PV Reliability as Addressed in IEA PVPS Task 13 · • Technical Report on “Assessment of PV...

IEA INTERNATIONAL ENERGY AGENCY

PHOTOVOLTAIC POWER SYSTEMS PROGRAMME

PV Reliability as Addressed in

IEA PVPS Task 13

Ulrike Jahn, Magnus Herz, TÜV Rheinland, Germany

Marc Köntges, ISFH, Germany

K. A. Berger, Austrian Institute of Technology GmbH

SAYURI-PV 2016

International Workshop on the Sustainable Actions

for “Year by Year Aging” under Reliability

Investigations in Photovoltaic Modules

4th - 5th, October 2016, Japan



IEA PVPS Basics

• 29 members: 23 countries, EC, SolarPower Europe, SEPA, SEIA, Copper Alliance

• Most recent member: Finland

• Activities are carried out collaboratively on a country basis along a number of technical and non-technical subjects

• Currently, 7 Tasks are active

http://www.iea-pvps.org/

http://www.seia.org/



Relevant PVPS Issues • Scenario work

• Market development and trends

• Policy framework

• Business models

• New technologies and applications

• Urban and rural implementation

• Large scale deployment

• Environmental aspects

• Quality and reliability

• Grid integration



PVPS Task 13 2014 - 2017

Task 13 work:

Subtask 1: Economics of PV System

Performance and Reliability

Subtask 2: System Performance and Analysis

Subtask 3: Module Characterization and

Reliability

Subtask 4: Dissemination



Focus on technical assumptions

used in PV financial models

• Review of current practices of

technical risk assessment

• Recommendation on means to

describe uncertainty

• Suggestions for inclusion of

uncertainty in output charts

Subtask 1: Economics of PV System Performance

and Reliability



Subtask 2: System Performance and Analysis

• Field performance analysis using two

complementary approaches

• Specific data evaluations, including

failure prediction and grid integration

impact on performance

• Uncertainty framework of data

acquisition, modelling and long-term

energy yield prediction accuracies

• PV Performance Modeling

Collaborative: international access to

the best modeling methods and tools



Subtask 3: Module Characterisation and Reliability

• Power rating, uncertainties and

propagation into modelling

• Module energy yield data from test

fields in different climates

• Characterization of PV modules in the

field

• Guidelines on IR and EL imaging for

PV qualification in the field

• Assessment of PV module failures in

the field



Subtask 3:

Module Characterization and Reliability

3.1 Power rating, uncertainties and propagation

into modelling

3.2 Module energy yield data from test fields in

different climates

3.3 Characterization of PV module condition in the

field - Guidelines on IR and EL in the field

3.4 Assessment of PV module failures in the field



Cost-based risk numbers for PV modules - Utility scale

Top 10 failures/risks detected by different

methods: VI, IR, EL, FL

Motivation

www.solarbankability.eu

RPN (Risk Priority Number)

-> CPN (Cost Priority Number)



Cost-based risk numbers for PV modules - Residential

• Only failures detected by visual inspection.

• most probably, most of the PV modules that belong

to residential segment, have failures that have not been

yet detected.

Motivation RPN (Risk Priority Number)

-> CPN (Cost Priority Number)



ST 3.4 Assessment of PV module failures in the

field

Motivation:

• To document observed conditions of PV modules in

the field aged in a range of different climates

• To classify and analyse PV module failures based on

a commonly defined failure description (database)

• To gain a comprehensive assessment of PV module

conditions in the field

– A growing number of PV installations world-wide fail to fulfil

quality and safety standards

– There is little knowledge on the extent of bad installations,

failure statistics and mechanisms.



Part 1:

Characterization of PV Module Condition in the Field

1.1: Review of literature and collection of local reports on

climatic depending aging of PV modules

1.2: Documentation of PV module condition according to

the Visual Inspection Sheet (2-year-operation)

1.3: Analysis of the available field data (visual inspection)

for trends to identify the most common failures and

their correlation to different climates (database).

ST 3.4 Assessment of PV module failures in the

field



ST 3.4 Method: Visual Inspection

Delamination, Hot Spot



ST 3.4 Method: Visual Inspection • Broken connector • Detached frame

• Broken module • Broken cell



ST 3.4 Method: Visual Inspection • Broken • Detached frame

Shading losses



Visual Data Collection Tool



Visual Data Collection Tool



PV module condition examples: 4. Backsheet -> Damage:

Burn marks: # = 2

Bubbles: # = 1, size> 30mm

Discoloration of encapsulent:

discolored area, where?

Delamination: wavy, dimension

• Inspector is asked to evaluate damage of the backsheet

indicating the types of damage and providing additional details



Documentation of PV Module Condition: Climate classification according to Köppen-Geiger

http://koeppen-geiger.vu-wien.ac.at/ according to the

geographic position (for example Cfb for Freiburg).

http://koeppen-geiger.vu-wien.ac.at/









PV Module Condition Database (TÜV)



Part 2: Objectives

• Provide status of ability to predict power degradation

PV module failure modes

• Provide a description of interactions and

incompatibilities of materials in PV modules

• Assess the impact of PV module failure modes for four

climatic zones

• Provide an order of importance of tests for the four

climatic zones

Subtask 3.4:

Assessment of PV Module Failures of the Field



Subtask 3.4: Survey1 (ISFH)

Assessment of PV Module Failures of the Field

1http://iea-pvps.org/index.php?id=344



Database Composition

• Main survey data from Europe

• Moderate climate dominates data

• Technology distribution equal to

market distribution

• 144 failure-survey-data

sets from 18 countries

23



Analysis of Failure Occurrence

• Count only failures leading to power loss

• Cell cracks 1-2 years, PIDs 3-4 years

PID

s

Cell

cra

cks

24



Analysis of Failure Occurrence

• Defect bypass diodes, in the first years but also later

• Discolouring all years, but accumulate after 18 years D

iscolo

uring

Defc

t B

PD

25



Degradation Rates – Impact on Investigated Part of PV System



Mean Degradation Rate of the Investigated Part of PV System

• Most harmful failures affect only part of the PV modules

• On system level cell cracks have similar degradation rates

• PIDs drops from 16%/a to 9%/a, cell cracks from 5%/a to 3%/a

27



Activity 3.4: Conclusion

• Developed method to evaluate failure data from the field

• Cell cracks dominate the early failures during year 1 and 2

• Degradation rate caused by cell cracks is highest

(8%/a) in cold and snow climates

• PIDs dominates year 3 and 4 in the failure statistic

(16%/a) in moderate climate

• Great variation of degradation rates for bypass diode failure,

may cause dramatic power loss

• In all climates mean degradation rate of discoloring is below 1%/a

Download survey and explanation:

http://iea-pvps.org/index.php?id=344



• Global network to improve the reliability of PV systems

and subsystems by collecting, analyzing and

disseminating information on their technical performance

and failures.

• Technical Report on “Assessment of PV Module Failures

in the Field” will be published in April 2017.

• Improved methods to detect failures in the field and

modeling of PV module power degradation will lead to

more qualified assessments of PV systems and thus

lower risk in PV investments.

ST 3.4 Summary



20+ IEA countries, 36+ institutions

45 participants, 60+ members

IEA PVPS Task 13 Team

14th Task13 Meeting in Bolzano, Italy, 06-08 April 2016

www.iea-pvps.org



Thank You for Your Attention !

- We, IEA PVPS Task 13, have published 4 documents.

- 9 documents (Derivatives) will be published in 2017.

http://www.iea-pvps.org/index.php?id=57

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