PV Reliability as Addressed in IEA PVPS Task 13

Transcription

1 PV Reliability as Addressed in IEA PVPS Task 13 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 Ulrike Jahn, Magnus Herz, TÜV Rheinland, Germany Marc Köntges, ISFH, Germany K. A. Berger, Austrian Institute of Technology GmbH

2 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

3 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

4 PVPS Task 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

5 Subtask 1: Economics of PV System Performance and Reliability 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

6 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

7 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

8 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

9 Motivation RPN (Risk Priority Number) -> CPN (Cost Priority Number) Cost-based risk numbers for PV modules - Utility scale Top 10 failures/risks detected by different methods: VI, IR, EL, FL

10 Motivation 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.

11 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.

12 ST 3.4 Assessment of PV module failures in the field 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).

13 Delamination, Hot Spot IEA INTERNATIONAL ENERGY AGENCY ST 3.4 Method: Visual Inspection

14 ST 3.4 Method: Visual Inspection Broken connector Detached frame Broken module Broken cell

15 ST 3.4 Method: Visual Inspection Broken Detached frame Shading losses

16 Visual Data Collection Tool

17 Visual Data Collection Tool

18 PV module condition examples: 4. Backsheet -> Damage: Burn marks: # = 2 Bubbles: # = 1, size> 30mm Delamination: wavy, dimension Discoloration of encapsulent: discolored area, where? Inspector is asked to evaluate damage of the backsheet indicating the types of damage and providing additional details

19 Documentation of PV Module Condition: Climate classification according to Köppen-Geiger according to the geographic position (for example Cfb for Freiburg).

20 PV Module Condition Database (TÜV)

21 Subtask 3.4: Assessment of PV Module Failures of the Field 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

22 Subtask 3.4: Survey 1 (ISFH) Assessment of PV Module Failures of the Field 1

23 23 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

24 PIDs Cell cracks IEA INTERNATIONAL ENERGY AGENCY 24 Analysis of Failure Occurrence Count only failures leading to power loss Cell cracks 1-2 years, PIDs 3-4 years

25 Defct BPD Discolouring IEA INTERNATIONAL ENERGY AGENCY 25 Analysis of Failure Occurrence Defect bypass diodes, in the first years but also later Discolouring all years, but accumulate after 18 years

26 Degradation Rates Impact on Investigated Part of PV System

27 27 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

28 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:

29 ST 3.4 Summary 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 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.

30 IEA PVPS Task 13 Team 20+ IEA countries, 36+ institutions 45 participants, 60+ members 14th Task13 Meeting in Bolzano, Italy, April 2016

31 Thank You for Your Attention! - We, IEA PVPS Task 13, have published 4 documents. - 9 documents (Derivatives) will be published in