Photovoltaic Module Energy Yield Measurements: Existing Approaches and Best Practice

IEA PVPS Task 13, Subtask 3 Report IEA‐PVPS T13‐11:2018 May 2018

Table of Contents

Foreword …………………………………………………………………………………… 9

Acknowledgements ……………………………………………………………………………….. 10

List of abbreviations ……………………………………………………………………………… 11

Executive Summary ………………………………………………………………. 13

1 2

3 4

Introduction ……………………………………………………………………………………… 17

Background Information ………………………………………………………… 18

  1. 2.1  Scope of Testing………………………………………………………………………………….. 18
  2. 2.2  Energy Yield versus Energy Rating …………………………………………………………. 19

International Survey on Measurement Practices ……………………………………………. 20

Test Environment and Hardware Requirements ……………………………………………….. 22

4.1 Mounting Structure & Surroundings ……………………………………………………. 22

  1. 4.1.1  Mounting rack layout ………………………………………………………………….. 23
  2. 4.1.2  PV module installation ……………………………………………………………… 24
  3. 4.1.3  PV module shading………………………………………………………………………… 24
  4. 4.1.4  Albedo ……………………………………………………………………….. 26
  5. 4.1.5  Sensor positioning ……………………………………………………….. 26

4.2 Current and Voltage Measurements ……………………………………………………. 27

  1. 4.2.1  Hardware solutions …………………………………………………….. 27
  2. 4.2.2  Hardware characteristics and configuration ………………………………….. 30
  3. 4.2.3  Recommendations …………………………………………………………….. 35

4.3 Measurement of Environmental Parameters …………………………………… 37

4.3.1 In‐plane irradiance ………………………………………………………… 37

4.3.2 Module temperature………………………………………………………… 42

4.3.3 Meteorological data ………………………………………………… 45

4.3.4 Spectral irradiance ………………………………………………………. 46

Data Quality Control and Maintenance Practice ………………………………. 50

  1. 5.1  Quality Markers ……………………………………………………………….. 50
  2. 5.2  Maintenance…………………………………………………………………… 50

Characterization of Test Modules ……………………………………………………… 52

  1. 6.1  Module Selection/Sampling………………………………………………………….. 52
  2. 6.2  Pre‐testing and Control Measurements ……………………………………… 53
  3. 7

7.1 Module Energy Yield Benchmarking ……………………………………………………. 55

  1. 7.1.1  Energy yield assessment………………………………………………………………………………. 55
  2. 7.1.2  Impact of STC power …………………………………………………………………………………… 57
  3. 7.1.3  Impact of temperature, irradiance, angle of incidence and spectrum ……………. 59
  4. 7.1.4  Calculation of derate factors ………………………………………………………………. 65
  1. 7.2  Comparison of Module Data from Different Climates……………………………………… 66
  2. 7.3  Module Performance Loss Rates (PLR) …………………………………………………………… 71
    1. 7.3.1  Methodologies …………………………………………………………………………………….. 71
    2. 7.3.2  Performance metrics …………………………………………………………………………… 72
    3. 7.3.3  Filtering and correction techniques ……………………………………………………. 73
    4. 7.3.4  Statistical techniques…………………………………………………………………………. 75

Measurement Uncertainty Analysis …………………………………………………………………………….. 79

  1. 8.1  Introduction ………………………………………………………………………………………………………. 79
  2. 8.2  Methodologies for Uncertainty Analysis ……………………………………………………………….. 80
  3. 8.3  Single Uncertainty Contributions ………………………………………………………………………….. 80
    1. 8.3.1  Uncertainty in STC power UPstc ……………………………………………………………………… 80
    2. 8.3.2  Uncertainty in irradiance Uand irradiation U………………………………………………. 81
    3. 8.3.3  Uncertainty in power UPmax ………………………………………………………………………….. 81
    4. 8.3.4  Uncertainty in key performance indicators UE, UYa and UMPR…………………………….. 82

8

8.4 Relative Uncertainties…………………………………………………………………………………………. 84 Summary and Conclusions …………………………………………………………………………………………. 85 Annex 1: Empty Questionnaire ………………………………………………………………………………………….. 98 Annex 2: Test Facility Sheets ……………………………………………………………………………………………… 99

Foreword

The International Energy Agency (IEA), founded in November 1974, is an autonomous body within the framework of the Organization for Economic Co‐operation and Development (OECD) which car‐ ries out a comprehensive programme of energy co‐operation among its member countries. The European Union also participates in the work of the IEA. Collaboration in research, development and demonstration of new technologies has been an important part of the Agency’s Programme.

The IEA Photovoltaic Power Systems Programme (PVPS) is one of the collaborative R&D Agree‐ ments established within the IEA. Since 1993, the PVPS participants have been conducting a variety of joint projects in the application of photovoltaic conversion of solar energy into electricity.

The mission of the IEA PVPS Technology Collaboration Programme is: To enhance the international collaborative efforts which facilitate the role of photovoltaic solar energy as a cornerstone in the transition to sustainable energy systems. The underlying assumption is that the market for PV sys‐ tems is rapidly expanding to significant penetrations in grid‐connected markets in an increasing number of countries, connected to both the distribution network and the central transmission net‐ work.

This strong market expansion requires the availability of and access to reliable information on the performance and sustainability of PV systems, technical and design guidelines, planning methods, financing, etc., to be shared with the various actors. In particular, the high penetration of PV into main grids requires the development of new grid and PV inverter management strategies, greater focus on solar forecasting and storage, as well as investigations of the economic and technological impact on the whole energy system. New PV business models need to be developed, as the decentralised character of photovoltaics shifts the responsibility for energy generation more into the hands of private owners, municipalities, cities and regions.

IEA PVPS Task 13 engages in focusing the international collaboration in improving the reliability of photovoltaic systems and subsystems by collecting, analyzing and disseminating information on their technical performance and failures, providing a basis for their technical assessment, and de‐ veloping practical recommendations for improving their electrical and economic output.

The current members of the IEA PVPS Task 13 include:

Australia, Austria, Belgium, Canada, China, Denmark, Finland, France, Germany, Israel, Italy, Japan, Malaysia, Netherlands, Norway, SolarPower Europe, Spain, Sweden, Switzerland, Thailand and the United States of America.

This report focusses on the measurement of modules in the field for the purpose of energy yield or performance assessments. This document should help anyone intending to start energy yield meas‐ urements of individual PV modules to obtain a technical insight into the topic, to be able to set‐up his own test facility or to better understand how to interpret results measured by third parties.

The editors of the document are Gabi Friesen and Ulrike Jahn.

The report expresses, as nearly as possible, the international consensus of opinion of the Task 13 experts on the subject dealt with. Further information on the activities and results of the Task can be found at: http://www.iea‐pvps.org.

List of abbreviations

AM Air mass
AoI Angle of incidence
APE Average photon energy
DHI Diffuse horizontal irradiance
DNI Direct normal irradiance
E Energy output
ECT Equivalent cell temperature
ER Energy rating
FF Fill factor
G Irradiance
Gi In‐plane (plane of array) irradiance
Gi,d In‐plane diffuse irradiance
Gi,b In‐plane direct beam irradiance
Geff Effective irradiance or spectrally sensitive irradiance Gstc Reference irradiance at standard test conditions GHI Global horizontal irradiance
GNI Global normal irradiance
H Irradiation
IAM Incident angle modifier
Imp Current at maximum power point
Isc Short circuit current
IR Infrared
KPI Key performance indicator
LID Light induced degradation
MM Spectral mismatch factor
MPP Maximum power point
MPPT Maximum power point tracker
MPR Module performance ratio
Pnom Nominal power
Pmax Power at maximum power point

11

Pstc Power at standard test conditions
Pstc,stab Stabilized power at standard test conditions
PID Potential induced degradation
PLR Performance loss rate
POA Plane of array
PR Performance ratio
Rs Series resistance
Rsc Resistance at short circuit current
Roc Resistance at open circuit voltage
SIF Spectral influence factor
Tstc Reference temperature at standard test conditions Tc Cell temperature
Tamb Ambient temperature
Tmod Module temperature
TBS Back sheet temperature
ΔTCBS Difference between cell and back sheet temperature u Uncertainty
UV Ultraviolet
Vmp Voltage at maximum power point
Voc Open circuit voltage
w Wind speed
Ya PV module (array) energy yield
Yf Final yield
Yr Reference yield
Θ Tilt angle
 Recording interval
γ Pmax temperature coefficient

Executive Summary

The monitoring of single PV modules plays an important role in the demonstration and deeper un‐ derstanding of technological differences in PV module performance, lifetime and failure mecha‐ nisms.

With the growing share and relevance of PV in the market, the number of stakeholders performing outdoor measurements at module level is continuously increasing: test institutes, certification labs, PV module manufacturers, but also non‐experts in the field, e.g. distributors, investors or insurance companies are publishing their results in a wide range of media, from scientific to technical journals, from risk assessment reports to purely commercial publications. The comparability of these meas‐ urements is however made difficult by the different testing approaches and missing declarations on measurement uncertainties. This is mainly due to the fact that there is no dedicated standard or recognized guideline published, covering the specific needs of PV module energy yield measure‐ ments.

The two main reference documents available today are a best practice guideline for the testing of single modules which was presented by DERLAB (European Distributed Energy Resources Labora‐ tories) in 2012 [1] and the IEC 61724‐1 Technical Standard for the monitoring of PV systems, pub‐ lished in 2017 [2]. The first one is limited to the definition of some testing requirements, without distinguishing between different testing purposes. It does not consider uncertainty contributions at single measurement level and gives no recommendations of how to reduce them. The second one addresses many of the missing aspects, with details on sensors, equipment accuracy, quality check and performance analysis, but without considering the special requirements of single module monitoring and benchmarking studies.

Besides the slightly different scopes, the main difference between monitoring at module or system level is that system monitoring generally does not obtain the same accuracy reachable at module level. Secondary effects related to the system configuration (e.g. inverter performance, module sampling, module selection, mismatch losses, …) and spatial variations over the system (e.g. venti‐ lation, soiling, shading, …) are often hiding the technological differences which are the focus and reason for module level monitoring. Moreover, the system monitoring standard does not include any IV‐curve measurements, which are the base of many performance, lifetime and failure studies performed at module level. On the other hand, system monitoring is including some measure‐ ments, which are not relevant for module monitoring like AC currents and voltages or other system related electrical parameters.

Small systems, designed specifically for the purpose of performance or reliability studies, could however be a good alternative if all secondary uncertainties would be reduced to a minimum and the measurements of the DC side and the meteorological parameters would be good enough to allow inter‐comparisons and detailed analysis. The disadvantages of the testing of entire systems are the higher space occupation and the larger number of modules to be characterized and in‐ spected, but, on the other hand, real system stress conditions are better simulated and a more statistically relevant number of modules is measured. New hardware solutions able to measure the IV‐curves of single PV modules within a string could make this approach more attractive and afford‐ able in the near future.

The goal of this document is to fill some of the normative gaps and to help anyone intending to start energy yield measurements of individual PV modules to obtain a technical insight into the topic, to be able to set‐up his own test facility or to better understand how to interpret results measured by third parties.

13

The current practices for energy yield measurements of individual PV modules applied by major international research institutes and test laboratories are presented in this report. Best practice recommendations and suggestions to improve energy yield measurements are given to the reader.

A survey was conducted within the IEA PVPS Task13 consortium to assess how module energy yield measurements are performed today and how the uncertainties are calculated and reported to the end‐users. Fifteen Task members with experience in PV module monitoring from over 30 test facil‐ ities installed all over the world have been interviewed. Many ISO17025 accredited test laborato‐ ries, as well as R&D institutes, have been included. The questionnaire covered all aspects, starting from general questions on the scope of testing to the test equipment, procedures, maintenance practice, data analysis and reporting.

The purposes, for which the monitoring is performed at PV module level, can be manifold:

  •   To assess the stability of a cell technology under specific environmental conditions and stress factors (degradation studies),
  •   to measure the over or under‐performance with respect to a reference technology (benchmarking studies), understanding single environmental loss factors (temperature, spectrum, irradiance, wind, shadows, soiling, etc.) and
  •   to collect data for the validation of energy prediction models or the calibration of PV module parameters for a specific model.It is to be mentioned that module energy yield measurements are also required for the validation of the IEC 61853 standard on energy rating [3,4,5,6], which is currently in elaboration and which aims at replacing the current power rating according to standard test conditions of modules. High precision measurements with accurately determined uncertainties are the key to be able to foster the introduction of any energy rating in the future. Further, energy yield predictions as described in the Report IEA‐PVPS T13‐12:2018 entitled ‘Uncertainties in PV System Yield Predictions and Assessments’ will profit from this.Less frequently, outdoor measurements are performed for the purpose of module characterization, which is mostly done indoors with solar simulators, for which the measurement uncertainties are better defined and known. If characterization is performed under outdoor conditions, it is generally done using a sun‐tracker and other means to control the irradiance and temperature levels. In this case the integrated energy yield is not relevant and the electrical characterization is therefore not within the scope of this document.The different scopes give rise to different testing requirements and data analysis. The most relevant measured or calculated key performance indicators (KPI) are: Instantaneous power (P), energy out‐ put E, energy yield (Ya), module performance ratio (MPR) and performance loss rate (PLR). The measurement accuracy of the output data depends as much on the measurement accuracy of the single components forming the measurement system, as on the conditions at the measurement system and its configuration.This report gives an overview of the most important aspects to be considered for the set‐up of a test facility, e.g. the layout of the test rack and mounting instructions for modules and sensors, as well as how to combine and configure any current/voltage measurement system, like IV‐curve tracers and/or maximum power point trackers (MPPT) for PV modules in order to reduce any measurement artefacts ( e.g transient or capacitive effects, MPP tracking errors, wrong loading, cable losses, …) and errors in the final determination of the KPI’s due to inadeguate data recording (e.g. low sampling rates, syncronisation errors,…).Available quality control measures, such as calibration needs, quality markers for erroneous data (e.g. temperature sensor detachment, sensor soiling, data acqusition errors, …) and maintenance14

practices (visual inspection, cleaning intervals, e‐mail alert, …) are presented to increase the early detection of problems such as drifts, failures or malfunctions, which could further increase the measurement uncertainty.

The final goal is to achieve accurate and reliable data, also over a long time period, and higly comparable data, even with data from other test facilities mounted according to the same guidelines. A better understanding how to reduce single measurement uncertainties, by quantifying and documenting them, is therefore essential.

However, even by reducing all measurement uncertainties, an adequate inter‐comparison between different PV technologies is only possible if the PV modules are selected according to well‐defined sampling procedures and if the STC power and its uncertainty are known. The STC power is actually one of the main contributions to the uncertainty for the calculation of parameters Ya and MPR. The nominal power Pnom as declared by the manufacturer is generally considered as the less adequate for any inter‐comparison, because it can considerably differ from the real power of a PV module, its measurement uncertainty is rarely documented and it is subject to commercial marketing strat‐ egies. The most suitable value for benchmarking of products is the real STC power, with known uncertainty values and no variation after installation. The last aspect is important because, if the module is not stabilized before measuring the STC power, it can lead to misleading results. In gen‐ eral, the lower the measurement uncertainty and the higher the stability in the field, the higher the accuracy of the ranking is. High precision measurements and validated stabilization procedures per‐ formed by accredited test laboratories lead to highest accuracies. In general, electrical characteri‐ zation and optical inspections of PV modules before installation will guarantee that no low quality, defective or damaged modules are chosen.

To understand technological differences and the over‐ or under‐performance of one technology with respect to another under specific climatic conditions, the individual sources of loss with re‐ spect to the power under standard test conditions have to be quantified. Different approaches exist to calculate single de‐rating factors which allow to select the technology with the lowest loss at specific conditions (e.g. high fraction of diffuse light, high temperatures, high angle of incidence, etc.). To calculate the losses, either a full electrical characterization of the module under controlled laboratory conditions or the monitoring of the IV‐curves is needed.

It has to be mentioned that, in terms of bankability of the modules, the degradation rate is more important than the precise knowledge of the instantaneous performance given by the electrical module parameters. In the long term, the annual performance loss can have a higher impact on the life‐time productivity than the electrical parameters. Much less is known on the impact of the en‐ vironment on the ageing process. For this reason, many tests laboratories focus on long‐term meas‐ urement campaigns and the calculation of the PLR.

Independent of the determined KPI, deviations are only meaningful if they are higher than the measurement uncertainties. There are situations, where the magnitude of measurement uncer‐ tainty is larger than the investigated environmental effect so that the result cannot be used for benchmarking or degradation studies without taking it into account. The knowledge and reduction of the uncertainties should be mandatory for anyone performing such measurements. Sometimes, a differentiation has to be done between absolute and relative measurements.

In general, the survey performed within the PVPS Task 13 expert group highlighted that the meas‐ urement accuracy and scientific detail within most test laboratories are very high. This is demon‐ strated by a recurrent use of high precision equipment, good measurement practice and the imple‐ mentation of good quality control and maintenance practice. Nevertheless, the survey revealed some limits, which are mainly the comparability of different outdoor data and the use of these for

15

the validation of models due to a limited harmonization or availability of measurement uncertain‐ ties for the main KPIs. The main reason for this is that compared to the measurement of the STC performance using a solar simulator, for which the measurement uncertainties have been inten‐ sively investigated and validated over the last years, in energy yield measurements the reproduci‐ bility of test conditions is not possible and the determination of the measurement uncertainty is much more complex. The uncertainty is actually site and time dependent and impacted by many factors, which are difficult to estimate and sparely described in literature.

The first step to improve the comparability of outdoor measurements is to agree on the main un‐ certainty contributions and to suggest a common approach for the reporting of measurement un‐ certainties. This document gives recommendations on how to reduce the main uncertainty contri‐ butions and how to calculate them in future projects. Major efforts should be invested in imple‐ menting and validating best practice approaches through international round robins in future.

About Ritesh Pothan

Ritesh Pothan, is an accomplished speaker and visionary in the Solar Energy space in India. Ritesh is from an Engineering Background with a Master’s Degree in Technology and had spent more than a decade as the Infrastructure Head for a public limited company with the last 9 years dedicated to Solar and Renewable Energy. He also runs the 2 largest India focused renewable energy groups on LinkedIn - Solar - India and Renewables - India
This entry was posted in PV, Renewables, Solar, Solar PV and tagged , , , , , , . Bookmark the permalink.

Leave a Reply

Please log in using one of these methods to post your comment:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Google photo

You are commenting using your Google account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s