Spectral Mismatch Factor Research Articles

Analysis of the Performance of mc-Si and CdTe Modules Under Soiling Conditions

In this work, we study the soiling impact on the performance of two PV technologies installed in the south of Spain. For this purpose, we include electrical measurements as well as spectral aspects such as dust transmittance, quantum efficiency and the local solar spectrum to analyse their response. The studied technologies were multicrystalline silicon (mc-Si) and cadmium telluride (CdTe) PV modules. The solar spectra representative for clear sky, clean glass cover and soiled glass as well as the spectral response of the PV modules were used for the calculation of the photogenerated current density and spectral mismatch factor. Two cloudless days were chosen for analysis. In terms of the solar resource, these days did not exhibit large differences. Nevertheless, soiling was present to a different extent. When comparing the corresponding power output of the technologies on day 1 and day 2, the power losses at 12 UTC were 3 times larger for mc-Si and nearly the same for CdTe. This result shows that the soiling impacts differently on PV modules having different spectral responses.

Quantifying spectral albedo effects on bifacial photovoltaic module measurements and system model predictions

AbstractWe provide a comprehensive analysis of the effect of spectral albedo on photovoltaic (PV) module measurements and system model predictions. We demonstrate how to account for albedo in indoor bifacial device measurements by adjusting the applied irradiance using the scaled rear irradiance method, exemplified on fabricated silicon heterojunction (SHJ) modules. System model performance is studied using a detailed 3D finite‐element model, DUET, for fixed‐tilt and horizontal single‐axis tracked (SAT) arrays between 15 and 75°N. Spectral effects cause variations in measured SHJ module short‐circuit current up to 2% and efficiency variation up to 0.3% abs. We further demonstrate that rear‐side spectral mismatch factors (SMMs) resulting from including or omitting spectral albedo in PV system modeling vary between ±13%, while total (front+rear) SMMs vary up to 3%, depending on the deployment configuration and latitude. SAT array SMMs are weakly correlated with latitude, while fixed‐tilt array SMMs increase with latitude, driven by an increasing proportion of ground‐reflected light on the front‐side of modules. Ground‐reflections can constitute between 2% and 32% of total incident module irradiance, with notably high (>10%) contributions for fixed‐tilt arrays at high latitude. Effects of spectral albedo are most significant for: (1) fixed‐tilt deployments at high latitudes, (2) wide bandgap technologies such as perovskite and cadmium telluride cells, (3) albedos which vary steeply over the technology's absorption range, and (4) high albedo ground covers. Overall, we demonstrate that omitting spectral albedo effects can result in PV measurement and system‐level modeling uncertainties on the order of several percent in these cases.

Rational selection of light sources for LED-based solar simulators

Solar simulators replicate the spectrum of sunlight and are essential for the research, development, and quality control of photovoltaic devices. The purpose of this paper is to explore the optimization of solar simulators based on light-emitting diodes (LEDs) and hybrid LED-halogen lamp combinations in a series of simulations, by taking into account newly defined criteria of the IEC 60904-9:2020 standard: new spectral ranges, requirements for the so-called A+ class spectrum, spectral coverage, spectral deviation, and spectral mismatch factors. We reveal new ways to configure LED-based solar simulators with just four light source types to achieve A+ class spectrum. Even with A+ class spectrum significant spectral mismatch effects can remain, but may be reduced by adding or adjusting light sources. We demonstrate optimum combinations of light sources necessary for the reduction of spectral mismatch effects in the cases of crystalline silicon (c-Si) cells or both amorphous silicon (a-Si) and c-Si cells. Simulations of the current–voltage characteristics of an encapsulated aluminum back-surface field (Al-BSF) Si solar cell were performed using Synopsys TCAD (Technology Computer-Aided Design) software to reveal the expected differences of the open-circuit voltages and the short-circuit currents in a real-life operation scenario. The advantages of higher spectral coverage and more precise photogenerated current values are envisaged for hybrid solar simulators with comparable numbers of different light source types. The manufacturability of several proposed simulator designs is demonstrated by a series of proof-of-concept experiments.

Comprehensive Analysis of Spectral Mismatch Factor for Solar Cells Based on In Situ Observation of Aerosol Optical Depth Spectra and Solar Spectral Irradiance in Korea

The spectral mismatch factor for solar cells quantifies their relative performance in converting solar irradiance between the incident and reference solar spectra into electricity. This study attempted to evaluate the spectral mismatch factor for eight types of solar cells and investigate their sensitivity to changes in the solar spectral irradiance, which is dependent on the aerosol optical properties in a clear sky. Copper indium gallium diselenide cells have the highest mean value of the spectral mismatch factor, implying that they are less sensitive to changes in the solar spectral irradiance. In contrast, perovskite and amorphous silicon cells are more sensitive to atmospheric conditions, with broader distributions of the spectral mismatch factor values. Additionally, our study found that heterojunction with intrinsic thin-layer cells has the highest substantial efficiency, considering the nameplate efficiency. The spectral mismatch factor decreased with increasing aerosol optical depth at 500 nm and was proportional to the humidity. The effects of aerosol optical properties on the spectral mismatch factor for different solar cells were clarified using clustering analysis and back-trajectory modeling results. In the present study, the aerosol optical depth spectra were found to be more important in determining the spectral mismatch factor than the aerosol optical depth at 500 nm. This study recommends further research on the relationship between the aerosol optical properties and solar spectral irradiance to better predict or estimate the spectral mismatch factor in solar power forecasting.

Predictability and interrelations of spectral indicators for PV performance in multiple latitudes and climates

When PV is installed in the field, the module technologies are rated according to their output energy yield under local operating conditions rather than at standard test conditions (STC), where the spectrum is set to AM1.5G. Care must be taken as this standard is not optimal for all latitudes and the solar spectral distribution variations are one primary influencing factor on PV performance. In addition, obtaining an accurate estimate of the spectral effects on PV performance, as set out in standard procedures, is hampered by the cost of gathering the inputs and the large amount of spectral data required for such a calculation. In this work, based on measured spectral irradiance data from nine sites of different latitudes and climates, we first show a characteristic trend in the spectral distribution over the year concerning the location latitude. The closer a site is to the equator, the more blue-rich the solar spectrum is and the fewer seasonal spectral variations it will contain. Then, we calculate and correlate the most popular metrics (device-independent and device-dependent) used to describe the influence of solar spectra on PV performance. In particular, the monthly irradiance-weighted Spectral Mismatch Factor for different PV technologies and Average Photon Energy show a global linear correlation for data from these nine sites. We use this global linear relationship to propose PV technology-dependent equations that predict annual and monthly spectral gains/losses within a prediction half-interval of up to ± 1.66% by only inserting the monthly or annual irradiance-weighted Average Photon Energy potentially for any site. Reducing the required spectral data sets for performance estimation through our methodology facilitates a more accessible and less costly communication of databases than complete spectral data sets. Finally, using this spectral data, we demonstrate statistically that the Spectral Mismatch Factor and Integrated Useful Fraction Ratio can be replaced by alternative spectral metrics, which require only averaged spectra and, thus, reduce the computational effort to estimate the above indicators.

Improving Spectral Responsivity Measurements by Correcting for Filter Bandwidth

Spectral responsivity (SR) measurements are key in characterizing photovoltaic (PV) devices and calculating spectral mismatch correction factors (MMF). SR is measured using different wavelengths of monochromatic light. In practical measurement systems, this light has a finite bandwidth, meaning that it is only quasi-monochromatic. The data analysis, however, typically assumes perfectly monochromatic light. The accuracy of the calculated SR then depends not only on the actual bandwidth of the monochromatic light used during the measurement but also on the intensity distribution inside the bandwidth. In our SR measurement system, we use quasi-monochromatic light obtained from a solar simulator and a range of bandpass filters. First, we measured and analyzed the spectral content of light transmitted for each filter. Then, we developed an iterative correction scheme for the measured SR. This numerical approach assumes no previous knowledge about the SR of the device under test (DUT). Applying this scheme for bandwidth correction to a range of PV cells with varying SR curves, we found that the corrections for most wavelengths are of minor importance. However, for those wavelengths where the shape of the SR curve of the reference device and DUT differ notably, the corrections are significant up to 20% and higher. We investigated the change in the spectral MMF, which was found to be negligible in most cases but not always. Therefore, the bandwidth correction is mainly important not only for improving SR measurements of PV devices but also relevant for the determination of spectral mismatch factors.

Validation of Photovoltaic Spectral Effects Derived From Satellite-Based Solar Irradiance Products

The Satellite Application Facility on Climate Monitoring (CM-SAF) Spectral Resolved Irradiance (SRI) and National Renewable Energy Laboratory National Solar Radiation Database Spectral on Demand (NSRDB-S) satellite-based spectral irradiance products are tested here against benchmark data and models at seven ground stations: one in Spain for CM-SAF SRI and six in North America for NSRDB-S. Benchmarks include WISER spectroradiometers, spectra modeled from SolarSIM-G measurements, the First Solar model of spectral mismatch factor (SMM), and the SMARTS radiative code with two alternate input sources: AErosol RObotic NETwork (AERONET) and the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) reanalysis. The satellite products are tested in terms of their ability to estimate photovoltaic (PV) spectral effects for six PV module technologies. Spectra are also compared directly. CM-SAF SRI generally outperforms First Solar and “no spectral effects” benchmarks, except for cadmium telluride modules. For NSRDB-S, predictions of long-term spectral derate factors show less skill than for instantaneous SMMs. Spectra comparisons reveal systematic differences between NSRDB-S and benchmark spectra, likely due to the NSRDB-S treatment of aerosols. Meanwhile, the mean SMARTS spectra with AERONET and MERRA-2 inputs are in good agreement, showing promise for the use of MERRA-2 as input to clear-sky models.

Towards a standard approach for annual energy production of concentrator-based building-integrated photovoltaics

A form of building-integrated photovoltaics, luminescent solar concentrators are devices used to enhance solar cell output per unit area through red-shifted, concentrated internal reflection of sunlight. Luminescent solar concentrators have shown promise, but they have yet to achieve commercial success. At present, it is prohibitively difficult for architects and solar engineers to assess their annual energy production and subsequently conceptualize their economic potential. To bridge this gap, this paper provides an approach for annual performance evaluation of luminescent solar concentrators that parallels conventional processes used internationally for existing photovoltaic projects and solar development proposals. The approach starts by following conventional processes to evaluate the plane-of-array irradiance. Then, two metrics are introduced to evaluate the effective irradiance incident on solar cells within an LSC: 1) LSC optical efficiency is employed to determine the proportion of light reaching solar cells relative to the exposed surface; 2) LSC spectral mismatch factor is defined to represent the impact of spectral differences due to absorption and luminescent emission within an LSC. These metrics have never been employed in such a context before. With their addition, the process to produce LSC energy estimates becomes analogous to the conventional process to produce estimates for solar panels. The proposed approach is first validated against the commercial software, PVsyst. Then, case studies in Albany, NY and Phoenix, AZ are conducted to present energy estimates (at the maximum power point) for solar panels, and both planar and wedge-shaped luminescent solar concentrators when mounted vertically on a southern facing surface.

Improving the Irradiance Data Measured by Silicon-Based Sensors

Silicon-based sensors are widely used for monitoring solar irradiance, in particular, in the field of Photovoltaic (PV) applications. We present a method to correct the global horizontal irradiance measured by silicon-based sensors that reduces the difference to the standard thermopile sensor measurements. A major motivation to use silicon-based sensors for the measurements of irradiance is their lower cost. In addition, their response time is much lower, and their spectral response is much closer to that of the PV systems. The analysis of the differences is based on evaluating four parameters that influence the sensor measurements, namely the temperature, cosine error, spectral mismatch, and calibration factor. Based on the analysis, a correction model is applied to the silicon sensors measurements. The model separates measurements under a clear sky and cloudy sky by combining the clearness index and the solar zenith angle. By applying the correction model on the measurements of the silicon-based sensor, the differences between sensor readings have been reduced significantly. The relative root mean squared difference (rRMSD) between the daily solar irradiation measured by both sensors decreased from 10.6% to 5.4% after applying the correction model, while relative mean absolute difference (rMAD) decreased from 7.4% to 2.5%. The difference in total annual irradiation decreased from 70 KWh/m2 (6.5%) to 15 kWh/m2 (1.5%) by the correction. The presented correction method shows promising results for a further improvement in the accuracy of silicon-based sensors.

Spectral effects on the energy yield of various photovoltaic technologies in Lima (Peru)

This study presents for the first time the spectral impact on the performance of different photovoltaic (PV) technologies in Lima, Peru. We experimentally monitored the spectral distributions over one year (March 2019–February 2020). The average photon energy (APE) is calculated as a representative parameter to evaluate the spectral distributions. The spectral mismatch factor (MM) enables an estimation of the spectral gains of distinct PV technologies: amorphous silicon (a-Si), perovskite, cadmium telluride (CdTe), multicrystalline silicon (multi-Si), monocrystalline silicon (mono-Si) and copper indium gallium selenide with two distinct band-gaps (CIGS-1 and CIGS-2).We found that the annual APE has a value of 1.923 eV, indicating that the spectrum is shifted to shorter wavelengths. In contrast to studies performed in other locations, the spectral distribution shows relatively small monthly APE value variations. This nearly negligible seasonality could be attributed to the low latitude and the particular climate in Lima. Larger-bandgap PV technologies, such as a-Si, perovskite, and CdTe, resulted in annual spectral gains of +6.8%, +4.8%, and +2.1%, respectively. Lower-bandgap PV technologies (CIGS-2, multi-Si, CIGS-1, and mono-Si), present small annual spectral gains of −0.9%, −1.4%, −1.6% and −2.3%, respectively. Also, a quasi-linear correlation between APE and MM was found for all PV technologies.

Spectral mismatch and its effect on artificial solar light source under standard test conditions

Under standard test conditions, the spectral irradiance of artificial solar light sources and the spectral response of photovoltaic devices are important factors that affect the accuracy of device test results. This paper takes the standard solar spectrum AM1.5 as a reference, and calculates the difference between the four commonly used artificial solar light sources (Arc Lamp, Q-Flash, Q-Flash w and ELH) and the standard solar spectrum AM1.5 from the perspective of spectral mismatch. The spectral mismatch factor and the output parameters of the amorphous silicon cell under the irradiation of these light sources. Calculations show that the spectral mismatch factor of Arc Lamp is only 1.005, which matches the standard solar spectrum AM1.5 best. Due to the effect of spectral mismatch, the output parameters of amorphous silicon cells will change significantly after different artificial light sources irradiate them.

Spectral impact on PV in low-latitude sites: The case of southeastern Brazil

The spectral impact on various PV materials –amorphous silicon (a-Si), CdTe, CIGS, single crystalline silicon (sc-Si) and multi crystalline (mc-Si)– in two nearby cities of Southeastern Brazil is presented. For every PV technology studied, the values of the spectral mismatch factor on instantaneous, monthly and annual basis were computed by means of spectra recorded over a 12-month experimental campaign carried out in São Paulo and São José dos Campos. A blue-biased however seasonal spectrum prevails in both cities, which leads to annual spectral gains of up to around 6% and 2% exhibited by a-Si and CdTe, respectively. On the other hand, CIGS, sc-Si and mc-Si show negligible annual gains that lie between around −1% and 0%. These results are well aligned with previous findings obtained using both experimental and modelled spectra in other low-latitude sites with tropical climate. Consequently, spectral effects cannot be ignored in such sites, especially when modelling the outdoor behavior of larger bandgap PV devices. Last, a quasi-linear relationship exists between the monthly average photon energy and the monthly spectral mismatch factor for all the PV materials under scrutiny. This conclusion is in good agreement with previous works carried out in mid-latitude sites.

Measurement Uncertainties in I–V Calibration of Multi-junction Solar Cells for Different Solar Simulators and Reference Devices

Different types of dual-junction solar cells (perovskite/silicon and GaInP/(Al)GaAs) are used in an investigation of measurement uncertainty for electrical characterization of multi-junction solar cells. A method traceable to international reference standards is presented. The spectral mismatch factor matrix is introduced and used with a Monte-Carlo method including manifold correlated and uncorrelated uncertainties. In this way, a detailed analysis of the solar simulator's spectral irradiance and its influence on uncertainty becomes possible. The use of subcell-adapted and broadband reference solar cells is addressed regarding their impact on uncertainty. This allows for finding optimal conditions for calibration with lowest measurement uncertainty. The short-circuit current of a series connected multi-junction solar cell is affected by luminescence coupling and other effects. With an experimental method it is shown how the uncertainty of the device short-circuit current can be precisely determined. The spectrometric characterization method allows deriving uncertainties of all I–V parameters. In this way a complete evaluation of measurement uncertainty for the calibration of multi-junction solar cells at standard testing conditions is introduced. This article is an extension to our work presented at the 46th IEEE PVSC. Here, we have added a detailed analysis of the influence of different solar simulator spectral irradiance distributions on measurement uncertainty by evaluating a Monte Carlo simulation introducing correlation coefficients. In addition for the first time, it is shown how luminescent coupling influences the calibration of multi-junction solar cells and how the effect needs to be implemented into the uncertainty of measurement for the short-circuit current as well as efficiency.

Spectral Response Measurements of Perovskite Solar Cells

A new spectral response (SR) measurement routine is proposed that is universally applicable for all perovskite devices. It is aimed at improving measurement accuracy and repeatability of SR curves and current–voltage curve spectral mismatch factor (MMF) corrections. Frequency response, effects of preconditioning as well as dependency on incident light intensity and voltage load on SR measurements are characterized on two differently structured perovskite device types. It is shown that device preconditioning affects the SR shape, causing errors in spectral MMF corrections of up to 0.8% when using a reference cell with a good spectral match and a class A solar simulator. Wavelength dependent response to incident light intensity and voltage load is observed on both device types, which highlights the need to measure at short-circuit current and maximum power point to correct spectral mismatch. The method with recommendations given ensures that the correct measurement conditions are applied and measurements are corrected for instability in performance.

Accuracy of Simplifications for Spectral Responsivity Measurements of Solar Cells

The determination of the spectral responsivity is an essential part of solar cell characterization. Since solar simulators only approximate the reference spectrum, a spectral mismatch correction has to be performed. This correction procedure requires spectral responsivity data. Apart from the complete differential spectral responsivity procedure, the IEC 60904-8 standard defines four simplifications. In this paper, we provide information on the variations in the spectral responsivity curves for these simplifications. We show that for nonlinear front junction cells, deviations predominantly occur at wavelengths above 700 nm and become largest around 1000 nm. While we found a maximum deviation of 30% for the simplification with lowest requirements in bias irradiance, all other simplifications yield deviations below 10%. For a nonlinear cell measured relative to a world photovoltaic scale reference cell using a class A solar simulator, this transfers to a deviation below 0.01% in the spectral mismatch factor. If one depends on the use of a simplification, we recommend using the multicolor approach. Even though the singlecolor approach might yield lower deviations, this approach requires knowledge about the maximum in the spectral responsivity, which is not generally known in advance of the measurement. Accepting a slightly higher deviation, the white bias approach is a recommendable alternative.

Spectral Corrections Based on Air Mass, Aerosol Optical Depth, and Precipitable Water for PV Performance Modeling

Broadband incident global irradiance must be corrected when modeling the performance of a photovoltaic (PV) module to account for the impact of spectrum. However, most existing correction methods exhibit both climate and site dependencies. This paper presents a new set of analytical equations aimed at modeling the spectral effects exhibited by six PV single-junction materials under all operating conditions. Thus, the equations proposed here involve the three parameters that mostly influence the spectrum shape: air mass (AM), aerosol optical depth, and precipitable water. The extraction of the equations and their coefficients is then presented. Next, the method is empirically validated over the course of a 12-mo experimental campaign. Thus, coefficients of determination ranging from 0.87 (multicrystalline silicon) to 0.92 (amorphous silicon) prove that modeled values of the spectral mismatch factor (MM) are well aligned with experimental ones. In addition to the values of mean bias error that are virtually equal to zero, this new procedure also yields values of root mean square error that stay below 0.85% when modeling MM for all the technologies under investigation. Such figures are far better than those achieved by using the popular Sandia Labs method, based solely on AM.

Spectral impact on PV performance in mid-latitude sunny inland sites: Experimental vs. modelled results

Abstract The influence of spectral irradiance on the performance of different PV materials—amorphous silicon, CdTe, CIS, and monocrystalline silicon—is studied in two cities assumed representative of mid-latitude inland sunny sites not affected by extreme atmospheric characteristics. Experimental and modelled spectral mismatch factors at different timescales—instantaneous, monthly, and annual—were derived from a) outdoor spectra recorded over a 24-month experimental campaign conducted in Madrid and Jaen (Spain) and b) synthetic spectra computed using SMARTS and input atmospheric data from AERONET. The experimental annual spectral gains presented here lie within ±1% for all PV materials under scrutiny in both sites, in close agreement with modelled results. In practical terms, this may lead to simpler PV modelling approaches by neglecting spectral effects on an annual basis in sites with spectral characteristics similar to Madrid's and Jaen's. Modelled spectral impacts on PV performance previously reported for these two cities are qualitatively well aligned with our findings. Interestingly, absolute differences between the results regarding the annual spectral influence on monocrystalline silicon and CdTe in both sites obtained by means of a model based on satellite-based spectrally resolved irradiance data and the experimental results for these materials presented here stay below 0.3%.

Spectral mismatch and solar simulator quality factor in advanced LED solar simulators

Solar cell simulators based on light emitting diodes (LED) have the potential to achieve a large potential market share in the next years. As advantages they can provide a short and long time stable spectrum, which fits very well to the global AM1.5g reference spectrum. This guarantees correct measurements during the flashes and throughout the light engines’ life span, respectively. Furthermore, a calibration with a solar cell type of different spectral response (SR) as well as the production of solar cells with varying SR in between two calibrations does not affect the correctness of the measurement result. A high quality 21 channel LED solar cell spectrum is compared to former study comprising a standard modified xenon spectrum light source. It is shown, that the spectrum of the 21-channel-LED light source performs best for all examined cases.

Effect of seasonal spectral variations on performance of three different photovoltaic technologies in India

The accuracy of outdoor performance of a photovoltaic (PV) array can be improved by considering the spectral effects. In this paper, the impact of seasonal spectral variations on the three different silicon PV tech- nologies: single junction amorphous silicon (a-Si), Hetero- junction with Intrinsic Thin-layer (HIT) and multi crys- talline silicon (mc-Si) has been presented first time in Indian environmental conditions. The spectral effect on HIT PV module technology has been presented first time along with the first simultaneous study of variation in spectral indicators by useful fraction (UF), average photon energy (APE) and spectral mismatch factor (MMF), based on monthly and seasonal data. The maximum observed variation in UF was 26.4, 8.2, 10.8 %, while in MMF, variation was up to 24.7, 7.6, 8.2 % for a-Si, HIT and mc- Si, respectively, and in APE variation was up to 15.3 %. Among all three technology modules, first time reported HIT technology showed the least variation while maximum variation was observed in a-Si technology. The observed spectral effect variations have been discussed on Perfor- mance Ratio and compared with reported results of other global sites. The value and trends of spectral parameters are important to understand the effect of spectral variation on different technology. This study is especially important in Indian subcontinent perspective because of the strong monsoon season, where observed variation in the spectrum-related parameter found to be highest among all the seasons.

On the uncertainty of energetic impact on the yield of different PV technologies due to varying spectral irradiance

Varying spectral irradiance affects performance of photovoltaic (PV) modules depending on their band gap and spectral response. Therefore, energy rating or yield prediction procedures should take into account the irradiance that is effectively available for a specific PV technology. This effective irradiance differs from broadband solar resource information first due to the different spectral sensitivity of PV devices and pyranometers, and second due to the difference between real and reference spectral distribution. The combined difference, also referred to as ‘spectral impact’, is to date considered in form of fixed spectral gain or loss factors applied to the broadband solar resource – if it is considered at all. Values for the monthly or annual spectral impact have been reported for several locations; however without estimates of their uncertainty. This article addresses the question of how large the uncertainty of the spectral impact is. Contributions to the uncertainty of the spectral impact are discussed, with focus on the method of determining the spectral impact by means of measured spectral irradiance and calculated spectral mismatch factor (MM). Using a simplified procedure, the uncertainty of spectral impact was estimated from the average spectral mismatch uncertainty. It was found to be of the same magnitude as the spectral impact itself, and dependent on the PV technology. For five single-junction PV technologies, amorphous silicon, cadmium telluride, standard crystalline silicon, high-efficiency crystalline silicon and a wide-band-gap CIGS technology, the estimated uncertainty values were 1.8%, 1.4%, 0.9%, 1.0% and 1.2%, respectively. The results were obtained from a specific measurement campaign conducted from 01.06.2010 to 31.12.2013 in Freiburg im Breisgau, Germany, but the order of magnitude is considered to be typical. In order to validate the simplified uncertainty estimation method, a sensitivity analysis was carried out to evaluate the influences of calibration and drift of the spectroradiometer, high-angle-of-incidence conditions, the available wavelength range of the spectroradiometer and results obtained with different spectroradiometers. With the smaller wavelength range of 350–1050nm, which is a typical range for various instruments used in many scientific publications, the calculated spectral impact was significantly smaller. The other influences were found to affect the result only within the estimated uncertainty limits. The uncertainty values presented here should be considered lower limits until they are backed up by further analysis.