pvdeg

Set of tools to calculate degradation responses and degradation related parameters for PV.
https://github.com/nrel/pvdegradationtools

Category: Renewable Energy
Sub Category: Photovoltaics and Solar Energy

Keywords

degradation duramat photovoltaic-systems pv-modules python reliability

Keywords from Contributors

photovoltaics renewable-energy renewables bifacial radiance solar-energy

Last synced: about 18 hours ago
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Repository metadata

Set of tools to calculate degradation responses and degradation related parameters for PV.

README.md

PVDeg: Python Package for Modeling Degradation in Photovoltaic Systems

PVDeg is an open-source Python package for modeling photovoltaic (PV) degradation, developed at the National Renewable Energy Laboratory (NREL) and supported by the Durable Module Materials (DuraMAT) consortium. It provides modular functions, materials databases, and calculation workflows for simulating degradation mechanisms (e.g., LeTID, hydrolysis, UV exposure) using weather data from the National Solar Radiation Database (NSRDB) and the Photovoltaic Geographical Information System (PVGIS). By integrating Monte Carlo uncertainty propagation and geospatial processing, PVDeg enables field-relevant predictions and uncertainty quantification of module reliability and lifetime.

Key Features

  • Core Degradation Functions: Dedicated functions for physical degradation mechanisms including moisture ingress, LeTID, UV exposure, and thermal stress
  • Scenario Class: Simplified workflow interface for complex multi-parameter degradation studies
  • Geospatial Analysis: Large-scale spatial analyses with parallel processing across geographic regions
  • Monte Carlo Framework: Uncertainty quantification through parameter distribution sampling
  • Material Databases: Curated degradation parameters, kinetic coefficients, and material properties
  • Weather Data Integration: Seamless access to NSRDB and PVGIS meteorological data
  • Standards Support: Contributions to IEC TS 63126 and other standardization efforts

Example Applications

PVDeg has been adopted in multiple studies across the PV reliability community:

  • Thermal Stability and IEC TS 63126 Compliance: Calculate effective standoff distances and generate public maps supporting the IEC TS 63126 standard
  • Light and Elevated Temperature Induced Degradation (LeTID): Integrated into international interlaboratory comparison studies and field-aged array analyses
  • Geospatial Performance Modeling: Coupled with GeoGridFusion to streamline weather-data storage and spatial queries for large-scale degradation simulations
  • Agrivoltaics and System-Level Modeling: Combined with PySAM to assess degradation-driven yield losses in dual-use agrivoltaic systems
  • Material-Property Parameterization: Studies of UV-induced polymer degradation and moisture-related failures in encapsulants and backsheets

Documentation

Full documentation is available at ReadTheDocs including:

Installation

PVDeg releases may be installed using pip and conda tools. Compatible with Python 3.10 and above.

Quick Install:

pip install pvdeg

With optional dependencies:

Group Install Command Purpose
sam pip install pvdeg[sam] PySAM support for system modeling
docs pip install pvdeg[docs] Sphinx documentation tools
test pip install pvdeg[test] Testing and validation tools
books pip install pvdeg[books] Jupyter Book publishing
all pip install pvdeg[all] All optional dependencies

Developer Installation:

git clone https://github.com/NREL/PVDegradationTools.git
cd PVDegradationTools
pip install -e .[all]

📖 For detailed installation instructions including conda environments, HPC setup, troubleshooting, and version compatibility, see the Installation Guide.

Tutorials

PVDeg provides comprehensive tutorials organized by topic. Choose your preferred environment:

Jupyter Book (Recommended)

Interactive tutorials with live execution: PVDeg Jupyter Book

  • Click the 🚀 rocket icon to launch notebooks in Google Colab
  • Development Preview: See latest changes at dev-preview

Binder

Run tutorials in your browser without installation: Binder

Local Installation

  1. Install PVDeg (see Installation)

  2. Clone the repository to access tutorial notebooks:

    git clone https://github.com/NREL/PVDegradationTools.git
    cd PVDegradationTools
    
  3. Start Jupyter:

    jupyter notebook
    
  4. Navigate to tutorials organized by category:

    • 01_basics/ - Introduction to PVDeg fundamentals
    • 02_degradation/ - Degradation mechanism modeling
    • 03_monte_carlo/ - Monte Carlo uncertainty analysis
    • 04_geospatial/ - Geospatial and HPC scenarios
    • 05_advanced/ - Advanced topics and API access
    • 10_workshop_demos/ - Workshop demonstrations
    • tools/ - Standalone analysis tools

📖 For more information on running and validating notebooks, see the documentation.

License

BSD 3-clause

Contributing

We welcome contributions to this software! Please see CONTRIBUTING.md for detailed instructions on:

  • Setting up your development environment
  • Installing and using pre-commit hooks
  • Code style guidelines
  • Testing and documentation requirements
  • Contributing to material property and degradation parameter databases
  • Submitting pull requests

Please read the copyright license agreement (cla-1.0.md), with instructions on signing it in sign-CLA.md.

All code, documentation, and discussion contributors are acknowledged for their contributions to the PVDeg project.

Getting support

If you suspect that you may have discovered a bug or if you'd like to
change something about PVDeg, then please make an issue on our
GitHub issues page.

Citing

If you use PVDeg in a published work, please cite both the software and the paper.

Software Citation:

Click the "Cite this repository" button in the right sidebar to get a formatted citation, or visit Zenodo for the DOI corresponding to your specific version:

DOI

On the Zenodo page, use the "Cite as" section in the right sidebar to copy the citation in your preferred format (BibTeX, APA, etc.).

JOSS Paper (In Review):

Daxini, R., Ovaitt, S., Springer, M., Ford, T., & Kempe, M. (2025). PVDeg: a python package for modeling degradation on solar photovoltaic systems. Journal of Open Source Software (In Review).

Acknowledgements

This work was authored by the National Renewable Energy Laboratory, operated by Alliance for Sustainable Energy, LLC, for the U.S. Department of Energy (DOE) under Contract No. DE-AC36-08GO28308. Funding provided as part of the Durable Modules Materials Consortium (DuraMAT), an Energy Materials Network Consortium funded by the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Solar Energy Technologies Office Agreement Number 32509. The research was performed using computational resources sponsored by the Department of Energy's Office of Energy Efficiency and Renewable Energy and located at the National Renewable Energy Laboratory. The views expressed in the article do not necessarily represent the views of the DOE or the U.S. Government. The U.S. Government retains and the publisher, by accepting the article for publication, acknowledges that the U.S. Government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this work, or allow others to do so, for U.S. Government purposes.

NREL Software Record: SWR-20-71 (Holsapple, Derek; Ayala Pelaez, Silvana; Kempe, Michael. "PV Degradation Tools", NREL Github 2020)

Citation (CITATION.cff)

cff-version: 1.2.0
message: "If you use this software, please cite both the software and the paper from preferred-citation."
title: "PVDeg: Photovoltaic Degradation Tools"
abstract: "PVDeg is an open-source Python package for modeling photovoltaic (PV) degradation, developed at the National Renewable Energy Laboratory (NREL) and supported by the Durable Module Materials (DuraMAT) consortium. It provides modular functions, materials databases, and calculation workflows for simulating degradation mechanisms (e.g., LeTID, hydrolysis, UV exposure) using weather data from the National Solar Radiation Database (NSRDB) and the Photovoltaic Geographical Information System (PVGIS). By integrating Monte Carlo uncertainty propagation and geospatial processing, PVDeg enables field-relevant predictions and uncertainty quantification of module reliability and lifetime."
authors:
  - family-names: Springer
    given-names: Martin
    affiliation: National Renewable Energy Laboratory
    orcid: "https://orcid.org/0000-0001-6803-108X"
  - family-names: Brown
    given-names: Matthew
    affiliation: National Renewable Energy Laboratory
    orcid: "https://orcid.org/0000-0002-0988-3431"
  - family-names: Ovaitt
    given-names: Silvana
    affiliation: National Renewable Energy Laboratory
    orcid: "https://orcid.org/0000-0003-0180-728X"
  - family-names: Ford
    given-names: Tobin
    affiliation: National Renewable Energy Laboratory
    orcid: "https://orcid.org/0009-0000-7428-5625"
  - family-names: Daxini
    given-names: Rajiv
    affiliation: National Renewable Energy Laboratory
    orcid: "https://orcid.org/0000-0003-1993-9408"
  - family-names: Holsapple
    given-names: Derek
    affiliation: National Renewable Energy Laboratory
  - family-names: Kempe
    given-names: Michael
    affiliation: National Renewable Energy Laboratory
    orcid: "https://orcid.org/0000-0003-3312-0482"
keywords:
  - photovoltaic
  - solar energy
  - degradation
  - reliability
  - module lifetime
  - LeTID
  - Monte Carlo
  - geospatial analysis
  - NSRDB
  - PVGIS
  - DuraMAT
license: BSD-3-Clause
repository-code: "https://github.com/NREL/PVDegradationTools"
url: "https://pvdegradationtools.readthedocs.io"
type: software
version: 0.7.0
date-released: 2025-12-04

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Last synced: 3 days ago

Total Commits: 2,015
Total Committers: 25
Avg Commits per committer: 80.6
Development Distribution Score (DDS): 0.623

Commits in past year: 1,104
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Avg Commits per committer in past year: 100.364
Development Distribution Score (DDS) in past year: 0.312

Name Email Commits
RDaxini R****i@n****v 760
martin-springer m****s@g****m 352
tobin-ford t****d@n****v 261
Brown m****o@g****m 127
MDKempe 5****e 120
Silvana Ovaitt s****a@n****v 104
Kempe m****e@n****v 90
github-actions[bot] g****] 69
tobin-ford t****d@n****v 40
Matthew Brown m****2@e****v 13
martin-springer m****s@g****m 11
AidanWesley a****y@n****v 10
Joe Karas j****s@g****m 10
Mark Campanelli m****i@g****m 8
Derek M Holsapple d****1@g****m 8
Maxx Millstein m****m@g****m 7
Matt Prilliman 5****n 5
Brown m****2@n****v 5
Matthew Brown m****2@e****v 4
dependabot[bot] 4****] 3
Trenton-Wells t****s@n****v 3
Matthew Brown m****2@e****v 2
Brown M****n@n****v 1
Brown m****2 1
Kevin Anderson k****o@g****m 1

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Last synced: 7 days ago

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Average time to close issues: about 2 months
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Average comments per issue: 0.9
Average comments per pull request: 1.16
Merged pull request: 182
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Past year issues: 48
Past year pull requests: 123
Past year average time to close issues: about 1 month
Past year average time to close pull requests: 12 days
Past year issue authors: 5
Past year pull request authors: 7
Past year average comments per issue: 1.15
Past year average comments per pull request: 1.48
Past year merged pull request: 66
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Package metadata

pypi.org: pvdeg

Pvdeg is a python library that supports the calculation of degradation related parameters for photovoltaic (PV) modules.

  • Homepage: https://github.com/NREL/PVDegradationTools
  • Documentation: https://pvdegradationtools.readthedocs.io/
  • Licenses: BSD-3
  • Latest release: 0.7.0 (published 22 days ago)
  • Last Synced: 2025-12-24T04:07:32.898Z (3 days ago)
  • Versions: 16
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 168 Last month
  • Rankings:
    • Dependent packages count: 7.246%
    • Stargazers count: 17.259%
    • Average: 22.208%
    • Forks count: 23.047%
    • Dependent repos count: 41.279%
  • Maintainers (2)

Dependencies

.github/workflows/pytest.yml actions
  • actions/cache v3 composite
  • actions/checkout v3 composite
  • actions/setup-python v3 composite
requirements.txt pypi
  • matplotlib ==3.2.1
  • numpy ==1.18.4
  • pandas ==1.0.3
  • python-dateutil ==2.8.1
  • pytz ==2020.1
setup.py pypi
  • matplotlib *
  • numpy *
  • pandas *
  • tqdm *
tests/data/meta.json cpan
pvdeg_tutorials/requirements.txt pypi
  • jupyter-book *
  • matplotlib *
  • numpy *

Score: 12.83201107639667