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 observation renewable-energy renewables animals virtual optimize transforms measur compose

Last synced: about 9 hours ago
JSON representation

Repository metadata

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

Host: GitHub
URL: https://github.com/nrel/pvdegradationtools
Owner: NREL
License: other
Created: 2020-06-03T20:26:52.000Z (almost 5 years ago)
Default Branch: main
Last Pushed: 2025-04-16T14:58:29.000Z (11 days ago)
Last Synced: 2025-04-17T09:19:01.274Z (10 days ago)
Topics: degradation, duramat, photovoltaic-systems, pv-modules, python, reliability
Language: Jupyter Notebook
Homepage: https://pvdegradationtools.readthedocs.io/
Size: 102 MB
Stars: 35
Watchers: 5
Forks: 18
Open Issues: 34
Releases: 16
Metadata Files:
- Readme: README.md
- License: LICENSE.md

PV Degradation Tools (pvdeg)

This repository contains functions for calculating degradation of photovoltaic modules. For example, functions to calculate front and rear relative Humidity, as well as Acceleration Factors. A degradation calculation function is also being developed, considering humidity and spectral irradiances models.

Tutorials

Jupyter Book

For in depth Tutorials you can run online, see our jupyter-book

Clicking on the rocket-icon on the top allows you to launch the journals on Google Colaboratory for interactive mode.
Just uncomment the first line pip install ... to install the environment on each journal if you follow this mode.

Binder

To run these tutorials in Binder, you can click here:

It takes a minute to load the environment.

Locally

You can also run the tutorial locally in a virtual environment, i.e., venv or
miniconda.

Create and activate a new environment, e.g., on Mac/Linux terminal with venv:

python -m venv pvdeg
. pvdeg/bin/activate

or with conda:

conda create -n pvdeg
conda activate pvdeg

Install pvdeg into the new environment with pip:
```
python -m pip install pvdeg
```
Start a Jupyter session:
```
jupyter notebook
```
Use the file explorer in Jupyter lab to browse to tutorials
and start the first Tutorial.

Documentation

Documentation is available in ReadTheDocs where you can find more details on the API functions.

Installation

Relative Humidity and Acceleration Factors for Solar Modules releases may be installed using the pip and conda tools. Compatible with Python 3.5 and above.

Install with:

pip install pvdeg

For developer installation, clone the repository, navigate to the folder location and install as:

pip install -e .[all]

License

BSD 3-clause

Contributing

We welcome contributiosn to this software, but please read the copyright license agreement (cla-1.0.md), with instructions on signing it in sign-CLA.md. For questions, email us.

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 this functions in a published work, please cite:

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

And/or the specific release from Zenodo:

Martin Springer, Matthew Brown, Silvana Ovaitt, Tobin Ford, Joseph Karas, Mark Campanelli, Derek M Holsapple, Kevin Anderson, Michael Kempe. (2024). NREL/PVDegradationTools: 0.3.2 (0.3.2). Zenodo. https://doi.org/10.5281/zenodo.11123249

Owner metadata

Name: National Renewable Energy Laboratory
Login: NREL
Email:
Kind: organization
Description:
Website: http://www.nrel.gov
Location: Golden, CO
Twitter:
Company:
Icon url: https://avatars.githubusercontent.com/u/1906800?v=4
Repositories: 599
Last ynced at: 2024-12-18T09:41:07.898Z
Profile URL: https://github.com/NREL

GitHub Events

Total

Create event: 19
Release event: 1
Issues event: 22
Watch event: 9
Delete event: 19
Issue comment event: 27
Push event: 89
Pull request review comment event: 27
Pull request event: 34
Pull request review event: 30
Fork event: 11

Last Year

Create event: 19
Release event: 1
Issues event: 22
Watch event: 9
Delete event: 19
Issue comment event: 27
Push event: 89
Pull request review comment event: 27
Pull request event: 34
Pull request review event: 30
Fork event: 11

Committers metadata

Last synced: 6 days ago

Total Commits: 922
Total Committers: 21
Avg Commits per committer: 43.905
Development Distribution Score (DDS): 0.781

Commits in past year: 325
Committers in past year: 8
Avg Commits per committer in past year: 40.625
Development Distribution Score (DDS) in past year: 0.529

Name	Email	Commits
tobin-ford	t**d@n**v	202
martin-springer	m**s@g**m	183
Brown	m**o@g**m	127
MDKempe	5****e	104
Silvana Ovaitt	s**a@n**v	104
github-actions[bot]	g****]	67
tobin-ford	t**d@n**v	40
Kempe	m**e@n**v	19
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
Derek M Holsapple	d**1@g**m	8
Mark Campanelli	m**i@g**m	8
Brown	m**2@n**v	5
Matthew Brown	m**2@e**v	4
dependabot[bot]	4****]	2
Matthew Brown	m**2@e**v	2
Brown	m****2	1
Brown	M**n@n**v	1
Kevin Anderson	k**o@g**m	1

Committer domains:

Issue and Pull Request metadata

Last synced: 1 day ago

Total issues: 71
Total pull requests: 115
Average time to close issues: about 2 months
Average time to close pull requests: 12 days
Total issue authors: 6
Total pull request authors: 10
Average comments per issue: 0.66
Average comments per pull request: 0.87
Merged pull request: 94
Bot issues: 0
Bot pull requests: 3

Past year issues: 34
Past year pull requests: 52
Past year average time to close issues: 22 days
Past year average time to close pull requests: 14 days
Past year issue authors: 3
Past year pull request authors: 5
Past year average comments per issue: 0.44
Past year average comments per pull request: 1.21
Past year merged pull request: 41
Past year bot issues: 0
Past year bot pull requests: 2

More stats: https://issues.ecosyste.ms/repositories/lookup?url=https://github.com/nrel/pvdegradationtools

Top Issue Authors

tobin-ford (34)
MDKempe (25)
martin-springer (7)
shirubana (2)
saikatghosh90 (2)
markcampanelli (1)

Top Pull Request Authors

martin-springer (42)
tobin-ford (34)
MDKempe (18)
jfkaras (7)
shirubana (4)
dependabot[bot] (3)
AidanWesley (3)
mcbrown042 (2)
markcampanelli (1)
kandersolar (1)

Top Issue Labels

enhancement (8)
documentation (3)
File Organization (2)
Clarity for users (2)
good first issue (2)

Top Pull Request Labels

dependencies (4)
python (2)
documentation (2)
enhancement (1)

Package metadata

Total packages: 2
Total downloads:
- pypi: 472 last-month
Total dependent packages: 0 (may contain duplicates)
Total dependent repositories: 0 (may contain duplicates)
Total versions: 14
Total maintainers: 3

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: 0.5.0 (published 2 months ago)
Last Synced: 2025-04-26T05:31:36.194Z (1 day ago)
Versions: 13
Dependent Packages: 0
Dependent Repositories: 0
Downloads: 405 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)
- shirubana
- martin-springer

pypi.org: geogridfusion

Homepage:
Documentation: https://geogridfusion.readthedocs.io/
Licenses: BSD-3
Latest release: 0.0.0 (published 2 months ago)
Last Synced: 2025-04-26T05:31:35.866Z (1 day ago)
Versions: 1
Dependent Packages: 0
Dependent Repositories: 0
Downloads: 67 Last month
Rankings:
- Dependent packages count: 9.63%
- Average: 31.928%
- Dependent repos count: 54.226%
Maintainers (1)
- tobin-ford

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: 13.441943746355324

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