Gaining Fundamental Understanding of Critical Failure Modes and Degradation Mechanisms in Fielded Photovoltaic Modules via Multiscale Characterization

In this work, a multiscale characterization and multimodal analysis approach is applied to silicon photovoltaic (PV) modules installed in the field. This approach links observed performance degradation to specific loss mechanisms (i.e., optical, recombination, resistive) and, ultimately, to root causes (i.e., changes in chemistry and/or microstructure). A key objective of this approach is the use of or, where needed, development of high-throughput, information dense data streams and the use of automated or semi-automated data analysis pipelines to remove subjectivity, improve reproducibility, and ensure scalability in both data collection and analysis. This work will present the application of this approach to a diverse collection of different PV modules installed at multiple sites, including lessons learned for each data stream and observations related to specific cell and module technologies.

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Published
2025-06-08
DOI
https://doi.org/10.1109/pvsc59419.2025.11133330
Primary Topic
Photovoltaic System Optimization Techniques
Type
article
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article

Gaining Fundamental Understanding of Critical Failure Modes and Degradation Mechanisms in Fielded Photovoltaic Modules via Multiscale Characterization

Hubert Seigneur, Philip J. Knodle, Manjunath Matam, Kristopher O. Davis et al.
Photovoltaic System Optimization Techniques
article

Gaining Fundamental Understanding of Critical Failure Modes and Degradation Mechanisms in Fielded Photovoltaic Modules via Multiscale Characterization

Hubert Seigneur, Philip J. Knodle, Manjunath Matam, Kristopher O. Davis, Dylan J. Colvin, Andrew M. Gabor, Laura S. Bruckman, Roger H. French, Sameera Nalin Venkat, Max Liggett, Joseph Raby, Mengjie Li, Brent A. Thompson
article en

Abstract

In this work, a multiscale characterization and multimodal analysis approach is applied to silicon photovoltaic (PV) modules installed in the field. This approach links observed performance degradation to specific loss mechanisms (i.e., optical, recombination, resistive) and, ultimately, to root causes (i.e., changes in chemistry and/or microstructure). A key objective of this approach is the use of or, where needed, development of high-throughput, information dense data streams and the use of automated or semi-automated data analysis pipelines to remove subjectivity, improve reproducibility, and ensure scalability in both data collection and analysis. This work will present the application of this approach to a diverse collection of different PV modules installed at multiple sites, including lessons learned for each data stream and observations related to specific cell and module technologies.

University of Central Florida (US)
Openalex Percentile: Top 85%
Photovoltaic System Optimization Techniques
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