gsee
Global Solar Energy Estimator.
https://github.com/renewables-ninja/gsee
Category: Renewable Energy
Sub Category: Photovoltaics and Solar Energy
Keywords
electricity energy irradiance ninja pandas photovoltaic pv solar
Last synced: about 18 hours ago
JSON representation
Repository metadata
GSEE: Global Solar Energy Estimator
- Host: GitHub
- URL: https://github.com/renewables-ninja/gsee
- Owner: renewables-ninja
- License: bsd-3-clause
- Created: 2016-09-01T11:41:04.000Z (over 8 years ago)
- Default Branch: main
- Last Pushed: 2025-04-22T08:22:57.000Z (5 days ago)
- Last Synced: 2025-04-25T12:45:37.519Z (2 days ago)
- Topics: electricity, energy, irradiance, ninja, pandas, photovoltaic, pv, solar
- Language: Python
- Homepage: https://gsee.readthedocs.io/
- Size: 389 KB
- Stars: 130
- Watchers: 13
- Forks: 47
- Open Issues: 8
- Releases: 0
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- License: LICENSE
- Citation: CITATION
- Authors: AUTHORS
README.md
GSEE: Global Solar Energy Estimator
GSEE
is a solar energy simulation library designed for rapid calculations and ease of use. Renewables.ninja uses GSEE
.
The development of GSEE
predates the existence of pvlib-python
but builds on its functionality as of v0.4.0. Use GSEE
if you want fast simulations with sensible defaults and solar energy technologies other than PV, and pvlib-python
if you need control over the nuts and bolts of simulating PV systems.
Installation
GSEE
requires Python 3. The recommended way to install is through the Anaconda Python distribution and conda-forge
:
conda install -c conda-forge gsee
You can also install with pip install gsee
, but if you do so, and do not already have numpy
installed, you will get a compiler error when pip tries to build to climatedata_interface
Cython extension.
Documentation
See the documentation for more information on GSEE
's functionality and for examples.
Credits and contact
Contact Stefan Pfenninger for questions about GSEE
. GSEE
is also a component of the Renewables.ninja project, developed by Stefan Pfenninger and Iain Staffell. Use the contact page there if you want more information about Renewables.ninja.
Citation
If you use GSEE
or code derived from it in academic work, please cite:
Stefan Pfenninger and Iain Staffell (2016). Long-term patterns of European PV output using 30 years of validated hourly reanalysis and satellite data. Energy 114, pp. 1251-1265. doi: 10.1016/j.energy.2016.08.060
License
BSD-3-Clause
Citation (CITATION)
To reference GSEE in publications, please cite the following paper: Stefan Pfenninger and Iain Staffell (2016). Long-term patterns of European PV output using 30 years of validated hourly reanalysis and satellite data. Energy 114, pp. 1251-1265. https://dx.doi.org/10.1016/j.energy.2016.08.060
Owner metadata
- Name: Renewables.ninja
- Login: renewables-ninja
- Email:
- Kind: organization
- Description: Renewable energy simulations, ninja style.
- Website: https://www.renewables.ninja/
- Location:
- Twitter:
- Company:
- Icon url: https://avatars.githubusercontent.com/u/11838260?v=4
- Repositories: 5
- Last ynced at: 2024-03-27T12:47:56.659Z
- Profile URL: https://github.com/renewables-ninja
GitHub Events
Total
- Issues event: 1
- Watch event: 7
- Push event: 3
- Fork event: 6
- Create event: 1
Last Year
- Issues event: 1
- Watch event: 7
- Push event: 3
- Fork event: 6
- Create event: 1
Committers metadata
Last synced: 6 days ago
Total Commits: 64
Total Committers: 3
Avg Commits per committer: 21.333
Development Distribution Score (DDS): 0.063
Commits in past year: 8
Committers in past year: 1
Avg Commits per committer in past year: 8.0
Development Distribution Score (DDS) in past year: 0.0
Name | Commits | |
---|---|---|
Stefan Pfenninger | s****n@p****g | 60 |
muelljoh | 4****h | 3 |
tsaoyu | t****u@t****m | 1 |
Committer domains:
- tsaoyu.com: 1
- pfenninger.org: 1
Issue and Pull Request metadata
Last synced: 2 days ago
Total issues: 7
Total pull requests: 11
Average time to close issues: 2 months
Average time to close pull requests: about 1 month
Total issue authors: 7
Total pull request authors: 6
Average comments per issue: 0.43
Average comments per pull request: 0.73
Merged pull request: 4
Bot issues: 0
Bot pull requests: 1
Past year issues: 1
Past year pull requests: 0
Past year average time to close issues: N/A
Past year average time to close pull requests: N/A
Past year issue authors: 1
Past year pull request authors: 0
Past year average comments per issue: 0.0
Past year average comments per pull request: 0
Past year merged pull request: 0
Past year bot issues: 0
Past year bot pull requests: 0
Top Issue Authors
- phumthep (1)
- ChanceQZ (1)
- moijn001 (1)
- mfleschutz (1)
- nurisensoy (1)
- jwohland (1)
- rabwent11 (1)
Top Pull Request Authors
- muelljoh (5)
- tsaoyu (2)
- knyghty (1)
- dependabot[bot] (1)
- arjunane (1)
- jwohland (1)
Top Issue Labels
Top Pull Request Labels
- dependencies (1)
Package metadata
- Total packages: 2
-
Total downloads:
- pypi: 328 last-month
- Total dependent packages: 0 (may contain duplicates)
- Total dependent repositories: 1 (may contain duplicates)
- Total versions: 5
- Total maintainers: 1
pypi.org: gsee
GSEE: Global Solar Energy Estimator
- Homepage: https://github.com/renewables-ninja/gsee
- Documentation: https://gsee.readthedocs.io/
- Licenses: bsd-3-clause
- Latest release: 0.3.1 (published almost 6 years ago)
- Last Synced: 2025-04-25T12:30:27.735Z (2 days ago)
- Versions: 4
- Dependent Packages: 0
- Dependent Repositories: 1
- Downloads: 328 Last month
-
Rankings:
- Forks count: 6.389%
- Stargazers count: 7.07%
- Dependent packages count: 7.373%
- Average: 11.177%
- Downloads: 12.82%
- Dependent repos count: 22.233%
- Maintainers (1)
conda-forge.org: gsee
GSEE is a solar energy simulation library designed for rapid calculations and ease of use.
- Homepage: https://github.com/renewables-ninja/gsee
- Licenses: BSD-3-Clause
- Latest release: 0.3.1 (published over 5 years ago)
- Last Synced: 2025-04-02T02:12:32.185Z (25 days ago)
- Versions: 1
- Dependent Packages: 0
- Dependent Repositories: 0
-
Rankings:
- Forks count: 26.414%
- Stargazers count: 31.305%
- Dependent repos count: 34.025%
- Average: 35.73%
- Dependent packages count: 51.175%
Dependencies
- mkautodoc *
- mkdocs ==1.0.4
- mkdocs-material ==4.6.0
- mkdocs-minify-plugin *
- pymdown-extensions ==6.2
- pandas ==1.4.3
- pvlib >=0.10.4,<0.11
- pyephem >=9.99,<10
- xarray ==2022.6
Score: 11.82495862828584