Zhang). https://doi.org/10.1016/j.energy.2019.06.146 0360-5442/© 2019 Elsevier Ltd. All rights reserved.
are generally rich, but the distribution is uneven. The climate zones [4] and Solar resource map [5] of China are shown in Fig. 1. In this article, Lhasa, Kunming, Chengdu, Chongqing and Guiyang were taken into consideration to study the energy saving effect of PV window in southwest China. These five cities are the provincial capitals of Southwest China with a large population. They are located in different climate zones and have different irradiation conditions. Usually, the PV cells used on STPV window are crystalline silicon solar cells(c-Si) and Amorphous silicon solar cells(a-Si). As shown in Fig. 2, crystalline silicon modules have the higher power generation efficiency but are not transparent. Thin film module has good transmittance, but its efficiency is among 4.1%e12% [6]. In recent years, the new generation of photovoltaics, concentrator photovoltaics (CPV) are used on STPV windows, which has higher power generation efficiency [7]. The presence of semi-transparent PV(STPV) windows greatly affects the solar energy through the windows and affects the load conditions, which are mainly shown as the decrease of the cooling load and the increase of heating load [8]. Also, STPV windows with
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Fig. 1. (a)Climate zone and (b)Solar resource map of China.
Fig. 2. Window integrated with different types of PV cell materials. (a).c-Si (b).a-Si (c).CPV.
appropriate transmittance also enable full use of daylight [9]. STPV windows can also affect the indoor load due to self-heating, which in turn may affect the power generation efficiency. Taking into account the influence of STPV windows on indoor load, daylighting, and power generation, the energy saving potential should be studied. In the studies of thermal-electricity performance of doublelayer PV window, most researches [10e15] mainly established a heat transfer model to simulate the thermal and electrical performance of double-layer STPV. Jong-Hwa Song et al. [10,11] established a numerical simulation model for double-layer STPV windows based on actual meteorological parameters in numerical simulation software TRNSYS. Simulation results showed that installation angle is an important factor affecting thermal and electrical performance and that 30 is the best installation angle. Tady Y.Y. Fung et al. [15] simulated thermal conduction of doublelayer PV windows using one-dimensional transient thermal equilibrium equation. The results showed that when the coverage of PV modules is close to 80%, the heat gain can be reduced by 70%. It can thus be concluded that the coverage area of PV modules has the greatest impact on indoor heating. Another focus of the research was double-layer PV windows as semi-transparent enclosure and their light-electricity performance. K. Kapsis et al. [16] used Daysim to study the indoor lighting of different film transmittances. The results showed that the opticalelectrical performance of the thin film photovoltaic window was optimal when the light transmittance was 30%. Shen Xu et al. [17] simulated the performance of crystalline silicon component
coverage on the photovoltaic performance. The results show that the higher photovoltaic coverage rate is suitable for buildings with large window to wall ratio and deep buildings, which increases the total power generation but reduces the photoelectric conversion efficiency. For the study on energy consumption, Miyazaki T [18] investigated a double layer amorphous silicon PV window by simulation study. It was found that the minimum electricity consumption can be achieved when solar cell transmittance is 40% and WWR is 50%. The electricity consumption could be reduced by 55% with the optimized PV window. A comprehensive methodology was developed by Lu L [19] to study the thermal and electrical performance of single-layer STPV window in Hong Kong. The total heat gain, electricity generation and daylight illuminance are included. The findings show that the primary factor of energy saving is thermal performance and the secondary is electricity consumption of artificial lighting. Most of previous research for PV windows were aimed at the amorphous silicon PV window, and the systematic research needs to be improved. In this article, the c-Si PV windows with reasonable crystal silicon arrangement, which has a higher conversion efficiency is used as the study object. There are limited studies about Southwest China despite rich solar resources, complex climatic conditions and diverse geographical conditions, in which the application of STPV window needs to be further investigated. This paper relies on the National Key Research and Development Program of China to study the application of BIPV in western China, especially solar windows, and pay more attention to the energy-
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saving effect of PV windows in practical application in Southwest China. Therefore, in light of the comprehensive process of three factors, light-heat-electricity, two comparison test units with c-Si PV and conventional windows were set up to test the performance and energy saving. The application effect of the c-Si PV window was investigated systematically, including energy consumption testing, energy consumption simulation, PV window design optimization and energy saving. A three-factor simulation model was established, and verified by the test results. In order to optimize the STPV window, its air gap depth, orientation, window-wall ratio and coverage were analyzed. The energy consumption of the test is compared with that of the simulation in order to correct the simulation results. Furthermore, five cities located in different climate zone in Southwest China were selected to predict and compare the energy saving potential of the buildings installed with the optimized c-Si PV window. 2. Methodology 2.1. STPV window module According to our previous study [20] on the STPV windows in southwest China, we and the industry partners jointly developed cSi PV windows with reasonable crystal silicon arrangement. The dimension of STPV window and the layout of PV cells are shown in Fig. 3. Fig. 3(a) is the layout of STPV window, and Fig. 3(b) a picture of real STPV window. The STPV window consists of three parts. The outermost layer is a 4 mm translucent photovoltaic glazing layer, the inner layer is an 5 mm conventional transparent glass, and the air gap is 9 mm. The detailed parameters are shown in Table .1.
front of the windows. The test was conducted in September 2018, in which the power generation is relatively higher. The test rig is shown in Fig. 4. The outdoor test equipment consisted of a weather station and an irradiance meter that measured global vertical solar irradiance. The weather station measures outdoor temperature and humidity, wind direction, wind speed, etc. The irradiance meter measured the solar irradiance in the direction of the window. The schematic diagram of the indoor environment test instruments was shown in Fig. 5(a) [20]. The double-skin window related parameters like IeV curve, solar radiation upon south façade, generation power was measured by the PV testing equipment. According to the “Method of daylighting measurements” (GB/T 5699-2017) [21], 4 points were evenly distributed indoors to test indoor daylighting illumination. Wireless lighting sensors were used to measure the illumination on the work surface. The height of the lighting sensors is 1.3 m and the horizontal position of the measuring point is as shown in Fig. 5(b). The experimental data except electrical parameters were collected by a wireless multi-channel data recorder with a sampling interval of 2 min. The temperature of the outer surface of PV window, and ambient temperature of the test unit were tested by seven T-type thermocouples, the position of the measuring point is as shown in Fig. 5(c). To get the indoor energy consumption, the energy consumption of the air-conditioner and lighting were collected by the electric quantity recorder. The quantity recorder is made by BULL and can transfer data through a wireless network. When the indoor illumination is less than 500lx, the light will turn on automatically. And if the indoor temperature is above 28 o C, the air conditioner will turn on automatically [22]. All the key instruments and their specifications have been shown in Table 2. 2.3. Simulation model
2.2. Test rig and instruments In order to test energy consumption and study the accuracy of the simulation model, a test rig was established in Chengdu. Chengdu is located in the central part of Sichuan Province, west of the Sichuan Basin, between 102 540 ~104 530 east longitude and 30 050 ～31260 north latitude. As shown in Fig. 4, the test rig has a length and a width of 3 m each, the wall of the window was 3.2 m high, and the wall of the window was 3 m high. The test rig is built on a flat surface with windows facing south and no obstructions in
In order to simulate the overall performance of the double-layer c-Si window in southwest China, a light-heat-electricity threefactor model was established using the lighting model, heat transfer model and Sandia model in EnergyPlus [23]. The temperature of the glass panel, the indoor illumination, and the power generation performance of the photovoltaic window were tested. The test results were used as verification of the simulation model. a) Daylighting model EnergyPlus controls the intensity of the light according to natural daylighting, keeping the reference point at a certain illumination. For the calculation of natural daylighting, there are mainly the following steps: calculating the daylight factor, calculating the natural illuminance, and calculating the required lighting power consumption [24]. b) Heat balance model
Fig. 3. C-Si PV window, (a)layout (b)real picture.
In EnergyPlus, the window glass face temperatures are determined by solving the heat balance equations on each face every time step. For a window with N glass layers there are 2 N faces and therefore 2 N equations to solve. Fig. 6 shows the variables used for double glazing (N ¼ 2). The four equations for double-glazing are as follows [25].where,Eo and Ei is exterior and interior long-wave radiation incident on window respectively. εi is the emissivity of face i. qi is the temperature of face i. ki is the conductance of glass layer i. ka is the conductance of air gap.ho and hi are the outside and inside air film convective conductance, respectively. To and Ti are outdoor and indoor air temperature respectively. Si is radiation (short-ware, and long wave from zone internal sources) absorbed
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Table 1 The dimension, layout and structure of STPV window. a. The dimension and layout of STPV window Glazing Size(m m) 1.24 0.64 b. Structure of STPV window Layer/Property Single STPV window Air gap Glass-tempered
PV cell size(mm mm) 155 155 Thickness(mm) 4 9 5
Fig. 4. Test rig.
PV cell number 28
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Fig. 5. Indoor environment test instruments.
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Table 2 The key instruments and their specifications. Equipment
Manufacture
Function and Model
Accuracy/Sensitivity
Multi-channel PV test equipment Solar radiation test equipment Weather station
Ceyear AV6595A AV87110 J.t
PV testing (three 500W module and one 10 kW module) Testing the solar radiation upon the south façade Weather condition recorder
0We10 kW
Thermocouples Light meter Electricity recorder Multi-channel data recorder
J.t J.t BULL J.t
Temperature test (T type thermocouple) e Record electricity consumption Data collector
by face i.
Eo ε1 ε1 sq41
0e1800 W/m2; ±3% Temperature: ±0.5 C, humidity: 0.1%,±2%; atmospheric pressure: 1 mbar; wind rate: 0.1 m/s; wind direction: ±5% 200Ce100 C; 0.1 C; ±0.5 C 0e100,000 lux; 1 lux; ±4% 0e3000W, ±1% The minimum resolutions are 1 mV and 0.1 C
Pmp ¼ Imp ,Vmp þ k1 ðq2 q1 Þ þ ho ðTo q1 Þ þ S1 ¼ 0
k1 ðq1 q2 Þ þ ka ðq3 q2 Þ þ s
(1)
ε2 ε3 q4 q42 þ S2 1 ð1 ε2 Þð1 ε3 Þ 3
¼0 (2) h1 ðq2 q3 Þ þ k2 ðq4 q3 Þ þ s
ε2 ε3 q4 q43 þ S3 1 ð1 ε2 Þð1 ε3 Þ 2
¼0 (3) Ei ε4 ε4 sq44 þ k2 ðq3 q4 Þ þ hi ðTi q4 Þ þ S4 ¼ 0
(4)
c) Sandia PV model The Sandia PV model is an empirical based model and is tightly coupled with the thermal model in EnergyPlus. Peng J et al. [26] has validated the Sandia model with indoor and outdoor measurements for semi-transparent amorphous silicon PV modules. Eqs. (5)e(9) [27] summarize the Sandia model.
h Isc ¼ Isco ,f1 ðAMa Þ, Eb , f2 ðAOIÞ þ fd , Ediff . i Eo ,½1 þ aIsc , ðTc To Þ
(5)
Imp ¼ Impo , C0 , Ee þ C1 , E2e , 1 þ aImp , ðTc To Þ
(6)
Voc ¼ Voco þ Ns ,dðTc Þ,lnðEe Þ þ bVoc ðEe Þ,ðTc Te Þ
(7)
(9)
where, Isc is the short-circuit current (A); Imp is the current at the maximum power point (MPP) (A); Voc is the open circuit voltage (V); Vmp is the voltage at the MPP (V); Imp0 is the current at the MPP under STC (A); Isc0 is the short-circuit current under STC (A); Vmp0 is the voltage at the MPP under STC (V); Voc0 is the open circuit voltage under STC (V); Ee is the effective irradiance (suns); Tc is the PV module's operating temperature (o C); T0 is the temperature of STC, it is 25 o C; Ns is the number of solar cells in series; dðTcÞ is the thermal voltage; aImp is the temperature coefficient of Imp ; aIsc is the temperature coefficient of Isc ; bVmp is the temperature coefficient of Vmp ; bVoc is temperature coefficient of Voc ; f ðAMaÞ is an empirical function of absolute air mass (AMa), it was introduced to correct the impact of solar spectrum on the short-circuit current, Isc ; C0 through C7 are dimensionless parameters needed to be fitted. C0 and C1 are empirically determined coefficients which relate Imp to the effective irradiance, Ee , C0 þ C1 ¼ 1, (dimensionless); C2 and C3 are empirically determined coefficients which relate Vmp to the effective irradiance (C2 is dimensionless, and the unit of C3 is 1 =V). 2.4. Model set up In this simulation, the room using double-layer STPV windows was compared with the room with ordinary double-layer windows. The structure of STPV window is shown in Fig. 3. The normal window consists of a 4 mm normal glazing layer, 9 mm air gap and a 5 mm normal glazing layer. Specific glass parameters are shown in Table .3. The length and width of the test rooms are 3 m 3 m. The height of the wall against window is 3 m, and the height of the wall where the window is located is 3.2 m. The room model is shown in Fig. 7. The photovoltaic panel is the polycrystalline silicon photovoltaic panel, and the coverage of PV cells is 0.72. The photovoltaic panel parameters were measured by Talesun and are shown in Table .4. According to the HVAC design requirements for China Office Building [22], the indoor air temperature was designed as 28 o C in summer and 18 o C in winter. When the indoor illumination at the working plane is less than 500lx [21], the light will turn on
Vmp ¼ Vmpo þ C2 ,Ns ,dðTc Þ,lnðEe Þ þ C3 ,N3 ,½dðTc Þ,lnðEe Þ2 þ bVmp ðEe Þ,ðTc To Þ
(8)
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fluctuation trend of outdoor temperature is similar to that of solar radiation. During the period of 1st/sep to 7th/sep, there were 4 sunny days, 2 cloudy-sunny days and 1 cloudy day. The test results of these days were selected to validate the simulation model. b). The I-V curve The I-V curve of the STPV window at 10:01, the 4th, is shown in Fig. 9. It was found that the open circuit voltage was 78.11 V. The short-circuit current was 2.46 A. The maximum power of the STPV window was 157.17W and the fill factor of the STPV window was 81%. The IeV curve was smooth and the PV window worked properly. c). The efficiency of the PV window
Fig. 6. Glazing system with two glass layers.
automatically. To couple the heat transfer and energy balance, the ‘Integrated Surface Outside Face’ was chosen for setting the cell temperature of STPV windows.
3. Test results and validation of simulation model of the PV window 3.1. Test results a). The incident solar irradiation upon the south façade in a month is shown in Fig. 8(a). The maximum incident solar radiation upon the south façade was 545.3 W/m2 in 28th/sep. The outdoor temperature is shown in Fig. 8(b). It can be seen that the
The efficiency of the PV window is shown in Fig. 10. The selected days for analysis were a sunny day (4th/sep), a cloudy-to-sunny day (6th/sep), and a cloudy day (5th/sep). During the sunny day, from morning to afternoon, the efficiency of the PV window firstly increases and then decreases. On the cloudy-to-sunny day, the efficiency maintains between 0.12 and 0.14. On cloudy day, the efficiency fluctuates greatly before 14:00, and after 15:00, the efficiency maintains between 0.11 and 0.14. From Fig. 10, the efficiency of the PV windows is larger than 0.11 when working properly. d). Average indoor illuminance The Average indoor illuminance in September is shown in Fig. 11. It can be seen that compared to sunny days, there are more cloudy days in September. But due to the larger window-wall ratio and the larger proportion of scattered radiation in Chengdu, the indoor illumination can still meet the lighting needs in most of the daytime.
Table 3 Parameters of glazing.
STPV Glazing Clear 4 mm Clear 5 mm
Thickness(mm)
Solar Transmittance at Normal Incidence
Visible Transmittance at Normal Incidence
Conductivity (W/m$k)
4 4 5
0.224 0.824 0.811
0.225 0.893 0.887
0.0415 0.0133 0.0133
Fig. 7. Room model.
M. Chen et al. / Energy 183 (2019) 584e598 Table 4 Parameters of STPV. Parameters
Value
Active area, A(m2) Number of cells in series, Ns Number of cells in parallel, Np Short circuit current, Isc(A) Open circuit voltage, Voc(V) Current at the maximum power point, Imp(A) Voltage at the maximum power point, Vmp(V)
3.3635 140 1 6.986 85.6 6.221 68.3
e). The tested energy consumption The daily tested energy consumption of the room with STPV window in September is shown in Fig. 12. It can be seen that because the solar radiation has a great influence on the room heat gain, the fluctuation trend of energy consumption for cooling and
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PV power generation is similar. Due to the large proportion of scattered radiation in Chengdu and its small proportion in building energy consumption, the fluctuation of lighting energy consumption is not obvious. The test energy consumption of rooms with STPV window and conventional window in September is shown in Fig. 13. From the energy consumption and productivity composition, air conditioning energy consumption is still the main energy consumption of buildings. Compared with the room with ordinary windows, lighting energy consumption of the room with PV windows has increased by 12.95 kWh, but the energy consumption of air conditioning has decreased by 22.13 kWh. The test results show that the electricity generated by PV can't meet all building energy consumption, but can compensate for the increase of lighting energy consumption, which is caused by the occlusion of photovoltaic modules.
Fig. 8. Outdoor test results.
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Fig. 9. I-V curve.
Fig. 10. Efficiency of the PV window.
Fig. 11. Average indoor illuminance.
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the window outside surface temperature, the illuminance of the test room and the power generation of STPV window were tested. The test results were used to validate the simulation model. Seven days are selected to validate the simulation model. There were 4 sunny days, 2 cloudy-sunny days and 1 cloudy day amongst the selected 7 days. To assess the accuracy of the simulation model, two statistical indices, viz. mean bias error (MBE) and the coefficient of variation of root mean square error (Cv(RMSE)), were chosen to evaluate the deviation between the simulated results and the measured data [28]. ASHRAE Guideline 14 suggests that if the MBE and Cv(RMSE) of a building energy simulation model fall within 10% and 30% respectively, it can be regarded as an acceptable model in accuracy [29,30]. Equations of calculating MBE and Cv(RMSE) are as follows:
PN MBEð%Þ ¼
Fig. 12. The daily tested energy consumption/generation.
i¼1 ðmi si Þ PN i¼1 mi
Cv ðRMSEÞð%Þ ¼
(10)
rffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi . ffi PN 2 N i¼1 ðmi si Þ m
(11)
where, mi and si are the measured and simulated data for the instance ‘i’, respectively; N is the number of data points; m is the average value of the all measured data. a). Validation of silicon surface temperature
Fig. 13. The total energy consumption in September.
3.2. Validation of simulation model of the PV window Beside the solar irradiation and the efficiency of the PV window,
The test result of outer surface temperature of the STPV window from 1st/sep to 7th/sep is shown in Fig. 14. The temperature reached the highest point in 4th/sep with about 55o C. From 5th/sep to 7th/sep, the temperature was relatively lower, since those days were rainy or cloudy. On sunny days, the outer surface temperature of the STPV window was very high with the temperature greater than 40o C for majority of the daytime. A comparison between the simulated and the measured outer surface temperature of the STPV window is presented in Fig. 14. The measured value of the photovoltaic window outer surface temperature is close to the simulated value. The MBE is 3.45%, and the Cv(RMSE) is 4.54%. This shows that the window heat transfer conditions in the simulation match those of the test.
Fig. 14. Temperature comparison.
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b). Validation of daylight illuminance Fig. 15 presents the comparison results between the simulated and the measured indoor daylight illuminance at the reference point. The illuminance at reference point reached the highest point at 4th/sep with about 1300lux. Within sunny days, the illuminance of reference point was larger than 300lux for about 8 h. During the period of 5th/sep to 7th/sep, the illuminance was relatively lower than other days. From Fig. 15, the simulation results are similar to the test results. The calculation results show that the MBE was 7.59% and the Cv (RMSE) was 14.04%. Therefore, the lighting model is acceptable in terms of accuracy. c). Validation of electricity generation
Fig. 17. The comparison between the tested and simulated energy consumption/ generation.
The test result of power of electricity generated during the period of 1st/sep to 7th/sep are shown in Fig. 16. The temperature reached the highest point on 4th/sep with about 200W. From 5th/ sep to 7th/sep, the power was relatively lower since those days were rainy or cloudy. It can be seen in Fig. 16 that the power of simulated photovoltaic panel electricity generation and test value were within the acceptable range. The calculation results show that the MBE
was 6.16% and the Cv(RMSE) was 12.26%. Therefore, the PV model is acceptable in terms of accuracy. Through the aforementioned experimental verification, it can be shown that the simulation model can simulate the real operation of the room. Therefore, the validated simulation model was used for optimization of STPV window and annual energy analysis.
Fig. 15. Reference Point Illuminance comparison.
Fig. 16. Comparison of Power of STPV window.
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3.3. The comparison between the tested and simulated energy consumption/generation The comparison between the tested and simulated energy consumption/generation is shown in Fig. 17. It can be seen that the simulated lighting energy consumption and cooling energy consumption are less than the test, and the simulated PV power generation is slightly larger than the test. The simulation results of lighting energy consumption and power generation are similar to the test results, but the simulation results of cooling energy consumption are different from the test results. One reason is that daylighting energy consumption and PV power generation are small. Another reason is that there is a difference between the simulation and the test in terms of the process of air conditioning. The tested net electricity consumption is 16.8% larger than the simulated net electricity consumption. The area of the test unit is small, but with a large building, the difference could be more obvious. As a result, when calculating the net building power consumption, it should be taken into account the loss energy of equipment in actual operation. The differences between the test and simulation data are analyzed to correct the simulation data, and used to accurately evaluate the effect of STPV windows in southwest China. 4. Optimization of STPV window
Fig. 19. Comparison of annual energy performance of STPV with different air gap depths.
4.1. Different orientation The overall energy performance of the test room which was equipped with STPV windows with different orientations is shown in Fig. 18. It can be seen that the room with south-facing window has the lowest total annual energy consumption with 960 kWh. Although the heating load of the room with the south-facing window(447 kWh) was much higher in comparison to other directions. The total cooling energy, 399 kWh, was ultimately the least due to the reduction of the cold load in summer. The room with south-facing window can produce more power generation and has the lowest lights electric energy because PV window can
accept more solar energy and thus have better daylighting effect.
4.2. Different air gap The overall energy performance of the test room which was equipped with the STPV windows with different air gap depths is shown in Fig. 19. The energy consumption reached the highest point with 970 kWh when the air gap depth was 1 mm and lowest
Fig. 20. Comparison of annual energy performance of different WWR. Fig. 18. Comparison of annual energy performance of STPV with different orientation.
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point with 961 kWh when the air gap depth was 9 mm.It can be seen that as the air gap increases, both the cooling load and the heat load decrease. At the same time, the amount of PV power generated is also reduced. The lighting load is unaffected, and the effect of the increase in the thickness of the air gap on the light transmission effect of the window is negligible. It can be seen from the total energy consumption graph that with the increase of the air gap, the total energy consumption of the room with the STPV window was reduced in Chengdu. However, in general, the difference of air gap had little impact on annual total energy consumption. 4.3. Different window-to-wall ratio a). Different window-to-wall ratio The overall energy performance of the test room with different WWR when PV cells cover 85% of the window is shown in Fig. 20. The energy consumption reaches highest point with 1178 kWh when WWR was 0.08 and lowest point with 648 kWh when WWR was 0.83. It can be seen that as the WWR increases, the lighting energy consumption decreases, and the cooling energy consumption increases, since more solar radiation shines through the window. However, this increases the heating energy consumption since with the increase of WWR, the amount of heat lost through heat transfer through the window is greater than the solar radiation passing through the window. As the active area increases, the PV power generation also increases. Thus, the total annual energy consumption decreases with the increase of WWR as a result of the balance of the decrease and increase of energy consumption and energy generation. b). Different coverage with different WWR
Fig. 21. Comparison of annual energy performance of STPV window with different coverage.
Fig. 21 shows the overall energy performance of the test room which was equipped with STPV windows with different coverage of PV cells. It can be seen that with WWR ¼ 0.33, as the coverage increased, the total energy consumption decreased at first and then increased, reaching a minimum when the coverage ratio was 0.73. This is because as the coverage rate increases, the cooling energy consumption decreases, the power generation increases, and the heating energy consumption and lighting energy consumption increase. When the coverage is small, the reduction of cooling energy consumption and the increase of power generation plays a major role. Thus, the total energy consumption decreases with the increase of coverage. When the coverage rate increases to a certain extent, the increase of heating energy consumption and lighting energy consumption plays a major role. Thus, the total energy consumption increases with the increase of coverage. When WWR becomes larger, the lowest point of total energy consumption shifts to the right. Since WWR becomes larger, if the coverage is kept constant, the effective area of the PV cells and the area of the transparent glass increases, and the balance of energy consumption will change. At this time, the reduction of cooling energy consumption and the increase of power generation plays a major role, and the lowest point of total energy consumption can be shifted to the point of greater coverage. When the WWR was 0.50, the maximum coverage was 0.82 and when the WWR was 0.83, the maximum coverage was 0.87, and the case where the coverage ratio was 1 is a case conceived for the convenience of analysis. In order to simulate the actual use of the room, the maximum value of WWR is 0.83. Through the above analysis it can be concluded that, the room with the south facing window had the smallest total energy consumption when the WWR was 0.83, the coverage of the PV cell was 0.87 and the air gap depth was 9 mm.
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Table 5 Radiation and temperature of 5 cities. Locations
Climatic Zone
Annual global solar radiation (kWh/m2)
Average temperature in summer(o C)
Average temperature in winter(o C)
Chengdu/Capital of Sichuan Chongqing Guiyang/Capital of Guizhou Lhasa/Capital of Tibet Kunming/Capital of Yunnan
Hot Summer Cold Winter Hot Summer Cold Winter Temperate Cold Zone Temperate
1310.3 1291.8 1283.4 1812.2 1601.5
25.03 28.57 23.3 15.3 19.65
7.47 9 6.63 0.52 9.29
5. Annual energy consumption
Fig. 22. Annual energy consumption of different cities in Southwest China.
The optimized silicon PV window was applied in five selected cities located across different climate zone in Southwest China to predict and compare the energy saving potential. Annual mean solar irradiance and temperature of 5 cities are shown in Table .5 [31]. The annual energy consumption of different cities in southwest China when the room equipped with STPV windows and conventional windows is shown in Fig. 22. It can be seen that Lhasa had the highest power generation with 893 kWh after using STPV windows, and Chongqing has the worst power generation with 462 kWh. Kunming has good energy generation and the lowest energy consumption. After the use of crystalline silicon windows, the lighting energy consumption increases in all the cities. The heating energy consumption increased and the cooling energy consumption decreased. In particular, the total energy consumption of each city dropped significantly. The annual energy saving potential of STPV window compared with normal window is shown in Fig. 23. It can be seen that after using STPV windows, the room in Kunming has the highest energy saving ratio of 0.83, followed by Lhasa with ratio of 0.6. In terms of power generated, Lhasa's was larger than that of Kunming. However, Lhasa is in the cold zone and Kunming is in the temperate zone, the heating energy consumption in Lhasa is greater than that in Kunming. This leads to that the energy saving effect of STPV windows in Lhasa is not as good as in Kunming. Guiyang was last with energy saving ratio of 0.42. The energy saving ratio of all these cities was larger than 0.4, so there is good energy saving potential
Fig. 23. Annual energy saving potential of STPV window compared with normal window.
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with the use of STPV windows.
References
6. Conclusion
[1] Skandalos Nikolaos, Karamanis Dimitris. PV glazing technologies. Renew Sustain Energy Rev 2015;49. [2] Pei Gang, Ji Jie, Jiang Aiguo. Performance analysis of PV double-glazed window. Acta Energiae Solaris Sin 2009;30(4):441e4. [3] Xiao Y, Li D. Application status and development trend of solar photovoltaic building integration. Energy Saving 2010;29:12e8. [4] GB 50178-93. Standard of climatic regionalization for architecture. Ministry of Construction of China; 1993. [5] © 2017 The World Bank. Solar resource data: Solargis. Available online: https://solargis.com/maps-and-gis-data/download/china. [Accessed 15 November 2018]. [6] Myong SY, Jeon SW. Effcient outdoor performance of esthetic bifacial a-Si: H semi-transparent PV modules. Appl Energy 2016;164:312e20. [7] Sarmah N, Mallick TK. Design, fabrication and outdoor performance analysis of a low concentrating photovoltaic system. Sol Energy 2015;112:361e72. [8] Cuce E, Young CH, Riffat SB. Thermal performance investigation of heat insulation solar glass: a comparative experimental study. Energy Build 2015;86:595e600. [9] Lynn N, Mohanty L, Wittkopf S. Color rendering properties of semitransparent thin-film PV modules. Build Environ 2012;54:148e58. [10] Jong-Hwa Song, Young-Sub An, Soek-Ge Kim, Sung-Jin Lee, Jong-Ho Yoon, Youn-Kyoo Choung. Power output analysis of transparent thin-film module in building integrated photovoltaic system (BIPV). Energy Build 2008;40(11). [11] Jong-Ho Yoon, Shim Se-Ra, Sub An Young, Ho Lee Kwang. An experimental study on the annual surface temperature characteristics of amorphous silicon BIPV window. Energy Build 2013;62. [12] Li Meia, Infield David. Thermal modelling of a building with an integrated ventilated PV façade. Energy Build 2003;35:605e17. [13] Charron Remi, Andreas K, Athienitis. Optimization of the performance of double-facades with integrated photovoltaic panels and motorized blinds. Sol Energy 2006;80:482e91. [14] Shahrestani Mehdi. Experimental and numerical studies to assess the energy performance of naturally ventilated PV façade systems. Sol Energy 2017;147: 37e51. [15] Tady YY, Yang Fung H. Study on thermal performance of semi-transparent building-integrated photovoltaic glazings. Energy Build 2007;40(3). [16] Kapsis K, Dermardiros V, Athienitis AK. Daylight performance of perimeter office façades utilizing semi-transparent photovoltaic windows: a simulation study. Energy Procedia 2015;78. [17] Xu Shen, Liao Wei, Huang Jing, Kang Jian. Optimal PV cell coverage ratio for semi-transparent photovoltaics on office building façades in central China. Energy Build 2014;77. [18] Miyazaki T, Akisawa A, Kashiwagi T. Energy savings of office buildings by the use of semi-transparent solar cells for windows. Renew Energy 2005;30(3): 281e304. [19] Lu L, Law KM. Overall energy performance of semi-transparent single-glazed photovoltaic (PV) window for a typical office in Hong Kong. Renew Energy 2013;49:250e4. [20] WeiWang, Zhang Wei. Experimental assessment of the energy performance of a double-skin semi-transparent PV window in the hot-summer and coldwinter zone of China. Energies 2018;11(7):1700. [21] GBT 5699-2017. Method of daylighting measurement. Beijing: Standards Press of China; 2017. [22] China Academy of Building Research. Design code for heating ventilation and air conditioning of civil buildings. Beijing, China: China Academy of Building Research; 2016. p. 12e20. [23] EnergyPlus energy simulation software. Available online: https://energyplus. net/. [Accessed 15 November 2018]. [24] U.S. Department of Energy. EnergyPlus™ version 8.9.0: documentation engineering reference;231-232 [25] U.S. Department of energy. EnergyPlus™ version 8.9.0: documentation engineering reference;359-362 [26] Peng J, Lu L, Yang H, et al. Validation of the Sandia model with indoor and outdoor measurements for semi-transparent amorphous silicon PV modules. Renew Energy 2015;80:316e23. [27] U.S. Department of energy. EnergyPlus™ version 8.9.0: documentation engineering reference;1626-1630 [28] Meng Wang a, Peng Jinqing, Li Nianping. Assessment of energy performance of semi-transparent PV insulating glass units using a validated simulation model. Energy 2016;112:538e48. [29] ASHRAE. Ashrae guideline 14-2014: measurement of energy demand and savings. Atlanta, GA, USA: American Society of Heating, Refrigerating and AirConditioning Engineers; 2014. [30] Coakley D, Raftery P, Keane M. A review of methods to match building energy simulation models to measured data. Renew Sustain Energy Rev 2014;37: 123e41. [31] Solar and wind energy resource assessment (SWERA). 2018. Available online: https://energyplus.net/weather. [Accessed 15 November 2018].
This article systematically studies the application prospects of crystalline silicon PV windows in Southwest China. The research included the following aspects: testing, simulation, optimization, and application of STPV window. A test rig was established in Chengdu to measure the performance of the STPV window. According to the tested parameters, the simulation model was established and then validated by test results in this paper. With the simulation model, the optimization of STPV window was conducted. The application of optimized STPV windows in Southwest China was then predicted. It was found that the application of STPV window in Southwest China has good energy saving potential. The research conclusions in this article were collected as follows: A test rig was built to measure the parameters and energy performance of STPV in September 2018. During the test period, the maximum incident solar radiation upon the south façade was 545.3 W/m2. The highest efficiency of the PV windows is about 0.16 could be found when the PV window worked properly. The test results show that though the electricity generated by PV couldn't meet all building energy consumption, it could compensate for the increase of lighting energy consumption. The tested net electricity consumption is 16.8% larger than the simulated net electricity consumption. The differences are used to accurately evaluate the effect of STPV windows in southwest China. A simulation model integrated with heat transfer model, daylighting model and Sandia PV model was established to investigate the application of STPV window and was validated by the test results. There was good agreement between simulation and test results, the MBE are between 3.45% and 7.59% and the Cv (RMSE) are between 4.54% and 14.04. It is therefore reliable to be used to predict energy consumption of STPV windows. For the optimization of STPV windows, its different air gap depth, orientation, window-wall ratio and coverage were simulated. According to the simulation results, when the WWR was 0.83, the coverage of the PV cell was 0.87, and the air gap depth was 9 mm, the room with the south facing window had the lowest total energy consumption with 633 kWh. According to the energy saving prediction of five cities in southwest China, the room in Kunming had the highest energy saving ratio of 0.83, followed by Lhasa, 0.6. Guiyang is the lowest at 0.42. The energy saving ratio of all these cities was greater than 0.4. Thus, there is good energy saving potential when using STPV windows in these cities. In the Southwest of China, through the analysis above, doubleglazed crystalline silicon PV windows have a good application prospect, especially in the temperate zone. In future, the optimized PV window will be installed on the demonstration buildings in the aforementioned cities for a field test to evaluate the actual use to promote the development of PV windows in Southwest China. Acknowledgments It is supported by National Key Research and Development Program of China (No. 2016YFE0124500), Sichuan Science and Technology Program (2019YFH0184) and Science & Technology Department Foundation of Chengdu City, China (2017-GH0200006-HZ).
Contents lists available at ScienceDirect
Energy journal homepage: www.elsevier.com/locate/energy
Experimental and numerical evaluation of the crystalline silicon PV window under the climatic conditions in southwest China Mo Chen a, Wei Zhang a, *, Lingzhi Xie b, Zhichun Ni c, Qingzhu Wei c, Wei Wang a, Hao Tian a a b c
College of Architecture and Environment, Sichuan University, Chengdu, 610065, China Institute of New Energy and Low-carbon Technology, Sichuan University, Chengdu, 610065, China Suzhou Talesun Solar Technologies Co., Ltd, Suzhou, 215542, China
a r t i c l e i n f o
a b s t r a c t
Article history: Received 29 December 2018 Received in revised form 30 May 2019 Accepted 23 June 2019 Available online 26 June 2019
Windows integrated with PV can provide electrical energy and control the energy flow (heat and light) through the windows. With the objective of evaluate the potential application of window integrated PV in southwest China, the performance of silicon PV windows was comprehensively studied. A test unit was developed to monitor the performance of window integrated PV, then a validated comprehensive approach integrated with heat transfer, optical, electrical and building simulation model was used to comprehensively evaluate the performance of the window integrated PV under various climatic conditions in southwest China. The effects of the air gap on window thermal performance, window orientation, different window-to-wall ratio and coverage ratio of PV cells are evaluated. It was found that a maximum energy saving could be achieved, when the PV window is installed on the south facing façade with a PV cell coverage ratio of 0,87, air gap of 9 mm between the two glazing panes. It was found that a maximum energy saving of 983 kWh was achieved in Lhasa. A highest energy saving ratio of 83% was found in Kunming. The window integrated PV shows good energy saving potential under different climatic conditions in Southwest China. © 2019 Elsevier Ltd. All rights reserved.
Keywords: c-Si PV window BIPV Light-heat-electricity Energy consumption Southwest China
1. Introduction Building integrated photovoltaics (BIPV) converts solar energy into electrical energy and has the potential to meet building energy consumption. Significant research has been carried out to evaluate the performance of BIPV [1]. Photovoltaic windows, one type of BIPV, can provide buildings with renewable electricity while meeting the architectural aesthetic design, and reduce the energy consumption of the building [2]. In Southwest China, solar energy application is being encouraged to develop at a rapid pace owing to an abundant availability of solar radiation and sparsely populated land [3]. The use of PV windows in Southwest China is promising. However, the climatic conditions of the region are more complicated. China can be divided into five climatic zones, and southwest China houses three of them, which are Hot Summer Cold Winter Zone, Cold Zone and Temperate Zone. The solar energy resources in the southwest China
* Corresponding author. E-mail address: [email protected] (W. Zhang). https://doi.org/10.1016/j.energy.2019.06.146 0360-5442/© 2019 Elsevier Ltd. All rights reserved.
are generally rich, but the distribution is uneven. The climate zones [4] and Solar resource map [5] of China are shown in Fig. 1. In this article, Lhasa, Kunming, Chengdu, Chongqing and Guiyang were taken into consideration to study the energy saving effect of PV window in southwest China. These five cities are the provincial capitals of Southwest China with a large population. They are located in different climate zones and have different irradiation conditions. Usually, the PV cells used on STPV window are crystalline silicon solar cells(c-Si) and Amorphous silicon solar cells(a-Si). As shown in Fig. 2, crystalline silicon modules have the higher power generation efficiency but are not transparent. Thin film module has good transmittance, but its efficiency is among 4.1%e12% [6]. In recent years, the new generation of photovoltaics, concentrator photovoltaics (CPV) are used on STPV windows, which has higher power generation efficiency [7]. The presence of semi-transparent PV(STPV) windows greatly affects the solar energy through the windows and affects the load conditions, which are mainly shown as the decrease of the cooling load and the increase of heating load [8]. Also, STPV windows with
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Fig. 1. (a)Climate zone and (b)Solar resource map of China.
Fig. 2. Window integrated with different types of PV cell materials. (a).c-Si (b).a-Si (c).CPV.
appropriate transmittance also enable full use of daylight [9]. STPV windows can also affect the indoor load due to self-heating, which in turn may affect the power generation efficiency. Taking into account the influence of STPV windows on indoor load, daylighting, and power generation, the energy saving potential should be studied. In the studies of thermal-electricity performance of doublelayer PV window, most researches [10e15] mainly established a heat transfer model to simulate the thermal and electrical performance of double-layer STPV. Jong-Hwa Song et al. [10,11] established a numerical simulation model for double-layer STPV windows based on actual meteorological parameters in numerical simulation software TRNSYS. Simulation results showed that installation angle is an important factor affecting thermal and electrical performance and that 30 is the best installation angle. Tady Y.Y. Fung et al. [15] simulated thermal conduction of doublelayer PV windows using one-dimensional transient thermal equilibrium equation. The results showed that when the coverage of PV modules is close to 80%, the heat gain can be reduced by 70%. It can thus be concluded that the coverage area of PV modules has the greatest impact on indoor heating. Another focus of the research was double-layer PV windows as semi-transparent enclosure and their light-electricity performance. K. Kapsis et al. [16] used Daysim to study the indoor lighting of different film transmittances. The results showed that the opticalelectrical performance of the thin film photovoltaic window was optimal when the light transmittance was 30%. Shen Xu et al. [17] simulated the performance of crystalline silicon component
coverage on the photovoltaic performance. The results show that the higher photovoltaic coverage rate is suitable for buildings with large window to wall ratio and deep buildings, which increases the total power generation but reduces the photoelectric conversion efficiency. For the study on energy consumption, Miyazaki T [18] investigated a double layer amorphous silicon PV window by simulation study. It was found that the minimum electricity consumption can be achieved when solar cell transmittance is 40% and WWR is 50%. The electricity consumption could be reduced by 55% with the optimized PV window. A comprehensive methodology was developed by Lu L [19] to study the thermal and electrical performance of single-layer STPV window in Hong Kong. The total heat gain, electricity generation and daylight illuminance are included. The findings show that the primary factor of energy saving is thermal performance and the secondary is electricity consumption of artificial lighting. Most of previous research for PV windows were aimed at the amorphous silicon PV window, and the systematic research needs to be improved. In this article, the c-Si PV windows with reasonable crystal silicon arrangement, which has a higher conversion efficiency is used as the study object. There are limited studies about Southwest China despite rich solar resources, complex climatic conditions and diverse geographical conditions, in which the application of STPV window needs to be further investigated. This paper relies on the National Key Research and Development Program of China to study the application of BIPV in western China, especially solar windows, and pay more attention to the energy-
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saving effect of PV windows in practical application in Southwest China. Therefore, in light of the comprehensive process of three factors, light-heat-electricity, two comparison test units with c-Si PV and conventional windows were set up to test the performance and energy saving. The application effect of the c-Si PV window was investigated systematically, including energy consumption testing, energy consumption simulation, PV window design optimization and energy saving. A three-factor simulation model was established, and verified by the test results. In order to optimize the STPV window, its air gap depth, orientation, window-wall ratio and coverage were analyzed. The energy consumption of the test is compared with that of the simulation in order to correct the simulation results. Furthermore, five cities located in different climate zone in Southwest China were selected to predict and compare the energy saving potential of the buildings installed with the optimized c-Si PV window. 2. Methodology 2.1. STPV window module According to our previous study [20] on the STPV windows in southwest China, we and the industry partners jointly developed cSi PV windows with reasonable crystal silicon arrangement. The dimension of STPV window and the layout of PV cells are shown in Fig. 3. Fig. 3(a) is the layout of STPV window, and Fig. 3(b) a picture of real STPV window. The STPV window consists of three parts. The outermost layer is a 4 mm translucent photovoltaic glazing layer, the inner layer is an 5 mm conventional transparent glass, and the air gap is 9 mm. The detailed parameters are shown in Table .1.
front of the windows. The test was conducted in September 2018, in which the power generation is relatively higher. The test rig is shown in Fig. 4. The outdoor test equipment consisted of a weather station and an irradiance meter that measured global vertical solar irradiance. The weather station measures outdoor temperature and humidity, wind direction, wind speed, etc. The irradiance meter measured the solar irradiance in the direction of the window. The schematic diagram of the indoor environment test instruments was shown in Fig. 5(a) [20]. The double-skin window related parameters like IeV curve, solar radiation upon south façade, generation power was measured by the PV testing equipment. According to the “Method of daylighting measurements” (GB/T 5699-2017) [21], 4 points were evenly distributed indoors to test indoor daylighting illumination. Wireless lighting sensors were used to measure the illumination on the work surface. The height of the lighting sensors is 1.3 m and the horizontal position of the measuring point is as shown in Fig. 5(b). The experimental data except electrical parameters were collected by a wireless multi-channel data recorder with a sampling interval of 2 min. The temperature of the outer surface of PV window, and ambient temperature of the test unit were tested by seven T-type thermocouples, the position of the measuring point is as shown in Fig. 5(c). To get the indoor energy consumption, the energy consumption of the air-conditioner and lighting were collected by the electric quantity recorder. The quantity recorder is made by BULL and can transfer data through a wireless network. When the indoor illumination is less than 500lx, the light will turn on automatically. And if the indoor temperature is above 28 o C, the air conditioner will turn on automatically [22]. All the key instruments and their specifications have been shown in Table 2. 2.3. Simulation model
2.2. Test rig and instruments In order to test energy consumption and study the accuracy of the simulation model, a test rig was established in Chengdu. Chengdu is located in the central part of Sichuan Province, west of the Sichuan Basin, between 102 540 ~104 530 east longitude and 30 050 ～31260 north latitude. As shown in Fig. 4, the test rig has a length and a width of 3 m each, the wall of the window was 3.2 m high, and the wall of the window was 3 m high. The test rig is built on a flat surface with windows facing south and no obstructions in
In order to simulate the overall performance of the double-layer c-Si window in southwest China, a light-heat-electricity threefactor model was established using the lighting model, heat transfer model and Sandia model in EnergyPlus [23]. The temperature of the glass panel, the indoor illumination, and the power generation performance of the photovoltaic window were tested. The test results were used as verification of the simulation model. a) Daylighting model EnergyPlus controls the intensity of the light according to natural daylighting, keeping the reference point at a certain illumination. For the calculation of natural daylighting, there are mainly the following steps: calculating the daylight factor, calculating the natural illuminance, and calculating the required lighting power consumption [24]. b) Heat balance model
Fig. 3. C-Si PV window, (a)layout (b)real picture.
In EnergyPlus, the window glass face temperatures are determined by solving the heat balance equations on each face every time step. For a window with N glass layers there are 2 N faces and therefore 2 N equations to solve. Fig. 6 shows the variables used for double glazing (N ¼ 2). The four equations for double-glazing are as follows [25].where,Eo and Ei is exterior and interior long-wave radiation incident on window respectively. εi is the emissivity of face i. qi is the temperature of face i. ki is the conductance of glass layer i. ka is the conductance of air gap.ho and hi are the outside and inside air film convective conductance, respectively. To and Ti are outdoor and indoor air temperature respectively. Si is radiation (short-ware, and long wave from zone internal sources) absorbed
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Table 1 The dimension, layout and structure of STPV window. a. The dimension and layout of STPV window Glazing Size(m m) 1.24 0.64 b. Structure of STPV window Layer/Property Single STPV window Air gap Glass-tempered
PV cell size(mm mm) 155 155 Thickness(mm) 4 9 5
Fig. 4. Test rig.
PV cell number 28
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Fig. 5. Indoor environment test instruments.
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Table 2 The key instruments and their specifications. Equipment
Manufacture
Function and Model
Accuracy/Sensitivity
Multi-channel PV test equipment Solar radiation test equipment Weather station
Ceyear AV6595A AV87110 J.t
PV testing (three 500W module and one 10 kW module) Testing the solar radiation upon the south façade Weather condition recorder
0We10 kW
Thermocouples Light meter Electricity recorder Multi-channel data recorder
J.t J.t BULL J.t
Temperature test (T type thermocouple) e Record electricity consumption Data collector
by face i.
Eo ε1 ε1 sq41
0e1800 W/m2; ±3% Temperature: ±0.5 C, humidity: 0.1%,±2%; atmospheric pressure: 1 mbar; wind rate: 0.1 m/s; wind direction: ±5% 200Ce100 C; 0.1 C; ±0.5 C 0e100,000 lux; 1 lux; ±4% 0e3000W, ±1% The minimum resolutions are 1 mV and 0.1 C
Pmp ¼ Imp ,Vmp þ k1 ðq2 q1 Þ þ ho ðTo q1 Þ þ S1 ¼ 0
k1 ðq1 q2 Þ þ ka ðq3 q2 Þ þ s
(1)
ε2 ε3 q4 q42 þ S2 1 ð1 ε2 Þð1 ε3 Þ 3
¼0 (2) h1 ðq2 q3 Þ þ k2 ðq4 q3 Þ þ s
ε2 ε3 q4 q43 þ S3 1 ð1 ε2 Þð1 ε3 Þ 2
¼0 (3) Ei ε4 ε4 sq44 þ k2 ðq3 q4 Þ þ hi ðTi q4 Þ þ S4 ¼ 0
(4)
c) Sandia PV model The Sandia PV model is an empirical based model and is tightly coupled with the thermal model in EnergyPlus. Peng J et al. [26] has validated the Sandia model with indoor and outdoor measurements for semi-transparent amorphous silicon PV modules. Eqs. (5)e(9) [27] summarize the Sandia model.
h Isc ¼ Isco ,f1 ðAMa Þ, Eb , f2 ðAOIÞ þ fd , Ediff . i Eo ,½1 þ aIsc , ðTc To Þ
(5)
Imp ¼ Impo , C0 , Ee þ C1 , E2e , 1 þ aImp , ðTc To Þ
(6)
Voc ¼ Voco þ Ns ,dðTc Þ,lnðEe Þ þ bVoc ðEe Þ,ðTc Te Þ
(7)
(9)
where, Isc is the short-circuit current (A); Imp is the current at the maximum power point (MPP) (A); Voc is the open circuit voltage (V); Vmp is the voltage at the MPP (V); Imp0 is the current at the MPP under STC (A); Isc0 is the short-circuit current under STC (A); Vmp0 is the voltage at the MPP under STC (V); Voc0 is the open circuit voltage under STC (V); Ee is the effective irradiance (suns); Tc is the PV module's operating temperature (o C); T0 is the temperature of STC, it is 25 o C; Ns is the number of solar cells in series; dðTcÞ is the thermal voltage; aImp is the temperature coefficient of Imp ; aIsc is the temperature coefficient of Isc ; bVmp is the temperature coefficient of Vmp ; bVoc is temperature coefficient of Voc ; f ðAMaÞ is an empirical function of absolute air mass (AMa), it was introduced to correct the impact of solar spectrum on the short-circuit current, Isc ; C0 through C7 are dimensionless parameters needed to be fitted. C0 and C1 are empirically determined coefficients which relate Imp to the effective irradiance, Ee , C0 þ C1 ¼ 1, (dimensionless); C2 and C3 are empirically determined coefficients which relate Vmp to the effective irradiance (C2 is dimensionless, and the unit of C3 is 1 =V). 2.4. Model set up In this simulation, the room using double-layer STPV windows was compared with the room with ordinary double-layer windows. The structure of STPV window is shown in Fig. 3. The normal window consists of a 4 mm normal glazing layer, 9 mm air gap and a 5 mm normal glazing layer. Specific glass parameters are shown in Table .3. The length and width of the test rooms are 3 m 3 m. The height of the wall against window is 3 m, and the height of the wall where the window is located is 3.2 m. The room model is shown in Fig. 7. The photovoltaic panel is the polycrystalline silicon photovoltaic panel, and the coverage of PV cells is 0.72. The photovoltaic panel parameters were measured by Talesun and are shown in Table .4. According to the HVAC design requirements for China Office Building [22], the indoor air temperature was designed as 28 o C in summer and 18 o C in winter. When the indoor illumination at the working plane is less than 500lx [21], the light will turn on
Vmp ¼ Vmpo þ C2 ,Ns ,dðTc Þ,lnðEe Þ þ C3 ,N3 ,½dðTc Þ,lnðEe Þ2 þ bVmp ðEe Þ,ðTc To Þ
(8)
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fluctuation trend of outdoor temperature is similar to that of solar radiation. During the period of 1st/sep to 7th/sep, there were 4 sunny days, 2 cloudy-sunny days and 1 cloudy day. The test results of these days were selected to validate the simulation model. b). The I-V curve The I-V curve of the STPV window at 10:01, the 4th, is shown in Fig. 9. It was found that the open circuit voltage was 78.11 V. The short-circuit current was 2.46 A. The maximum power of the STPV window was 157.17W and the fill factor of the STPV window was 81%. The IeV curve was smooth and the PV window worked properly. c). The efficiency of the PV window
Fig. 6. Glazing system with two glass layers.
automatically. To couple the heat transfer and energy balance, the ‘Integrated Surface Outside Face’ was chosen for setting the cell temperature of STPV windows.
3. Test results and validation of simulation model of the PV window 3.1. Test results a). The incident solar irradiation upon the south façade in a month is shown in Fig. 8(a). The maximum incident solar radiation upon the south façade was 545.3 W/m2 in 28th/sep. The outdoor temperature is shown in Fig. 8(b). It can be seen that the
The efficiency of the PV window is shown in Fig. 10. The selected days for analysis were a sunny day (4th/sep), a cloudy-to-sunny day (6th/sep), and a cloudy day (5th/sep). During the sunny day, from morning to afternoon, the efficiency of the PV window firstly increases and then decreases. On the cloudy-to-sunny day, the efficiency maintains between 0.12 and 0.14. On cloudy day, the efficiency fluctuates greatly before 14:00, and after 15:00, the efficiency maintains between 0.11 and 0.14. From Fig. 10, the efficiency of the PV windows is larger than 0.11 when working properly. d). Average indoor illuminance The Average indoor illuminance in September is shown in Fig. 11. It can be seen that compared to sunny days, there are more cloudy days in September. But due to the larger window-wall ratio and the larger proportion of scattered radiation in Chengdu, the indoor illumination can still meet the lighting needs in most of the daytime.
Table 3 Parameters of glazing.
STPV Glazing Clear 4 mm Clear 5 mm
Thickness(mm)
Solar Transmittance at Normal Incidence
Visible Transmittance at Normal Incidence
Conductivity (W/m$k)
4 4 5
0.224 0.824 0.811
0.225 0.893 0.887
0.0415 0.0133 0.0133
Fig. 7. Room model.
M. Chen et al. / Energy 183 (2019) 584e598 Table 4 Parameters of STPV. Parameters
Value
Active area, A(m2) Number of cells in series, Ns Number of cells in parallel, Np Short circuit current, Isc(A) Open circuit voltage, Voc(V) Current at the maximum power point, Imp(A) Voltage at the maximum power point, Vmp(V)
3.3635 140 1 6.986 85.6 6.221 68.3
e). The tested energy consumption The daily tested energy consumption of the room with STPV window in September is shown in Fig. 12. It can be seen that because the solar radiation has a great influence on the room heat gain, the fluctuation trend of energy consumption for cooling and
591
PV power generation is similar. Due to the large proportion of scattered radiation in Chengdu and its small proportion in building energy consumption, the fluctuation of lighting energy consumption is not obvious. The test energy consumption of rooms with STPV window and conventional window in September is shown in Fig. 13. From the energy consumption and productivity composition, air conditioning energy consumption is still the main energy consumption of buildings. Compared with the room with ordinary windows, lighting energy consumption of the room with PV windows has increased by 12.95 kWh, but the energy consumption of air conditioning has decreased by 22.13 kWh. The test results show that the electricity generated by PV can't meet all building energy consumption, but can compensate for the increase of lighting energy consumption, which is caused by the occlusion of photovoltaic modules.
Fig. 8. Outdoor test results.
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Fig. 9. I-V curve.
Fig. 10. Efficiency of the PV window.
Fig. 11. Average indoor illuminance.
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the window outside surface temperature, the illuminance of the test room and the power generation of STPV window were tested. The test results were used to validate the simulation model. Seven days are selected to validate the simulation model. There were 4 sunny days, 2 cloudy-sunny days and 1 cloudy day amongst the selected 7 days. To assess the accuracy of the simulation model, two statistical indices, viz. mean bias error (MBE) and the coefficient of variation of root mean square error (Cv(RMSE)), were chosen to evaluate the deviation between the simulated results and the measured data [28]. ASHRAE Guideline 14 suggests that if the MBE and Cv(RMSE) of a building energy simulation model fall within 10% and 30% respectively, it can be regarded as an acceptable model in accuracy [29,30]. Equations of calculating MBE and Cv(RMSE) are as follows:
PN MBEð%Þ ¼
Fig. 12. The daily tested energy consumption/generation.
i¼1 ðmi si Þ PN i¼1 mi
Cv ðRMSEÞð%Þ ¼
(10)
rffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi . ffi PN 2 N i¼1 ðmi si Þ m
(11)
where, mi and si are the measured and simulated data for the instance ‘i’, respectively; N is the number of data points; m is the average value of the all measured data. a). Validation of silicon surface temperature
Fig. 13. The total energy consumption in September.
3.2. Validation of simulation model of the PV window Beside the solar irradiation and the efficiency of the PV window,
The test result of outer surface temperature of the STPV window from 1st/sep to 7th/sep is shown in Fig. 14. The temperature reached the highest point in 4th/sep with about 55o C. From 5th/sep to 7th/sep, the temperature was relatively lower, since those days were rainy or cloudy. On sunny days, the outer surface temperature of the STPV window was very high with the temperature greater than 40o C for majority of the daytime. A comparison between the simulated and the measured outer surface temperature of the STPV window is presented in Fig. 14. The measured value of the photovoltaic window outer surface temperature is close to the simulated value. The MBE is 3.45%, and the Cv(RMSE) is 4.54%. This shows that the window heat transfer conditions in the simulation match those of the test.
Fig. 14. Temperature comparison.
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b). Validation of daylight illuminance Fig. 15 presents the comparison results between the simulated and the measured indoor daylight illuminance at the reference point. The illuminance at reference point reached the highest point at 4th/sep with about 1300lux. Within sunny days, the illuminance of reference point was larger than 300lux for about 8 h. During the period of 5th/sep to 7th/sep, the illuminance was relatively lower than other days. From Fig. 15, the simulation results are similar to the test results. The calculation results show that the MBE was 7.59% and the Cv (RMSE) was 14.04%. Therefore, the lighting model is acceptable in terms of accuracy. c). Validation of electricity generation
Fig. 17. The comparison between the tested and simulated energy consumption/ generation.
The test result of power of electricity generated during the period of 1st/sep to 7th/sep are shown in Fig. 16. The temperature reached the highest point on 4th/sep with about 200W. From 5th/ sep to 7th/sep, the power was relatively lower since those days were rainy or cloudy. It can be seen in Fig. 16 that the power of simulated photovoltaic panel electricity generation and test value were within the acceptable range. The calculation results show that the MBE
was 6.16% and the Cv(RMSE) was 12.26%. Therefore, the PV model is acceptable in terms of accuracy. Through the aforementioned experimental verification, it can be shown that the simulation model can simulate the real operation of the room. Therefore, the validated simulation model was used for optimization of STPV window and annual energy analysis.
Fig. 15. Reference Point Illuminance comparison.
Fig. 16. Comparison of Power of STPV window.
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3.3. The comparison between the tested and simulated energy consumption/generation The comparison between the tested and simulated energy consumption/generation is shown in Fig. 17. It can be seen that the simulated lighting energy consumption and cooling energy consumption are less than the test, and the simulated PV power generation is slightly larger than the test. The simulation results of lighting energy consumption and power generation are similar to the test results, but the simulation results of cooling energy consumption are different from the test results. One reason is that daylighting energy consumption and PV power generation are small. Another reason is that there is a difference between the simulation and the test in terms of the process of air conditioning. The tested net electricity consumption is 16.8% larger than the simulated net electricity consumption. The area of the test unit is small, but with a large building, the difference could be more obvious. As a result, when calculating the net building power consumption, it should be taken into account the loss energy of equipment in actual operation. The differences between the test and simulation data are analyzed to correct the simulation data, and used to accurately evaluate the effect of STPV windows in southwest China. 4. Optimization of STPV window
Fig. 19. Comparison of annual energy performance of STPV with different air gap depths.
4.1. Different orientation The overall energy performance of the test room which was equipped with STPV windows with different orientations is shown in Fig. 18. It can be seen that the room with south-facing window has the lowest total annual energy consumption with 960 kWh. Although the heating load of the room with the south-facing window(447 kWh) was much higher in comparison to other directions. The total cooling energy, 399 kWh, was ultimately the least due to the reduction of the cold load in summer. The room with south-facing window can produce more power generation and has the lowest lights electric energy because PV window can
accept more solar energy and thus have better daylighting effect.
4.2. Different air gap The overall energy performance of the test room which was equipped with the STPV windows with different air gap depths is shown in Fig. 19. The energy consumption reached the highest point with 970 kWh when the air gap depth was 1 mm and lowest
Fig. 20. Comparison of annual energy performance of different WWR. Fig. 18. Comparison of annual energy performance of STPV with different orientation.
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point with 961 kWh when the air gap depth was 9 mm.It can be seen that as the air gap increases, both the cooling load and the heat load decrease. At the same time, the amount of PV power generated is also reduced. The lighting load is unaffected, and the effect of the increase in the thickness of the air gap on the light transmission effect of the window is negligible. It can be seen from the total energy consumption graph that with the increase of the air gap, the total energy consumption of the room with the STPV window was reduced in Chengdu. However, in general, the difference of air gap had little impact on annual total energy consumption. 4.3. Different window-to-wall ratio a). Different window-to-wall ratio The overall energy performance of the test room with different WWR when PV cells cover 85% of the window is shown in Fig. 20. The energy consumption reaches highest point with 1178 kWh when WWR was 0.08 and lowest point with 648 kWh when WWR was 0.83. It can be seen that as the WWR increases, the lighting energy consumption decreases, and the cooling energy consumption increases, since more solar radiation shines through the window. However, this increases the heating energy consumption since with the increase of WWR, the amount of heat lost through heat transfer through the window is greater than the solar radiation passing through the window. As the active area increases, the PV power generation also increases. Thus, the total annual energy consumption decreases with the increase of WWR as a result of the balance of the decrease and increase of energy consumption and energy generation. b). Different coverage with different WWR
Fig. 21. Comparison of annual energy performance of STPV window with different coverage.
Fig. 21 shows the overall energy performance of the test room which was equipped with STPV windows with different coverage of PV cells. It can be seen that with WWR ¼ 0.33, as the coverage increased, the total energy consumption decreased at first and then increased, reaching a minimum when the coverage ratio was 0.73. This is because as the coverage rate increases, the cooling energy consumption decreases, the power generation increases, and the heating energy consumption and lighting energy consumption increase. When the coverage is small, the reduction of cooling energy consumption and the increase of power generation plays a major role. Thus, the total energy consumption decreases with the increase of coverage. When the coverage rate increases to a certain extent, the increase of heating energy consumption and lighting energy consumption plays a major role. Thus, the total energy consumption increases with the increase of coverage. When WWR becomes larger, the lowest point of total energy consumption shifts to the right. Since WWR becomes larger, if the coverage is kept constant, the effective area of the PV cells and the area of the transparent glass increases, and the balance of energy consumption will change. At this time, the reduction of cooling energy consumption and the increase of power generation plays a major role, and the lowest point of total energy consumption can be shifted to the point of greater coverage. When the WWR was 0.50, the maximum coverage was 0.82 and when the WWR was 0.83, the maximum coverage was 0.87, and the case where the coverage ratio was 1 is a case conceived for the convenience of analysis. In order to simulate the actual use of the room, the maximum value of WWR is 0.83. Through the above analysis it can be concluded that, the room with the south facing window had the smallest total energy consumption when the WWR was 0.83, the coverage of the PV cell was 0.87 and the air gap depth was 9 mm.
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Table 5 Radiation and temperature of 5 cities. Locations
Climatic Zone
Annual global solar radiation (kWh/m2)
Average temperature in summer(o C)
Average temperature in winter(o C)
Chengdu/Capital of Sichuan Chongqing Guiyang/Capital of Guizhou Lhasa/Capital of Tibet Kunming/Capital of Yunnan
Hot Summer Cold Winter Hot Summer Cold Winter Temperate Cold Zone Temperate
1310.3 1291.8 1283.4 1812.2 1601.5
25.03 28.57 23.3 15.3 19.65
7.47 9 6.63 0.52 9.29
5. Annual energy consumption
Fig. 22. Annual energy consumption of different cities in Southwest China.
The optimized silicon PV window was applied in five selected cities located across different climate zone in Southwest China to predict and compare the energy saving potential. Annual mean solar irradiance and temperature of 5 cities are shown in Table .5 [31]. The annual energy consumption of different cities in southwest China when the room equipped with STPV windows and conventional windows is shown in Fig. 22. It can be seen that Lhasa had the highest power generation with 893 kWh after using STPV windows, and Chongqing has the worst power generation with 462 kWh. Kunming has good energy generation and the lowest energy consumption. After the use of crystalline silicon windows, the lighting energy consumption increases in all the cities. The heating energy consumption increased and the cooling energy consumption decreased. In particular, the total energy consumption of each city dropped significantly. The annual energy saving potential of STPV window compared with normal window is shown in Fig. 23. It can be seen that after using STPV windows, the room in Kunming has the highest energy saving ratio of 0.83, followed by Lhasa with ratio of 0.6. In terms of power generated, Lhasa's was larger than that of Kunming. However, Lhasa is in the cold zone and Kunming is in the temperate zone, the heating energy consumption in Lhasa is greater than that in Kunming. This leads to that the energy saving effect of STPV windows in Lhasa is not as good as in Kunming. Guiyang was last with energy saving ratio of 0.42. The energy saving ratio of all these cities was larger than 0.4, so there is good energy saving potential
Fig. 23. Annual energy saving potential of STPV window compared with normal window.
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with the use of STPV windows.
References
6. Conclusion
[1] Skandalos Nikolaos, Karamanis Dimitris. PV glazing technologies. Renew Sustain Energy Rev 2015;49. [2] Pei Gang, Ji Jie, Jiang Aiguo. Performance analysis of PV double-glazed window. Acta Energiae Solaris Sin 2009;30(4):441e4. [3] Xiao Y, Li D. Application status and development trend of solar photovoltaic building integration. Energy Saving 2010;29:12e8. [4] GB 50178-93. Standard of climatic regionalization for architecture. Ministry of Construction of China; 1993. [5] © 2017 The World Bank. Solar resource data: Solargis. Available online: https://solargis.com/maps-and-gis-data/download/china. [Accessed 15 November 2018]. [6] Myong SY, Jeon SW. Effcient outdoor performance of esthetic bifacial a-Si: H semi-transparent PV modules. Appl Energy 2016;164:312e20. [7] Sarmah N, Mallick TK. Design, fabrication and outdoor performance analysis of a low concentrating photovoltaic system. Sol Energy 2015;112:361e72. [8] Cuce E, Young CH, Riffat SB. Thermal performance investigation of heat insulation solar glass: a comparative experimental study. Energy Build 2015;86:595e600. [9] Lynn N, Mohanty L, Wittkopf S. Color rendering properties of semitransparent thin-film PV modules. Build Environ 2012;54:148e58. [10] Jong-Hwa Song, Young-Sub An, Soek-Ge Kim, Sung-Jin Lee, Jong-Ho Yoon, Youn-Kyoo Choung. Power output analysis of transparent thin-film module in building integrated photovoltaic system (BIPV). Energy Build 2008;40(11). [11] Jong-Ho Yoon, Shim Se-Ra, Sub An Young, Ho Lee Kwang. An experimental study on the annual surface temperature characteristics of amorphous silicon BIPV window. Energy Build 2013;62. [12] Li Meia, Infield David. Thermal modelling of a building with an integrated ventilated PV façade. Energy Build 2003;35:605e17. [13] Charron Remi, Andreas K, Athienitis. Optimization of the performance of double-facades with integrated photovoltaic panels and motorized blinds. Sol Energy 2006;80:482e91. [14] Shahrestani Mehdi. Experimental and numerical studies to assess the energy performance of naturally ventilated PV façade systems. Sol Energy 2017;147: 37e51. [15] Tady YY, Yang Fung H. Study on thermal performance of semi-transparent building-integrated photovoltaic glazings. Energy Build 2007;40(3). [16] Kapsis K, Dermardiros V, Athienitis AK. Daylight performance of perimeter office façades utilizing semi-transparent photovoltaic windows: a simulation study. Energy Procedia 2015;78. [17] Xu Shen, Liao Wei, Huang Jing, Kang Jian. Optimal PV cell coverage ratio for semi-transparent photovoltaics on office building façades in central China. Energy Build 2014;77. [18] Miyazaki T, Akisawa A, Kashiwagi T. Energy savings of office buildings by the use of semi-transparent solar cells for windows. Renew Energy 2005;30(3): 281e304. [19] Lu L, Law KM. Overall energy performance of semi-transparent single-glazed photovoltaic (PV) window for a typical office in Hong Kong. Renew Energy 2013;49:250e4. [20] WeiWang, Zhang Wei. Experimental assessment of the energy performance of a double-skin semi-transparent PV window in the hot-summer and coldwinter zone of China. Energies 2018;11(7):1700. [21] GBT 5699-2017. Method of daylighting measurement. Beijing: Standards Press of China; 2017. [22] China Academy of Building Research. Design code for heating ventilation and air conditioning of civil buildings. Beijing, China: China Academy of Building Research; 2016. p. 12e20. [23] EnergyPlus energy simulation software. Available online: https://energyplus. net/. [Accessed 15 November 2018]. [24] U.S. Department of Energy. EnergyPlus™ version 8.9.0: documentation engineering reference;231-232 [25] U.S. Department of energy. EnergyPlus™ version 8.9.0: documentation engineering reference;359-362 [26] Peng J, Lu L, Yang H, et al. Validation of the Sandia model with indoor and outdoor measurements for semi-transparent amorphous silicon PV modules. Renew Energy 2015;80:316e23. [27] U.S. Department of energy. EnergyPlus™ version 8.9.0: documentation engineering reference;1626-1630 [28] Meng Wang a, Peng Jinqing, Li Nianping. Assessment of energy performance of semi-transparent PV insulating glass units using a validated simulation model. Energy 2016;112:538e48. [29] ASHRAE. Ashrae guideline 14-2014: measurement of energy demand and savings. Atlanta, GA, USA: American Society of Heating, Refrigerating and AirConditioning Engineers; 2014. [30] Coakley D, Raftery P, Keane M. A review of methods to match building energy simulation models to measured data. Renew Sustain Energy Rev 2014;37: 123e41. [31] Solar and wind energy resource assessment (SWERA). 2018. Available online: https://energyplus.net/weather. [Accessed 15 November 2018].
This article systematically studies the application prospects of crystalline silicon PV windows in Southwest China. The research included the following aspects: testing, simulation, optimization, and application of STPV window. A test rig was established in Chengdu to measure the performance of the STPV window. According to the tested parameters, the simulation model was established and then validated by test results in this paper. With the simulation model, the optimization of STPV window was conducted. The application of optimized STPV windows in Southwest China was then predicted. It was found that the application of STPV window in Southwest China has good energy saving potential. The research conclusions in this article were collected as follows: A test rig was built to measure the parameters and energy performance of STPV in September 2018. During the test period, the maximum incident solar radiation upon the south façade was 545.3 W/m2. The highest efficiency of the PV windows is about 0.16 could be found when the PV window worked properly. The test results show that though the electricity generated by PV couldn't meet all building energy consumption, it could compensate for the increase of lighting energy consumption. The tested net electricity consumption is 16.8% larger than the simulated net electricity consumption. The differences are used to accurately evaluate the effect of STPV windows in southwest China. A simulation model integrated with heat transfer model, daylighting model and Sandia PV model was established to investigate the application of STPV window and was validated by the test results. There was good agreement between simulation and test results, the MBE are between 3.45% and 7.59% and the Cv (RMSE) are between 4.54% and 14.04. It is therefore reliable to be used to predict energy consumption of STPV windows. For the optimization of STPV windows, its different air gap depth, orientation, window-wall ratio and coverage were simulated. According to the simulation results, when the WWR was 0.83, the coverage of the PV cell was 0.87, and the air gap depth was 9 mm, the room with the south facing window had the lowest total energy consumption with 633 kWh. According to the energy saving prediction of five cities in southwest China, the room in Kunming had the highest energy saving ratio of 0.83, followed by Lhasa, 0.6. Guiyang is the lowest at 0.42. The energy saving ratio of all these cities was greater than 0.4. Thus, there is good energy saving potential when using STPV windows in these cities. In the Southwest of China, through the analysis above, doubleglazed crystalline silicon PV windows have a good application prospect, especially in the temperate zone. In future, the optimized PV window will be installed on the demonstration buildings in the aforementioned cities for a field test to evaluate the actual use to promote the development of PV windows in Southwest China. Acknowledgments It is supported by National Key Research and Development Program of China (No. 2016YFE0124500), Sichuan Science and Technology Program (2019YFH0184) and Science & Technology Department Foundation of Chengdu City, China (2017-GH0200006-HZ).