pvdegradationtools

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

https://github.com/nrel/pvdegradationtools

Science Score: 49.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
    Found 5 DOI reference(s) in README
  • Academic publication links
    Links to: zenodo.org
  • Committers with academic emails
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (16.7%) to scientific vocabulary

Keywords

degradation duramat photovoltaic-systems pv-modules python reliability

Keywords from Contributors

photovoltaics renewables renewable-energy optim sequences interactive annotation charts packaging projection
Last synced: 6 months ago · JSON representation

Repository

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

Basic Info
Statistics
  • Stars: 36
  • Watchers: 4
  • Forks: 20
  • Open Issues: 47
  • Releases: 16
Topics
degradation duramat photovoltaic-systems pv-modules python reliability
Created over 5 years ago · Last pushed 6 months ago
Metadata Files
Readme License

README.md

License license
Publications DOI
Documentation Documentation Status
Build status GitHub Actions Testing Status

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 Jupyter Book Badge

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: Binder 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.

  1. 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

  2. Install pvdeg into the new environment with pip: python -m pip install pvdeg

  3. Start a Jupyter session:

jupyter notebook

  1. 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

  • Name: National Renewable Energy Laboratory
  • Login: NREL
  • Kind: organization
  • Location: Golden, CO

GitHub Events

Total
  • Create event: 49
  • Release event: 1
  • Issues event: 45
  • Watch event: 11
  • Delete event: 44
  • Member event: 2
  • Issue comment event: 121
  • Push event: 276
  • Pull request review comment event: 62
  • Pull request event: 83
  • Pull request review event: 86
  • Fork event: 13
Last Year
  • Create event: 49
  • Release event: 1
  • Issues event: 45
  • Watch event: 11
  • Delete event: 44
  • Member event: 2
  • Issue comment event: 121
  • Push event: 276
  • Pull request review comment event: 62
  • Pull request event: 83
  • Pull request review event: 86
  • Fork event: 13

Committers

Last synced: 7 months ago

All Time
  • Total Commits: 922
  • Total Committers: 21
  • Avg Commits per committer: 43.905
  • Development Distribution Score (DDS): 0.781
Past Year
  • Commits: 325
  • Committers: 8
  • Avg Commits per committer: 40.625
  • Development Distribution Score (DDS): 0.529
Top Committers
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 (Top 20 + Academic)

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 72
  • Total pull requests: 218
  • Average time to close issues: about 1 month
  • Average time to close pull requests: 12 days
  • Total issue authors: 8
  • Total pull request authors: 12
  • Average comments per issue: 0.74
  • Average comments per pull request: 1.12
  • Merged pull requests: 162
  • Bot issues: 0
  • Bot pull requests: 5
Past Year
  • Issues: 35
  • Pull requests: 104
  • Average time to close issues: 26 days
  • Average time to close pull requests: 11 days
  • Issue authors: 4
  • Pull request authors: 7
  • Average comments per issue: 0.8
  • Average comments per pull request: 1.38
  • Merged pull requests: 63
  • Bot issues: 0
  • Bot pull requests: 4
Top Authors
Issue Authors
  • tobin-ford (27)
  • MDKempe (17)
  • RDaxini (14)
  • martin-springer (8)
  • shirubana (2)
  • saikatghosh90 (2)
  • markcampanelli (1)
  • alecote (1)
Pull Request Authors
  • martin-springer (62)
  • tobin-ford (60)
  • RDaxini (39)
  • MDKempe (33)
  • dependabot[bot] (5)
  • jfkaras (5)
  • AidanWesley (4)
  • shirubana (4)
  • markcampanelli (2)
  • mcbrown042 (2)
  • maxx-mill (1)
  • kandersolar (1)
Top Labels
Issue Labels
enhancement (9) Clarity for users (6) documentation (4) bug (3) python (3) help wanted (3) File Organization (2) api (2) deprecation (2) development_workflow (1) good first issue (1)
Pull Request Labels
enhancement (14) python (10) documentation (9) dependencies (6) api (5) Clarity for users (1) development_workflow (1) deprecation (1) release (1) bug (1)

Packages

  • Total packages: 1
  • Total downloads:
    • pypi 38 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 13
  • Total maintainers: 2
pypi.org: pvdeg

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

  • Versions: 13
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 38 Last month
Rankings
Dependent packages count: 7.2%
Stargazers count: 17.3%
Average: 22.2%
Forks count: 23.0%
Dependent repos count: 41.3%
Maintainers (2)
Last synced: 6 months ago

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 *