Roadmap 6
Quality assurance to increase lifetime and reliability
Rationale for support
In the last decade and longer, photovoltaic module man- ufacturers have experienced a rapidly growing market along with a dramatic decrease in module prices (72). Such cost pressures have resulted in a drive to develop and im- plement new module designs, which either increase per- formance and/or lifetime of the modules or decrease the cost to produce them. Many of these innovations include the use of new and novel materials in place of more con- ventional materials or designs (73). As a result, modules are being produced and sold without a long-term understand- ing about the performance and reliability of these new materials. This presents a technology risk for the industry. In the past, several unexpected degradation mechanisms appeared after a few years of operational time in the field although they were not detected in any laboratory acceler- ated testing. Examples range from Potential Induced Deg- radation (PID) (74), Light and elevated Temperature Induced Degradation (LeTID) (75) or back sheet cracking (76) appeared after a few years operational time in the field although they were not detected in any laboratory accelerated testing.
Consumers and manufacturers rely on international stand- ards, such as those from Technical Committee “Solar Pho- tovoltaic Energy Systems” TC 82, or testing procedures proposed by international initiatives such as PVQAT (77) or test institutes to ensure that PV modules do not result in unexpected performance or reliability problems. Howev- er, testing procedures and also standards often have to be adapted to suit new module technologies or reflect new degradation modes. Another issue is that module manu- facturers do not typically advertise their bill of materials (BOM) and the BOM for a particular module model can vary depending on when and where it was made.
Status
A “one module type fits all” approach is still widely used in the PV industry, where one standard module design and unified material quality level composition is used for appli- cations in widely varying environmental and climatic con- ditions and setups around the world. Due to the high cost pressure, new materials, components or module designs that promise a reduction of LCOE are brought into the mar- ket at a very early stage. Examples for recent changes are new wafer and module sizes, replacement of Al-BSF cells with PERC and SHJ cells, half cells, new interconnection technologies (multiwire, shingling), new polyolefin encap- sulants and back sheets and so on.
Currently the industry relies mostly on extended IEC testing for qualification of new module designs. However, these are single stress tests that do not replicate typical operat- ing conditions of PV modules. Hence, the aforementioned field failures were not detected during module qualification testing. Recently a lot of effort has been put into development in sequential or combined test approaches, such as MAST (78) or CAST (79) tests. However, these approaches are elaborate, time consuming and expensive, and therefore are mostly used for R&D purposes, but not widely used for module qualification in the PV industry.
Targets, Type of Activity and TRL
PV Module development
Innovations to reduce module environment tem- perature in hot and dry climates in order to increase energy yield
Database/Design Tool for material and component selection with respect to climatic or environmental conditions of PV system
Virtual prototyping tools to predict thermo-me- chanical failure probability in the design phase
PV Module qualification
Combined stress test infrastructure for qualification of new PV module designs
- Climate-specific (e.g. for use in deserts or tropi- cal regions)
- Application-specific (e.g. floating PV, BIPV, AgriPV, etc.)
Established methods for module forensics
Lifetime and yield prediction
Development of data-driven and/or physical models for prediction of (remaining) lifetime of PV modules and PV systems based on accelerated life cycle test- ing
Development of a methodology to determine the long term degradation and performance loss rates from several years of operation data.
More accurate yield assessments and LTYP. Novel technologies and system design require more accu- rate models for the determination of Yield Assess- ment and Long-term Yield Prediction
The role of digitalisation
Comprehensive generation of relevant data during produc- tion and operation of photovoltaics will be a key feature for enabling enhanced quality assurance of PV. This in- cludes automated data processing (e.g. feature selection, image analysis and data reduction), statistical modelling to find correlations and the creation of predictive models (data driven or physical) describing long term behaviour of photovoltaic modules and systems.
KPIs
| KPI | Target Value (2030) |
|---|---|
| Proven lifetime of PV modules through extended testing (de- fined as 80 % of initial performance) | 40 years |
| Accuracy of yield assessments for new technologies and novel system design with uncertainty (1 sigma) | <5 % |
| Milestone | |
| Establishment of European testing capacities for combined or sequential stress tests | |