Title: Advance Degradation Modelling of Photovoltaic Modules and Materials!
Project Management: Austrian Institute of Technology
Funding Agency: FFG
Duration: 01/2021 to 12/2022
- Polymer Competence Center Leoben
- FH Technikum Wien
- OFI Österreichisches Forschungsinstitut für Chemie u. Technik
- Silicon Austria Labs
Due to the large effort in terms of time and equipment necessary for reliability testing of photovoltaic (PV) modules, the PV community has always endeavoured to obtain service life estimates, based on an extrapolation of measurement and characterization data from accelerated aging tests or modelling.
The planned ADVANCE! R&D project will address the potential of innovative and complex statistical and machine learning data processing methods for digital analysis and improved modelling of the time and stress-dependent performance (degradation and reliability) of PV modules.
The proposed research will focus on data science approaches to understand material degradation. Quantitative evaluation algorithms of spectroscopic data, characteristics, and innovative image analyses will be developed to describe the material degradation depending on certain stress factors in numbers (digitization of images, spectral and characteristics information). Using a materials science approach that employs statistical analyses, the mechanistic processes / degradation network pathways for the materials used in PV modules will be developed by using network structural equation modelling (netSEM). Path diagrams will visualize the effects of stress factors and material properties on PV module degradation and loss of performance; the underlying mathematical relationships will make the effects digitally describable.
- characterization data of PV materials / components / modules, determined before, during and after accelerated aging tests (originating from the INFINITY project) for material degradation and
- measurement data from field-aged modules
predictions can be made regarding the service life of PV modules (i.e. multi-material composites) under a wide variety of operating conditions. These predictive models will also be used to derive suggestions for improvements in manufacturing and guidelines for predictive maintenance of PV-plants.
This highly interdisciplinary research project is intended to open up new paths in the digital analysis of the long-term and degradation behaviour of PV modules and to lay the foundations for future highly efficient material developments for PV and predictive maintenance requirements for PV systems.
A comprehensive database generated in the flagship project INFINITY will be used as the data basis: extensive measurement and characterization data of hundreds of sample modules that were subjected to precisely defined accelerated aging scenarios. These existing data time series of multiple characterization methods - if necessary supplemented by further test series, and by the inclusion of literature data - will be used to derive internal causal relationships, with the focus put on the correlations between aging of materials and material composites and the electrical module performance.