Correlation for Estimating Solar Cell Temperature Based on a Tropical Field Operation of a Photovoltaic System Azah Mohamed
Tamer Khatib
Department of Electrical, Electronic, and Systems Engineering
Institute of Networked & Embedded Systems/Lakeside Labs Alpen-Adria-Universität Klagenfurt Klagenfurt, Austria,
[email protected]
UniversitiKebangsaanMalaysia Bangi, Malaysia
[email protected] Abstract-Efficiency of a solar cell strongly depends on the cell temperature, Tc which is calculated using the ambient temperatureand the reference value of the cell temperature known as the nominal operating cell temperature (NOCT). This paper presents the development of a new NOCT applicable for tropical regions and it is called as the tropical field operation cell temperature (tFOCT). A new equation for calculating cell temperature is developed by determining a new value for the tFOCT and its measuring conditions, which are solar radiation, ambient temperature, and wind speed. These conclusions are based on the condition of the tropical weather environment as a unique approach for field value adaptation. Site monitoring and analysis of the installed system were performed for 10 consecutive months at the Universiti Kebangsaan Malaysia. The results show that the suitable weather conditions for measuring tFOCT are irradiance of 954 W/m2, ambient temperature of 330 °C,and wind speed of 1.5 m/s. The proposed correlation model between ambient temperature and solar radiation and the cell temperature is useful for PV manufacturers who intend to install their PV products in tropical countries. Index Terms-- NOCT, cell temperature, PV systems,
tropical condition. I. INTRODUCTION Global energy consumption is expected to rise by 1.6% annually or by 45% in total for the next 20 years. In Malaysia, the demand for electricity is forecasted to be around 19,000 megawatts (MW) in 2020, escalating to 23,000 MW by 2030 [1]. The Malaysian government recently showed growing interestinrenewable energy sources. This national concern was highlighted during the recent official launching of the green technology policy.The policy contained five strategic thrusts that focus on strengthening the institutional framework, providing a conducive environment for green technology development, intensifying human capital development by introducing green collar jobs, supporting green technology research and innovations, and upgrading promotion and public awareness. This policy also includes long-term goals that extend to the 12th Malaysia Plan (2021 to 2025) [1].
978-1-4799-3656-4/14/$31.00 ©2014 IEEE
The characteristics of Malaysian weather feature a climate of uniform temperature with high humidity and rainfall and generally light wind. The land is situated in the equatorial doldrums’ spot, where attaining a full day with completely clear skies is almost impossible even during the drought season. Having a stretch of a few days with completely no sunshine is also rare, except during the northeast monsoon seasons. The Malaysian tropical climate can be categorized based onfourdifferent seasons, namely, Northeast Monsoon (November to February), First intermonsoon (March to May), Southwest Monsoon (June to August), and Second intermonsoon (September to October). Most of the areas in peninsular Malaysia also receive strong sun radiation with average readings from 14 MJ/m2to 18 MJ/m2 for approximately 6 h daily [2]. Therefore, photovoltaic (PV) technology is adopted by the renewable energy policy approved by the Malaysian government given that PV systems are clean, environment friendly, and secure energy sources. However, the size and performance of the PV system strongly depends on the available solar energy and ambient temperature; thus, extensive studies related to the solar energy and ambient temperature at the site of system installationis necessary to optimize the system [3]. The application of solar PV requires an in-depth consideration of these typical meteorological data to ensure more sustainable and reliable energy generation. Solar cell temperature inversely affects the PV output voltage in which high cell temperatures reduce the voltage of the cell, and consequently, the output voltage of the PV system [4]. Increasing the temperature of the PV cell by 1° decreases the power of the PV module by 0.5% to 0.6%. Therefore, precise estimation ofthe cell temperature of a PV system installed at a specific site is very important because this estimation affects the size and performance of the system [4]. The standard approach for defining efficiency of a solar cell strongly depends on the cell temperature, Tc which is calculated using the ambient temperature and the reference value of the cell temperature known as the nominal operating
cell temperature (NOCT). NOCT is defined as the temperature reached by the open-circuited cells in a photovoltaic module under conditions of 800 W/m2 irradiance on the cell surface, 20 °C air temperature, and 1 m/s wind velocity. However, these conditions may vary depending on the climate zone nature. In this research, a new terminology of NOCT called as the tropical field operation cell temperature (tFOCT) is introduced. Therefore, the main objective of this paper is to develop a correlation model between ambient temperature and solar radiation and the cell temperature for a PV system installed in Malaysia. The correlation model is derived from the new weather conditions for measuring the NOCT. In this research, the data for a 10-month yield experience of a PV system installed at Universiti Kebangsaan Malaysia is used. II.
THE TEMPERATURE ELEMENT IN STANDARD TESTING CONDITION
The temperature element effect on the efficiency of PVcells and modules involving the elements of photocurrent, absorption of energy, and solar radiation has been studied for the past few decades. Osterwald in [5] explained that temperature measurements of a PV module are difficult to conduct because the temperature measurement of the surface of the PV module usually leads to an error because of the temperature difference between the surface and the cells laminated inside. This statement is supported by the fact that solar cell construction is firmly enclosed for moisture protection, which makes the process of installing the thermocouple sensor for temperature measurements difficult [4]. However, the standard testing condition (STC) described in the MS/IEC 61836 standards [6] for PV technology uses in-plane irradiance (G) reference values of 1000 W/m2, PV cell junction temperature of 25 °C, and air mass of 1.5 value during the quality testing of PV devices.A high-quality, safe, and durable PV module delivers the expected rated power (Wp) that can withstand an extremely wide range of environmental conditions and is reputedly capable of delivering high energy yield over a period of time. The environmental test for both module qualification and reliability testing is set at extreme conditions to accelerate any degradation, especially onthe PV surface.The following are the tests conducted [5][6]: • Thermal Cycling Sequence • Damp-Heat Sequence/Test which is an environmental test intended todetermine the ability of the PV module to withstand the effects of long-term humidity penetration • Ultraviolet Exposure and Thermal Cycling • Hail Test to determine capability of surviving the impact of hailstones • Hot Spot Endurance Test to evaluate capability of surviving hot-spot heating effects
• • • • • •
Humidity-Freeze Sequence to assess capability of withstanding the effect of high temperature and humidity followed by subzero temperature Insulation Test Mechanical Load Test and Outdoor Exposure Salt Mist Test Robustness-of-Termination Test Twist and Wet Leakage Current Test
The MS/IEC standard defines standard operating conditions as the operating values ofin-plane irradiance (1000 W/m2), where the PV device junction temperature equals the nominal operating PV cell junction temperature with an air mass of 1.5.The NOCT based on the MS/IEC standards [7] is defined as the temperature element in a PV module exposed at 45° south to the 800 w/m2 irradiation at 20 °C ambient temperature and wind speed of about 1 ms−1.. The PV module is an electrically opencircuit and openrack mounted at normal incidence and at solar noon clocked at 12 pm midday. Some studies conducted in various locations in Malaysia haverevealed that the ambient temperature values do not suit the STC, which is usually applied and referred to by PV makers. Katsumata et al. [8] studied the gap of the common method in estimating the PV module efficiency in STC, which only considers an incident solar irradiance of 1 kW/m2, a solar spectrum distribution of air mass 1.5, and a module temperature of 25 °C despite the fact that the efficiency varies with the natural hourly change of actual outdoor conditions. Tsai and Tsai in [9] conducted a verification approach using the STC and NOCT condition for their integrated PV, which simultaneously describes the electricity characteristics and thermal dynamics of a commercial PV module. The STC-based references, which describe cell electrical performance, are open-circuit voltage, short-circuit current, rated current and voltage at the maximum power point, temperature coefficients at the opencircuit voltage, and short-circuit current. In this study, it is claimed that the value of the STC in the IEC standards deflects the fluctuating phenomena of transient weather conditions, especially in tropical countries. Therefore, alternative standard testing conditions are presented for the tropical climate. III.
PV MODULE TEMPERATURE PREDICTION FOR A PV SYSTEM IN THE TROPICS
The intermittent supply of energy from a PV system and other forms of direct solar energy applications clearly affect overall energy performance, as studied by Islam etal. [11]. This effect corresponds to the highly dense PV generation in a power distribution grid with slow variations in days and weeks, which further challengesthe maintenance of the energy
balance in the system and is a valuable basis for the necessity of a localized spectral analysis to statisticallyevaluate the fluctuation power index. The fluctuation phenomena can be a fast and short irradiance, which leads to instabilities in cases of intermediate power shortages with insufficient back-up capacity. Most PV manufacturers provide temperature elements for their crystalline PV modules based on the NOCT as the cell temperature (Tc) [12],which has a standard equation of
Tc = Ta +
G NOCT − 20 o C 800
(
)
(1)
where Tc is the cell temperature, Ta is the ambient temperature, G is the instant solar radiation, and NOCT is the nominal operation cell temperature. This equation also denotes the module temperature (Tm) with 1 m/s wind speed, 20 °C ambient temperature, and 800 W/m−2hemispherical irradiance (G) set as the environmental conditions. The location of the measuring temperature element in the PV module remains debatable [13] because of the issue on the effect of the surface temperature (Ts), bottom temperature (Tb), and surrounding temperature (Ta) on the cell temperature (Tc). An in-depth review on the PV module temperature was conducted by Skoplaki and Palyvos [13], where some of the explicit equations for Tc were provided. The thermal energy balance approach, which seeks to define the cell temperature of the PV module,has been extensively used by most researchers [12] [13] [14] [15] [16]. This approach defines the sum of all energy flows that enters (radiation source) and exits (convection heat plus radiation loss) the PV module that is equal to zero. The importance of the standard heat transfer mechanisms has been emphasized by these authors and must be taken into account when calculating the cell temperature. The concept easily creates a differential equation and a mathematical hypothesis that governs the PV module temperature. The modeling of the PV cell temperature has been previously extensively studied and described. However, a new concept of the tropical field elements isproposed in this study, with the maximum radiation (G) as the key reference that is supported by Tc modeling, which deals with surface temperature (Ts) as one of the main factors that influences PV performance. Mattei et al. [12] proved via a field test arrangement that the temperature is uniform in the PV panel. Huang et al. [17] presented a simple non-destructive method in measuring the solar cell junction temperature using correlation analysis of the measured irradiance and opencircuit voltage. The experiments highlighted the surface
temperature measurement to be considered in defining the junction or cell temperature. IV.
RESULTS AND DISCUSSION
In Universiti Kebangsaan Malaysia, there is a 5 kWp grid-tied PV system equipped with a GPRS-monitoring system and athree-parameter weather station. Graphical LabVIEW software and cRIO housing were used as data acquisition and real-time monitoring systems. These systems enable thecapture of environmental measurement from multiple sources and the visual analysis of data in both real-time and synchronized modes, which are crucial forrapidly fluctuating data flow. This PV system is equipped with threetemperature sensors, a solar radiation sensor, and a wind speed sensor. The threetemperature sensors measure the ambient, PV cell face, and PV cell bottom temperatures. Data for 10 months (September 2011 to June 2012) were recorded. These records were taken for every5 mins given the uncertain nature of the recorded data. In this research, a new terminology of tFOCT is defined as the mean value of the equilibrium cell temperature calculated from the average maximum monthly standard climatic parametersmeasured in the tropical field conditions. This definition reveals that the best weather conditions for measuring the NOCT can be found using the average maximum solar radiation, average value of the ambient temperature at the maximum solar radiation, and average value of the wind speed at the maximum solar radiation value. Table 1 shows samples of the monthly maximum values of solar radiation, ambient temperature, and wind speed for monthly data recorded duringthe monitoring period of 10 months. Table 1.Monthly maximum values of solar radiation, ambient temperature and wind speed Month
Rad. (W/m2) 926.675
Amb. Temp. (°C) 33.36
W. Speed (m/s) 1.66
887.32
32.81
1.66
Nov. 2011
989.33
32.39
1.33
Jan. 2012
1118
33.02
1.56
Feb.2012
1016.86
33.25
1.67
Mar. 2012
825.48
32.35
1.44
Apr. 2012
1035.23
33.76
1.48
Jun. 2012
834.54
34.08
1.67
Avg.
954.179
33.128
1.559
Sept. 2011 Oct. 2011
Given the previous assumption that the NOCT or tFOCT for a system installed in Malaysia or a nearby country must be calculated at 954 W/m2 solar radiation, 33 °C ambient temperature, and 1.6 m/s wind speed, Equation 1 for the cell temperature can be redefined as follows:
G (t ) Tc (t ) = Ta (t ) + tFOCT − 33o C 954
(
)
(2)
The tFOCT can be found at954 W/m2 solar radiation, 33 °C ambient temperature, and 1.5 m/s wind speed based on Equation 3. In this study, two cell temperature sensors were used to measure the cell surface cell temperature, and the cell bottom temperature. Figure 1 shows the 703 samples of a specific day for the ambient temperature (Ta), surface solar cell temperature (FFs), and bottom solar cell temperature (FFb) for the installed system.The figure clearly shows that the temperature of the solar cell bottom is higher than that of the solar cell surface. The tFOCT of the solar cell can be estimated in two ways: based on the FFs and the FFb. Therefore, the tFOCT is calculated twice using both values, which are presented as the two estimated values of the solar cell temperature. Table 2 shows the FFs and FFb values of the eight samples at the recommended weather condition used to calculate the tFOCT, at the 954 W/m2 solar radiation, 33 °C ambient temperature, and 1.5 m/s wind speed. The data in Table 2 are taken with an error ± 5%.
Temperature (C)
50 45 40 35
FFs
30
FFb
25
Table 2. FFs and FFb at the recommended weather condition for calculating the tFOCT Sample 1 2 3 4 5 6 7 8 Avg.
Solar radiation 920 913 915 932 939 965 917 922 928
Ambient temperature 35.4 34.7 35.2 35.8 34 32.3 34.2 34.5 34.5
Wind speed 0 2.6 2.2 1.4 1.2 2.2 1.7 0.3 1.45
FFs
FFb
54.4 43.7 51.2 48.8 42.8 32.8 34.1 33.7 42.7
57.4 47.8 57.7 54.4 46.7 33.3 35 34.5 45.9
⎧Tc (t ) = Ta (t ) + 0.0102G (t ) → FFs ⎫ ⎨ ⎬ (3) ⎩Tc (t ) = Ta (t ) + 0.0135G (t ) → FFb ⎭ The first part of Equation 3 shows the relation between the cell temperature and solar radiation and the ambient temperature using the surface cell temperature to calculate the tFOCT. The second part shows the same relation but uses the bottom solar celltemperature to calculate the tFOCT. The cell temperature for a specific day is calculated using the models proposed in Equation 3 and the standard equation presented in Equation 1 to validate the proposed cell temperature models. The NOCT value used in Equation 1 is 47 °C based on the used PV module datasheet. The cell temperatures calculated using Equation 3 are the solar temperature based on FFs (Tcs) and the solar temperature based on FFb (Tcb). The cell temperature calculated using the standard Equation 1 is Tcr. Figure 2 shows the cell temperature results for temperatures Tcs, Tcb and Tcr as well FFs and FFb.
Ta 1 61 121 181 241 301 361 421 481 541 601 661
20 Time
Figure 1. Samples for the ambient temperature, surface cell temperature (FFs), and bottom cell temperature (FFb) Two values of tFOCT, namely, FFs and FFb, can be derived from Table 2. The tFOCT based onFFs is 42.7 ± 5%, whereas the tFOCT based on FFb is 45.9 ± 5%. Thus, two correlation equations can be drawn for the cell temperature given in Equation 3 as follows:
Figure 2. Testing results of the proposed models for the calculation of the solar cell temperature
The figure reveals that the solar cell temperature values calculated based on the proposed model presented in Equation 3 are more accurate than the results of the standard model shown in Equation 1. The values of the solar cell temperature based on the FFs (Tcs) and based on FFb (Tcb) are closer to the actualvalues of the FFs and FFb than the values of the solar cell temperature based on the standard equation (Tcr). The average absolute error (AE) between the actual FFs and the predicted FFs values (Tcs) is12.86%. The AE between the FFb (actual values) and Tcb (predicted values) is 14.52%. However, the AE values between the Tcr values and the FFs and FFb values are 18.3% and 15.7%, respectively. Therefore, the proposed model is more accurate in calculating the cell temperature than the standard model presented in Equation 1. V. CONCLUSION A new terminology for tFOCT is introduced and is defined as the mean value of the equilibrium cell temperature applicable for tropical field conditions and calculated using the averagemaximum monthly standard climatic parameters. Given the 10-month yield of the PV pilot plant, the average monthly readings are obtained based on the maximum radiationof 954 W/m2 irradiance, 33 °C ambient temperature, and 1.5 m/s wind speedfor an electricallycharged and openrack system application. The proposed cell temperature model is more accurate than the standard model in calculating solar cell temperature. The outcome of this work can be applied for determining optimal sizing of a PV system installed in Malaysia and in nearby regions. REFERENCES [1] S.M. Shafie, T.M.I. Mahlia, H.H. Masjuki, A. Andriyana. “Current energy usage and sustainable energy in Malaysia”. Renewable and Sustainable Energy Reviews. vol. 15. pp. 4370-4377. 2011. http://www.sciencedirect.com/science/article/pii/S136403211100360. [2] T. Khatib, A, Mohamed, M. Mahmoud, K. Sopian. “Modeling of daily solar energy on a horizontal surface for five main sites in Malaysia”. J. of Green Energy. vol. 8. pp.795-819.2011. http://www.tandfonline.com/doi/full/10.1080/15435075.2011.602156#.UoyfT 8RQGao. [3] PiyatidaTrinuruk, ChumnongSorapipatana, DhirayutChenvidhya. “Estimating operating cell temperature of BIPV modules in Thailand”. Renewable Energy. vol. 34. pp. 2515-2523. 2009. http://www.sciencedirect.com/science/article/pii/S0960148109000962. [4] T. Khatib, A.Mohamed, K. Sopian, M. Mahmoud. “A new approach for metrological variables prediction using ANNs: application for sizing and maintain PV systems”. J. of Solar Energy Engineering. vol.134. pp 205217.2012. http://solarenergyengineering.asmedigitalcollection.asme.org/Mobile/article.a spx?articleid=1458834. [5] C. Osterwald Standards, Calibration, and Testing of PV Modules and Solar Cells .National Renewable Energy Laboratory. 2006. http://techno.su.lt/~bielskis/straipsniai%20ir%20knygos/Practical%20Handbo ok%20of%20Photovoltaics%20(Second%20Edition)/Chapter%20III2%20%96%20Standards,%20Calibration,%20and%20Testing%20of%20PV %20Modules%20and%20Solar%20Cells.pdf. [6] Solar Photovoltaic Energy Systems – Terms, Definitions and Symbols. Malaysian Standard MS IEC 61836:2010
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