Energy rating is gaining importance in the
photovoltaic (PV) community as it, unless
power rating at standard conditions, allows an
accurate estimation of the performance of PV
modules in different climatic conditions. The
device characterisation currently requires the
measurement of a performance matrix using
irradiance and temperature where values
between measurements might be interpolated.
Spectral changes are included by correcting
using a quantum efficiency measurement. I-V
translations of PV modules give better idea
about the measurements of the PV modules as
a function of irradiance and temperature. Two
methods of I-V translations are applied in this
study. Bilinear interpolation between the
consecutive points of three selective data sets
of irradiance and temperature in the power
matrix reduces the prediction error below 2.5%
compared to over 6% with linear interpolation
between two extreme data set points in the
power matrix

Jyotirmoy Roy (1257567)

Martin Bliss (1250019)

Ralph Gottschalg (1247661)

Tom Betts (1258395)

English

Loughborough University Institutional Repository

   This item was submitted to Loughborough’s Institutional Repository (https://dspace.lboro.ac.uk/) by the author and is made available under the following Creative Commons Licence conditions.      For the full text of this licence, please go to: http://creativecommons.org/licenses/by-nc-nd/2.5/  EFFECT OF I-V TRANSLATIONS OF IRRADIANCE-TEMPERATURE ON THE ENERGY YIELD PREDICTION OF PV MODULE AND SPECTRAL CHANGES OVER IRRADIANCE AND TEMPERATURE  J. Roy*, M. Bliss, T.R. Betts, R. Gottschalg Centre for Renewable Energy Systems Technology (CREST), Department of Electronic and Electrical Engineering, Loughborough University, Loughborough, LE11 3TU, UK Tel.: +44 1509 635311, Fax: +44 1509 635301, Email: J.Roy2@lboro.ac.uk *Corresponding author   Abstract      Energy rating is gaining importance in the photovoltaic (PV) community as it, unless power rating at standard conditions, allows an accurate estimation of the performance of PV modules in different climatic conditions. The device characterisation currently requires the measurement of a performance matrix using irradiance and temperature where values between measurements might be interpolated. Spectral changes are included by correcting using a quantum efficiency measurement. I-V translations of PV modules give better idea about the measurements of the PV modules as a function of irradiance and temperature. Two methods of I-V translations are applied in this study. Bilinear interpolation between the consecutive points of three selective data sets of irradiance and temperature in the power matrix reduces the prediction error below 2.5% compared to over 6% with linear interpolation between two extreme data set points in the power matrix.   Introduction      Photovoltaic modules are typically being sold on the basis of £/Wp, which is determined at Standard Testing Conditions (STC). However, the return of investments or user interest is better expressed in terms of £/kWh generation. This means that there is a mismatch between the initial investment and its returns. This mismatch in expectations can be overcome by given the user the opportunity to judge modules on expected energy yield. There are few energy yield prediction models available developed by different research groups across the Europe, but yet there is no standard available commercially. Development of a standard based on energy rating of PV module is underway proposed by IEC [1], which involves a standardised energy yield prediction for a standard operating environment using a standard method of calculation. Accuracy of energy yield prediction is the most important factor on the robustness of an energy rating method. Specific PV module measurement data and site specific environmental data are two common requirements as an input into the energy prediction modelling of any PV module.  Understanding of the behaviour of PV device performance over the range of irradiance, temperature and spectrum is very important in order to achieve an accurate energy yield prediction method. This can be assured by means of an uncertainty analysis of the modelling to estimate the power output of PV modules. Modelling uncertainty analysis allows better understanding of the behaviour of PV module output at their certain range, which allows deciding the appropriate modelling approach for energy yield prediction. Employing bilinear interpolation, linear interpolation between to consecutive points, can lead to better accuracy in prediction of the output of PV modules. This helps to decide the required number of measurement points for each parameter to characterise the module with better accuracy. Minimisation of number of measurement points in the performance matrix can minimise the cost of testing of PV modules. Uncertainty analysis of the energy rating methodology can significantly helps financial evaluation of PV systems.           A previous study [2] demonstrated the uncertainty of the modelling issues for IEC energy rating method using linear interpolation. In this study a comparison between linear and bilinear interpolation is employed for I-V translation to estimate the deviation between two approaches in the output of the PV module in terms of maximum power, which ultimately explain the appropriate method to use for better accuracy in the energy yield prediction.  The methodologies for I-V translations used are based on the IEC 60891 standard [3].           Spectral effects on the efficiency of the c-Si PV device over the irradiance and temperature are also analysed. Effect of spectral contribution in the energy generation of PV modules in outdoor condition at different spectrum is under development.        I-V Translation Methodologies      Characterisation of PV module is one of the input required data into the energy yield prediction model are explained above along with environmental characterisation data. In order to achieve input module characterisation data, a c-Si PV module is characterised indoors under variable irradiance, temperature and spectrum using a in-house developed LED-based solar simulator [4]. Deviations of actual measured Pmax and estimated Pmax of different approaches of I-V translations in compared. These modelling approaches ultimately declare the possibilities of the scale of modelling uncertainty in the energy yield prediction of PV modules. Marion et al [5], explains an indoor characterisation method to determine a PV module’s temperature and irradiance correction factors in order to translate a reference curve to outdoor conditions of PV module temperature and irradiance for energy yield calculation based on translation equations of ASTM E 1036–96.           Anderson et al [6] demonstrated a new approached of I-V translation using dimensionless (relative) values of temperature coefficients for current and voltage.  Procedure 2 of IEC 60891 (working draft) is employed for irradiance and temperature corrections based on single I-V measurement. In this paper IEC methods is been analysed and also a linear interpolation is applied using different datasets within the performance matrix as a function of irradiance and temperature for better accuracy over the wide range of irradiance and temperature generally a PV module can see in real operation.   I-V Translations     The measured current-voltage characteristics are translated to the other targeted irradiance and temperature conditions by using equations (1) and (2).     111 *))(*1(* GGTTII TTrelT −+= α   (1) )(**ln*)(** 11111 TTIkGGaTTVVV TTTTrelocT −−+−+= β   (2) Where (I1, V1) are coordinates and Voc1 is the open circuit voltage at measured irradiance G1 and temperature T1. (IT, VT) are targeted coordinates at target irradiance GT and target temperature TT. α and β are the relative current and voltage temperature coefficients at G1. ‘a’ is the irradiance correction factor for open circuit voltage with a typical value of 0.06 [3]. “k” is the curve correction factor of the test sample.     Temperature coefficients for current and voltage are estimated from measured I-V curves at AM1.5 spectrum and irradiance at 765 W/m2 and temperature in the range of 15-55 oC. To calculate curve corrector factor (k), I-V characteristics at lowest temperature and at constant irradiance are used. All other I-V curves at different temperatures within the range of interest and at higher irradiances are translated to the I-V curve at temperature of 150C using equations (1) and (2) and also using the values of RS and temperature coefficients as described in Figure 1.    Figure 1: Flow diagram to estimate curve correction factor (k).   Maximum Power Interpolation     Linear interpolation is applied using equations (3) and (4) to estimate the intermediate maximum power (Pmax) of the c-Si PV module of the power matrix as a function of irradiance and temperature at AM1.5 spectrum.   ( )121 * PPaPPT −+=  (3)  ( )( )121GGGGa T−−=  OR ( )( )121TTTTa T−−=   (4)  Where PT is the maximum power of the I-V curve at targeted irradiance and temperature (GT,TT). P1 and P2 are the measured maximum power of the I-V curves at irradiance and temperature at (G1,T1) and (G2,T2) respectively.           Pmax is corrected to its intermediate values from the four measured various irradiances and temperatures.    Figure 2: Different sets of data points in the power matrix as a function of irradiance and temperature.          Bilinear interpolation is basically a linear interpolation between different sets of four measured points in the range of interest as shown in Figure 2 where blue squares are the measured points in the matrix. and the deviation of estimated Pmax and measured Pmax are analysed.  Results and Discussion      Using equation (1) and (2) with the measured current-voltage (I-V) characteristics at 765 W/m2 irradiance and 250C temperature, all other I-V curves are translated at different irradiance and temperature within wide range  irradiance and temperature conditions as illustrated in Figure 3. Relative values of the temperature coefficients are used for current and voltage. Estimated and the measured maximum power points of each curve are then compared. Deviations between the estimated Pmax and the actual measured Pmax are shown in the Figure 3.    Figure 3: Deviation of measured and translated Pmax based on procedure 2 of IEC 60891 standard.      For better accuracy at lower intensity levels Tsuno et al [7], demonstrated a linear interpolation/extrapolation between the four measured I-V curves within the range of irradiance and temperature conditions. Similar approach based on equation (3) and (4) in the power matrix is carried out in this study. Linear interpolations between extreme four points in the matrix are used. With this method the deviation between estimated and measured Pmax are reduced to a certain extent compare to the previous method, as shown in Figure 4.   Figure 4: Deviation of measured and interpolated Pmax with four extreme points of irradiance and temperature in the power matrix.        Figure 5: Deviation of measured and interpolated Pmax with two different sets of four points of irradiance and temperature in the power matrix.      But the deviation of Pmax over 6% (Figure 5) by the linear interpolation method can also significantly increase the energy yield prediction uncertainty. To minimise the modelling uncertainty in order to achieve accurate energy yield prediction method, a bilinear interpolation within the range of irradiance and temperature is introduced by selecting different set of data points and using linear interpolation between the consecutive points. By selecting two set of data points (blue squares blocks in Figure 2), deviation of Pmax can minimised below 2.5% as shown in Figure 5 compared to over 6% deviation in Pmax in Figure 4. This deviation implies that power output of c-Si is not linear in the lower irradiance level but it’s linear over the temperature.             Performance matrix of efficiency as a function of spectrum at different Air Mass (AM) and irradiance are analysed. Efficiency matrix at variable AM are normalised at AM 1.5 spectrum. Figure 6 shows that the normalised efficiency increases with air mass for c-Si module.    Figure 6: Spectral dependence of Pmax over the irradiance.   Figure 7: Spectral dependence of efficiency over the temperature.      Another trend also visible in Figure 6 and Figure 7 that the efficiency is increasing over the irradiance at the same spectrum but change in efficiency over the temperature at the same spectrum is not significant.  Conclusions and Future Works      Two different approaches of I-V corrections are studied in this paper. Procedure 1 of the standard IEC 60891 can introduce larger uncertainty in the energy yield prediction of a PV device in the UK where maximum energy yield occurs at lower irradiance level. Power output is linear at higher irradiance levels compared to lower irradiance. A better fitting can be achieved by applying bilinear interpolation of two different set of data points in the power matrix within the range of interest of irradiance and temperature compared to a linear interpolation between the extreme four points in the matrix. Uncertainty of the energy yield prediction model can further be minimised by increasing the number of measured data set points with bilinear interpolation between two consecutive points.         Optimisation of the required number of measurements and identification of the correlation between irradiance, temperature and spectrum based on Average Photon Energy (APE) at each spectrum is the current state of the work for this study in order to achieve higher accuracy in the energy rating of a PV module.  Acknowledgements    This work is supported by the EPSRC under grant number EP/D078431/1.  References   [1] Roy et al, ”Validation of Proposed Photovoltaic Energy Rating standard and sensitivity to environmental parameters” Proceedings of the 23rd European Photovoltaic Solar Energy Conference, Fiera Valencia, Spain, September 2008. [2] Roy et al, “Modelling Uncertainty of Photovoltaic Module Energy Rating” Proceedings of the 5th Photovoltaic Science Application and Technology Conference and Exhibition, Wrexham, UK, April 2009.  [3] IEC 60891 (Working Draft): Procedure for Temperature and Irradiance Corrections to Measured I-V Characteristics of Photovoltaic Devices.  [4] Bliss, M.  et al, Proceedings of the 24th European Photovoltaic Solar Energy Conference, Hamburg, Germany, September 2009.  [5] Marion et al, Progress in Photovoltaics: Research and Applications. 2002; 10:205–214  [6] Anderson et al, Photovoltaic Translation Equations: A New Approach, NREL/TP-411-20279, January 1996  [7] Tsuno et al, Solar Energy Materials & Solar Cells 93 (2009) 1070–1073. 

Effect of I-V translations of irradiance-temperature on the energy yield prediction of PV module and spectral changes over irradiance and temperature

https://repository.lboro.ac.uk/articles/Effect_of_I-V_translations_of_irradiance-temperature_on_the_energy_yield_prediction_of_PV_module_and_spectral_changes_over_irradiance_and_temperature/9553460/files/17185214.pdf

Effect of I-V translations of irradiance-temperature on the energy yield prediction of PV module and spectral changes over irradiance and temperature

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