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Assessing Factors Underpinning PV Degradation Through Data Analysis

DuraMAT uses advanced data analytics to more accurately pinpoint photovoltaic (PV) module degradation and isolate its causes.

PV degradation is difficult to isolate among the multitude of factors leading to observed power loss (from benign to problematic). Therefore, through data analysis, we seek to:

  • Improve estimates of overall degradation using standard PV data sets
  • Better separate and isolate the factors underpinning observed degradation (system versus module, various electrical parameters, climate, or materials).

Outputs of this project include open-source software for analyzing production PV data and identifying potential failure modes as well as information regarding how bill of materials may influence module robustness.

Core Objective

Central Data Resource


Lawrence Berkeley National Laboratory


  • Algorithms developed for data cleaning can be used in conjunction with many analyses of degradation and will be integrated into existing tools (e.g., pvlib, rdtools, pvanalytics).
  • The PV-Pro method developed can be used to analyze production data and extract single diode parameters that can indicate sources of degradation.
  • The bill of materials analysis can help address whether data analytics can identify issues in materials properties that ultimately lead to reliability failures.


The results of this project will be available and disseminated publicly.


To learn more about this capability, contact Anubhav Jain.

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