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Office of Energy Efficiency & Renewable Energy

Operated by the Alliance for Sustainable Energy, LLC

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Laboratory (NREL) at www.nrel.gov/publications.

Contract No. DE-AC36-08GO28308

Technical Report

NREL/TP-5D00-72599

December 2018

Developing a Framework for Reference 

Cell Standards for PV Resource 

Applications

Aron Habte,

1 Manajit Sengupta,1 Yu Xie,1 Mike Dooraghi,1

Ibrahim Reda,

1 Anton Driesse,2 Christian Gueymard,3 

Stefan Wilbert,4 and Frank Vignola5

1 National Renewable Energy Laboratory

2 PV Performance Labs

3 Solar Consulting Services

4 German Aerospace Center (DLR)

5 University of Oregon
NREL is a national laboratory of the U.S. Department of Energy

Office of Energy Efficiency & Renewable Energy

Operated by the Alliance for Sustainable Energy, LLC

This report is available at no cost from the National Renewable Energy

Laboratory (NREL) at www.nrel.gov/publications.

Contract No. DE-AC36-08GO28308

National Renewable Energy Laboratory

15013 Denver West Parkway

Golden, CO 80401

303-275-3000 • www.nrel.gov

Technical Report

NREL/TP-5D00-72599

December 2018

Developing a Framework for Reference 

Cell Standards for PV Resource 

Applications

Aron Habte,

1 Manajit Sengupta,1 Yu Xie,1 Mike Dooraghi,1

Ibrahim Reda,

1 Anton Driesse,2 Christian Gueymard,3 

Stefan Wilbert,4 and Frank Vignola5

1 National Renewable Energy Laboratory

2 PV Performance Labs

3 Solar Consulting Services

4 German Aerospace Center (DLR)

5 University of Oregon

Suggested Citation 

Habte, Aron, Manajit Sengupta, Yu Xie, Mike Dooraghi, Ibrahim Reda, Anton Driesse, 

Christian Gueymard, Stefan Wilbert, and Frank Vignola. 2018. Developing a Framework 

for Reference Cell Standards for PV Resource Applications. Golden, CO: National 

Renewable Energy Laboratory. NREL/TP-5D00-72599.

https://www.nrel.gov/docs/fy19osti/72599.pdf.
NOTICE

This work was authored in part by the National Renewable Energy Laboratory, operated by Alliance for Sustainable 

Energy, LLC, for the U.S. Department of Energy (DOE) under Contract No. DE-AC36-08GO28308. Funding 

provided by U.S. Department of Energy Office of Energy Efficiency and Renewable Energy Solar Energy 

Technologies Office. The views expressed herein do not necessarily represent the views of the DOE or the U.S. 

Government.

This report is available at no cost from the National Renewable 

Energy Laboratory (NREL) at www.nrel.gov/publications.

U.S. Department of Energy (DOE) reports produced after 1991 

and a growing number of pre-1991 documents are available 

free via www.OSTI.gov.

Cover Photos by Dennis Schroeder: (clockwise, left to right) NREL 51934, NREL 45897, NREL 42160, NREL 45891, NREL 48097, 

NREL 46526.

NREL prints on paper that contains recycled content.
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Acknowledgments

We are grateful to the U.S. Department of Energy Solar Energy Technologies Office and its

photovoltaic and systems integration subprograms for supporting this research. Specifically, we 

acknowledge Dr. Tassos Golnas, Dr. Dave Rench-McCauley, Dr. Lenny Tinker, Dr. Rebecca 

Jones-Albertus, and Dr. Charlie Gay for their support and encouragement.
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List of Acronyms

BORCAL

DHI

DNI

GHI

GTI

IEC

ISO

NREL

POA

PV

SI

Broadband Outdoor Radiometer Calibration 

Diffuse horizontal irradiance 

Direct normal irradiance 

Global horizontal irradiance 

Global total irradiance 

International Electrotechnical Commission 

International Organization for Standardization 

National Renewable Energy Laboratory 

Plane of array 

Photovoltaic 

International Systems of Units

WRR World Radiometric Reference 
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Executive Summary

Quantifying and predicting electricity production from photovoltaic (PV) systems is based on 

measured or modeled irradiance data. These solar resource data consist of global horizontal 

irradiance, global tilted irradiance, direct normal irradiance, and diffuse horizontal irradiance,

which are either derived from satellite observations validated against ground-based 

measurements or directly obtained from ground-based measurements. The ground-based 

measurements are made using thermopile or photodiode radiometers. 

For a PV plant, the efficiency of the energy production is verified by comparing measured output 

with the modeled production, which is computed using either modeled or measured irradiance

data. Thus, plant performance assessments typically include the uncertainty of the transposition 

and, in some cases, decomposition of a given irradiance to convert to the appropriate plane-ofarray (POA) irradiance corresponding to the orientation of the PV installation. Additionally, the 

various types of uncertainty in radiometric measurements or the modeled irradiance and the PV 

module specifications influence the model results and thereby further increase the uncertainty. 

An alternative method of assessing the PV system performance has been to use reference cells to 

measure the “PV resource.” When used to calculate PV performance ratios, there are inherent 

systematic differences between radiometers and reference cells, such as spectral, directional, 

temperature, time responses, nonstability, and nonlinearity differences. Reference cells tend to 

mimic the performance and characteristics of a PV module more closely. In this report, a 

framework is proposed to develop standards that will better quantify and characterize the use of 

reference cells for PV resource measurements.

The measurement from an appropriate reference cell in the POA correlates closely with the plant 

performance, reduces the number of modeling steps needed to simulate PV performance, and 

hence reduces the uncertainties of the comparisons. Because technologically matched reference 

cells and PV modules respond similarly to each wavelength of light that composes the incident 

solar radiation, the uncertainty associated with the changing spectral distribution of incident 

radiation during the day and year can be greatly reduced. This will reduce the overall uncertainty 

in estimated PV performance. The same can be said for the angle-of-incidence effects because

the reference cells are deployed in the same POA as the PV module. At that point, the main 

sources of uncertainty are in modeling the temperature effect differences between the reference 

cells and the PV module and accounting for the difference between the short-circuit current 

monitored by the reference cells and max power point current and voltage at which the PV 

module operates. These sources of uncertainty are also associated with typical irradiance 

measurements made by pyranometers and pyrheliometers; however, typical irradiance 

measurements also include uncertainties associated with the spectral mismatch between 

thermopile or photodiode pyranometers and the PV module, which are minimized with the use of 

reference cells. 

To enhance the use of reference cells for resource assessment, we identify the necessary data, 

characteristics, and calibration methodologies of reference cells and how to standardize the use 

of these data and methods. Further, as we develop this framework, the classification of reference 

cells will be essential to provide guidance for selecting PV reference cells appropriate for a 

specific application. As we address the calibration and sources of uncertainties of reference cells, 
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classification schemes and expected limits of performance with respect to certain parameters 

become important.

Moreover, this report discusses possible technical and analytical challenges that might be 

encountered as these methodologies are developed. The development of these methodologies is

also needed for other initiatives, such as the use of reference cell measurements directly in 

performance or economic models. It should be possible to meet various application needs with 

reference cells through the verification, acceptance, and implementation of reference cells for 

resource assessments.
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Table of Contents

1 Overview................................................................................................................................................ 1

2 Developing a Framework for New Reference Cell Standards.......................................................... 2

2.1 Standard Spectra for a Wide Range of Standard Atmospheres..................................................... 3

2.2 Outdoor Process for Reference Cell Calibration and Characterization......................................... 5

2.2.1 Develop Standard Filter for Reference Cells Calibration to PV Resource....................... 1

2.3 Develop Standardized Outdoor Process to Transfer Calibration from Primary Reference Cell to 

Secondary or Field Reference Cells.............................................................................................. 3

2.4 Develop Best Practices for Field Deployment of Reference Cells................................................ 4

2.5 Classification of Reference Cells.................................................................................................. 4

3 Challenges............................................................................................................................................. 6

References................................................................................................................................................... 7
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List of Figures

Figure 1. Flowchart demonstrating essential required standards and their linkage ...................................... 3

Figure 2. Additional spectra GTI (20°) obtained from [12] compared to the IEC standard spectrum for 37° 

tilt angle ................................................................................................................................... 4

Figure 3. Absolute cavity pyrheliometer (left) and shaded diffuse pyranometer (right). Photos by Dennis 

Schroeder, NREL 22510 (left); and Tom Stoffel (right)........................................................... 0

Figure 4. Calibration result for reference cell and associated calibration uncertainty. Illustration by 

Ibrahim Reda, NREL................................................................................................................ 1

Figure 5. Flowchart illustrating the filter-based approach for reference cell calibration.............................. 3
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1 Overview

Historically, solar irradiance measurements for outdoor photovoltaic (PV) performance 

monitoring has been carried out using either pyranometers, reference cells, or sometimes both.

The results obtained with these options are not directly comparable, resulting in frequent 

discussions about which option is preferred [1], [2]. The PV community is increasingly 

interested in using reference cells that accurately quantify the solar resource available to a PV 

system for outdoor solar resource measurement and characterizing PV performance. The specific 

energy in the plane of array (POA) contained within the spectral range that a PV-based 

technology is sensitive to is referred to as the “PV resource.” Fortunately, reference cells are 

readily available, but the methodologies and standards for how to use these sensors for outdoor 

applications are not well established. Therefore, current calibration and characterization 

approaches for these devices are applicable only for the spectral irradiance distribution under 

which they were configured. Because the incident spectral distribution changes with changes in

atmospheric conditions, solar zenith angle, or PV geometry, the development of dynamic 

calibration methods is needed to characterize the sources of uncertainties of reference cells,

similar to what is done with thermopile instruments. Alternatively, a different approach might

also be considered. Because solar panel nameplate ratings and efficiencies are defined relative to 

a specific reference spectrum, the methodology used for the calibration of matching reference 

cells could match the methodology for defining the specifications of the solar panels. This is 

expected to provide increased relative accuracy when estimating PV module performance. 

Further, it is essential to outline and standardize the outdoor deployment procedures, 

maintenance requirements, verification procedures, and calibration frequencies to use of 

reference cells. Similarly, the International Electrotechnical Commission (IEC) Technical 

Committee 82 Working Group 2 has a series of standards (e.g., IEC 61853-1 to IEC 61853-4; see

[3]–[6]) that can assist in estimating the actual energy production from field-deployed PV 

modules under various temperature, tilt, irradiance, and solar spectral distributions. Thus, the 

characterization challenges for PV reference cells and modules are similar, and the ultimate 

objectives are the same: achieving better prediction of energy production. 

We intend to use these existing standards in the development of the framework and later during 

the development of the needed standards. Moreover, this project’s framework includes the 

development of a classification of PV reference cells based on their specifications to provide 

guidance to the PV community so that the most appropriate reference cell can be selected to suit 

the users’ applications.

The National Renewable Energy Laboratory (NREL) has long-standing leadership roles and 

involvements with ASTM, the International Commission on Illumination, the International 

Energy Agency, and IEC to advance developments in solar resource assessment and support 

solar energy stakeholder needs. Hence, NREL will initiate the development of these new 

standards. Such standards are expected to play a significant role in improving the durability and 

efficiency of solar energy products, increasing consumer confidence in the quality of these 

products, contributing to a better understanding of the availability of the PV resource for solar 

energy conversion systems, and reducing the cost of solar project development.
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2 Developing a Framework for New Reference Cell 

Standards

PV reference cells have been used to measure solar irradiance for outdoor PV performance 

monitoring applications. Comparisons between reference cells and pyranometers are stated in 

[1], wherein reference cells can lead to improved characterizations of PV performance and 

thereby reduce the cost of capital and levelized cost of energy. Following is a summary of the 

possible applications of reference cells:

1. PV reference cells can be used for prospecting. As stated in [1], [2], PV reference cells

and the PV modules have close spectral matches that reduce the uncertainty in the 

available energy for conversion into electricity, which ultimately reduces the levelized 

cost of energy.

2. PV reference cells can be used for long-term system monitoring to estimate the service 

life and degradation of PV modules. 

3. PV reference cells can be used for short-term system performance tests, including 

performance guarantee tests. Reference cells and PV modules tend to respond similarly to 

varying meteorological conditions [2].

4. PV reference cells can be used to conduct research into specific aspects of performances: 

bifacial modules, thin-film spectral gains, soiling, etc.

In this report, we list a few possible standards that could guide the PV community toward using 

PV reference cells for estimating the PV resource (Figure 1). As we start developing the actual 

framework, we will include additional standards as needed to complete the logical sequence of 

standards for use by the PV industry.
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Figure 1. Flowchart demonstrating essential required standards and their linkage

2.1 Standard Spectra for a Wide Range of Standard Atmospheres

Existing international standards for reference broadband or ultraviolet spectra, such as ASTM 

G173, ASTM G177, ASTM G197, and IEC 60904-3 [7]–[19], are based on a single air mass, 

orientation, tilt, and set of atmospheric conditions. For instance, ASTM G173 is based on 1.5 air

mass (AM1.5), sun-facing, 37° tilt, and low-aerosol conditions. As stated in [11]–[14], these 

standards are essential for reporting standard testing conditions of materials such as reference 

cells. Appendix A of the new International Organization for Standardization (ISO) 9060:2018 

standard for pyranometers contains a spectral responsivity standard. This standard is based on a 

mismatch factor between two spectral distributions at air masses of 1.5 and 5 and for various 

atmospheres. The comparison is made between an instrument that has no spectral dependence 

and an ideal instrument that changes responsivity with changes in spectral distributions. Air 
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masses at 1.5 and 5 for various atmospheric conditions are used characterize the spectral 

dependence of the instrument. This characterization can be done theoretically as well as by 

measurement and describes the effect of changing spectrums on the instrument under study. A 

variety of reference climates are mentioned representing various climate zones. This information 

can then be used to characterize the spectral effects on reference cells at different tilts and 

orientations.

This work will follow the recommendation described in [12], which developed subordinate 

standard spectra representing various “characteristic” atmospheric conditions. These include both 

drier and moister climates than the U.S. Standard Atmosphere used in current standards as well 

as hazier aerosol conditions (more turbidity) or higher elevation. A total of eight supplementary 

atmospheric conditions are considered in [12], which demonstrate significant differences in 

global total irradiance (GTI), as shown in Figure 2.

Figure 2. Additional spectra GTI (20°) obtained from [12] compared to the IEC standard spectrum 

for 37° tilt angle 

Similarly, as we develop the framework and later in the standards development, we will use and 

build on the work done in the IEC 61853-4 [4] standard by including more representative 

standard reference climatic profiles that represent climate conditions of multiple areas and that

will benefit energy rating calculations. One difficult task will be to evaluate the impact of 

cloudiness on the spectral distribution and develop cloudiness spectral standards. The application 

of measured irradiance spectra can allow for the evaluation of performance tests during cloudy 

periods. In recent years, the number of spectroradiometers deployed worldwide has increased 

considerably, and we aim to draw heavily on this new resource to better understand and represent 

field conditions.
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2.2 Outdoor Process for Reference Cell Calibration and 

Characterization

Several methods are used to calibrate reference cells, as described in [20]–[21]. Here, we will use

and build on the work done in IEC 60904-4 [20], which is described as the “global sunlight 

method.” This will maintain the outdoor calibration of reference cells traceable to the World 

Radiometric Reference (WRR). As stated in [19], the WRR is determined by a group of selected 

absolute pyrheliometers maintained by the World Meteorological Organization, located in 

Davos, Switzerland. In addition, a spectroradiometer traceable to the National Metrology 

Institute will be used to understand the spectral, temperature, and angle-of-incidence effects.

The feature of the outdoor calibration of reference cells is that all types of reference cells are 

related to a single reference under outdoor irradiance conditions instead of standard test 

conditions. The general calibration approach will follow IEC 60904-4, ISO 9846, and ASTM 

G167 [20], [23]–[24]. For instance, the proposed method will entail an absolute cavity 

radiometer with a 5° field of view for direct normal irradiance (DNI) measurements and a diffuse 

pyranometer with a shading disk (Figure 3). The calibration of reference cells will include the 

temperature-corrected short-circuit current as well as the solar spectrum and spectral response of 

PV reference cells under clear-sky conditions from sunrise to sunset, thus encompassing all 

possible air masses for the day of calibration. As an example, the clear-sky conditions will be 

determined with a sky camera and will encompass long periods during which the sun is 

unobstructed by clouds and the sky is nearly cloudless. 

This outdoor calibration method will attempt to address some of the sources of uncertainty in the 

method considering that PV reference cells have limited spectral response ranges, nonuniform 

spectral responses, and varying temperature and cosine response characteristics. Given the 

accuracy of the spectroradiometers, measuring the temperature of the reference cell, and 

knowing the effect of temperature on the spectroradiometers, the effect of changing spectrum can 

be determined. The reference cell must be tested under a variety of temperatures to get the proper 

temperature effect. The same can be said for the spectroradiometers. The reference cell 

temperature is normally monitored, and this can be used to normalize the temperature to 25°C by 

correcting for the temperature effect that was measured. Under a spectral lamp, the spectral 

responsivity of the reference cell can be determined. When convolved with the spectral data, the 

average spectral response of the reference cell can be determined. Once the information on the 

spectral and temperature effects is available, the angle-of-incidence effects can be estimated. 

This can be done when the reference cell is in a horizontal position, and the spectral distribution 

of the global irradiance can be measured along with temperature. After the temperature and 

spectral effects, the angle-of-incidence effects are evaluated. These effects can then be compared 

to a theoretical model.

Finally, the method will also attempt to include a comprehensive calibration uncertainty analysis 

by following the Guide to the Expression of Uncertainty in Measurement [22].
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Figure 3. Absolute cavity pyrheliometer (left) and shaded diffuse pyranometer (right). Photos by 

Dennis Schroeder, NREL 22510 (left); and Tom Stoffel (right)

As an example, Figure 4 shows the calibration result for one silicon reference cell performed by

NREL’s Broadband Outdoor Radiometer Calibration (BORCAL) procedure in 2009. The 

BORCAL procedure follows a principle similar to that of ISO 9846 and ASTM G167 [23]–[24].

BORCAL provides responsivity in 2° bins of solar zenith angle. Note that the uncertainty (U95)

of the responsivity at 45° is around 4% and that the spectral dependence of the reference cell 

varies slightly from one day to another, considering the two traces of the afternoon blue line 

(p.m.) during two different days.

To reduce this uncertainty, several approaches could be followed. One approach could use a 

specific filter, as explained in Section 2.2.1. Another approach could make use of parallel 

spectroradiometer measurements and reference cell characteristics, such as its cosine response 

and spectral responsivity for various temperatures. Together with the reference cell properties, 

the measured spectra allow for the calculation of the spectral mismatch and cosine errors for 

each measurement of the calibration data set. The reference cell measurement can then be 

adjusted to remove these biases. Hence, the calibration factor can be derived by comparing the 

adjusted reference cell measurements to the broadband reference measurements.
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Figure 4. Calibration result for reference cell and associated calibration uncertainty. Illustration by 

Ibrahim Reda, NREL

Moreover, calibration of the reference cell in the manner that it is used (under various possible 

geometries) will also be considered by including a reference broadband diffuse on a tilted 

surface. Further, to understand the effect of tilt and orientation on the reference cell calibration, a 

spectroradiometer will be used to simultaneously measure the solar spectrum. The spectral 

measurement will enable understanding of the performance under various geometries. This type 

of calibration will also enable the determination of the temperature and angle-of-incidence 

effects.

2.2.1 Develop Standard Filter for Reference Cells Calibration to PV Resource

Historically, the calibration of reference cells that are used to assess the performance of PV 

systems has been done relative to the total solar resource under standard test conditions. The 

solar resource used to calibrate instruments that evaluate PV-based technologies covers a larger 

spectral range (300 nm–approximately 3,000 nm), which is a superset of the spectral irradiance 

range (300 nm–1,100 nm) to which current PV silicon-based technologies are sensitive. 

Performance guarantees based on the solar resource normally rely on a thermopile pyranometer 

mounted in the horizontal plane rather than the POA that matches the PV technology. This 

typically creates additional uncertainty in the performance estimates. To mitigate this issue 

(because reference cells are responsive to only a specific part of the solar spectrum to which a 

PV array is sensitive), it is recommended to evaluate the use of calibrated reference cells to 

measure the actual usable energy or PV resource. Several options can be used to “calibrate” 

reference cells. One possible option is to calibrate reference cells in a manner that is traceable to 
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the International Systems of Units (SI) of irradiance through the WRR. This involves a reference 

absolute cavity radiometer equipped with a spectral filter (300–1,100 nm) and a reference diffuse 

reference cell or a diffuse pyranometer with a similar spectral filter (300–1,100 nm). The 

approach is described by the flowchart in Figure 5.

Several papers have been published comparing reference cells and thermopile pyranometers on 

horizontal, fixed, and tracking surfaces; see [6], [25]–[31]. These studies show several of the 

characteristics of reference cells that need to be established to fully characterize a reference cell.

In addition, the shade and unshade calibration methods are difficult to apply to reference cells 

because they extend over a larger area compared to pyranometer sensors, and this increases the 

uncertainty in the calibration method.

An additional advantage of the filter method is to assist in establishing a spectral mismatch 

correction to the calibration method described in Section 2.2, which implements a broadband 

calibration.
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Figure 5. Flowchart illustrating the filter-based approach for reference cell calibration

2.3 Develop Standardized Outdoor Process to Transfer Calibration 

from Primary Reference Cell to Secondary or Field Reference 

Cells

This method will build on that described in IEC 60904-2 as the “calibration of secondary 

reference devices against a primary reference cell” using the “natural sunlight” method [20]. The 

calibration of the reference cells on a horizontal plane or for other orientations can be carried out 

using a “primary” reference cell, whose prior calibration would follow the method described in 

Section 2.2. This approach guarantees traceability to the WRR, but the primary and the unit
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under test should be same model with similar characteristics to reduce an unintended increase in 

uncertainty caused by differing device specifications. 

Similar to the method described in Section 2.2, the outdoor transfer of the calibration represents 

outdoor environmental conditions at a specific moment and specific atmospheric conditions. 

Even though this represents a large number of variables, care can be taken to minimize 

environmental effects, such as ground albedo or shading, by ensuring that such effects similarly 

affect both the primary and reference cells under test. 

2.4 Develop Best Practices for Field Deployment of Reference Cells

As described in [32]–[33], after a calibration procedure is developed carefully, a best practices

document will need to define the deployment conditions, maintenance requirements, verification 

procedures, and calibration frequencies for the appropriate use of reference cells during field 

deployment. The core of the best practices document will address the use of the new extended 

characterizations of reference cells in the field. These characteristics include:

• Linearity of output over the range of irradiance values being measured 

• Temperature dependence of the output of the devices over the range of temperatures to 

which the reference cells are subjected during deployment 

• Spectral responsivity of the reference cells in the spectral band for which they are 

designed to operate compared to the specific solar spectrum to which they are exposed

• Directional response through all incidence and azimuth angles that the reference cells are 

expected to experience throughout the year. For consistency, a specific orientation of the 

reference cell should be determined and used.

Separate best practices might be developed for sophisticated users who have a need for the

highest accuracy and for routine applications with more modest demands.

2.5 Classification of Reference Cells

ISO 9060 [34] provides classifications of pyranometers and pyrheliometers based on their 

specifications. The classifications of radiometers provide an easy way of referral in other 

standards and guides to facilitate the definition of a target measurement uncertainty and the 

process of uncertainty evaluation. The proposal here is to develop a classification standard 

similar to ISO 9060 but for reference cells. Comparison with these standards will inform the user

about how accurate and reliable the reference cell can be when used to evaluate the PV resource.

Obviously, developing this kind of standard will require effective engagement among all 

manufacturers of reference cells, users, calibration service providers, and research institutions. 

This will involve performing specification tests for variables that affect the accuracy of the

reference cells. Many indoor and outdoor characterization methods have been published, such as

those in [6], [25]–[31]. These specifications and reported results will be used as input to the 

standard. 

Further, the standards for reference cells should be robust enough to determine when the 

technologies used for the reference cells render them less reliable for the evaluation of new PV 
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technologies. These standards should be evaluated every few years to ensure that they are still 

adequate. 

The classification system is a qualification process, and thus it needs to be based on a set of 

reference characteristics and their acceptance intervals for each reference cell. Evidence of 

conformity will need to be obtained from the reference cells’ characteristics through testing the 

instrument design and through characterization of individual instruments during production or 

during a dedicated test. Depending on the reference cells’ class and characteristics, the quality 

assurance system of the manufacturer should either guarantee (within a reasonable level of 

confidence) that instruments of a certain model comply with the requirement or verify 

compliance by testing a requirement for the individual instrument.
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3 Challenges

• The approach described for developing this framework starts with reference cell 

measurements; however, the PV models and the satellite-derived irradiance data must 

also be adapted to the reference cell measurements. The adaptation of the PV models is 

required to assimilate reference cell data. The adaptation of the satellite models is 

required for plant yield predictions or satellite-based performance evaluation. One 

method to adapt the PV models and satellite data is by developing methods that use

spectrally resolved irradiance data.

• Another important challenge is how to account for the impact of cloudiness on standard 

spectra. Clouds tend to act as nearly ideal grey filters, thus depleting the clear-sky global 

horizontal irradiance (GHI) or GTI spectrum in a relatively spectrally constant way. One 

conceptually simple method to obtain a representative spectrum under realistic (partly 

cloudy) conditions during a long-term period is through a weighted average. Assuming a 

long-term average fraction, Fc, of cloudy periods over a given region, the mean 

representative spectrum would be Fc Tc Eλ during the cloudy periods and (1 – Fc) Eλ 

during the clear periods, where Tc is the average cloud transmittance, and Eλ is the 

spectral irradiance under scrutiny. This formulation is only a simple approximation, and 

detailed studies are needed to evaluate Fc and Tc over many regions. A similar approach 

has been used for adjustments to the diffuse component of rotating shadowband 

radiometers that use photodiode-based pyranometers [31].

• The development of consensus test methods to determine reference cell characteristics is 

a significant challenge. For instance, it is important to clearly identify the relationships 

among the temperature, spectral, and angle-of-incidence effects. Once the relationships 

are established, standardized test methods that detail the individual and aggregated effects

will need to be developed.

• It is critical to understand the propagation of uncertainty while various calibration and 

characterization methodologies are being developed. As an example, for calibration under

various tilts and orientations, the temperature and angle-of-incidence effects must be 

determined. This can be done, but the uncertainty increases if modeling is used.

• In the long term, additional research will be needed to evaluate to what extent the outdoor 

transfer of calibration described can be considered “universal” despite the interference 

caused by unavoidable solar spectrum variations when considering different seasons, 

locations, or geometries.

• Another challenge will be to harmonize existing methodologies/standards with the 

proposed standards so that consistency is maintained. This might require some changes to 

existing standards.

• The rapid evolution of various PV technologies will need to be closely monitored. It can 

be expected that the number of reference cells having specific spectral responses will 

continue to increase, thus making their regular calibration increasingly labor and time 

intensive.
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References

1. J. Meydbray, K. Emery, and S. Kurtz, “Pyranometers and Reference Cells: What’s the 

Difference?,” PV Magazine: Photovoltaic Markets and Technology (2012): 108–110.

2. A. Driesse, D. Dirnberger, C. Reise, and N.H. Reich, “Spectrally Selective Sensors for PV 

System Performance Monitoring,” Proceedings of the 38th IEEE PVSC (2012): 3,294–3,299.

3. International Electrotechnical Commission (IEC), IEC 61853-1 (Ed. 1.0 b: 2011):

Photovoltaic (PV) Module Performance Testing and Energy Rating—Part1: Irradiance and 

Temperature Performance Measurements and Power Rating (Geneva, Switzerland: 2011). 

4. ———, IEC 61853-2 (Ed. 1.0 b: 2016): Photovoltaic (PV) Module Performance Testing and 

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