solar-and-wind-potentials
Estimation of solar and wind power generation potentials in Europe.
https://github.com/calliope-project/solar-and-wind-potentials
Science Score: 41.0%
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○codemeta.json file
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○.zenodo.json file
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Found 4 DOI reference(s) in README -
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2 of 2 committers (100.0%) from academic institutions -
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Low similarity (15.3%) to scientific vocabulary
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Repository
Estimation of solar and wind power generation potentials in Europe.
Basic Info
Statistics
- Stars: 10
- Watchers: 3
- Forks: 2
- Open Issues: 12
- Releases: 0
Topics
Metadata Files
README.md
Potentials of solar and wind power
This Snakemake workflow allows to estimate potentials of solar and wind power. We applied it in a former publication in which we estimated potentials for Europe as a whole, as well as all countries, sub-national regions, and municipalities in Europe (see below).
However, it can be used to generate potentials for different areas by modifying the configuration files (and likely some of the rules as well). If you want to use it for different areas, consider the workflow as a starting point for your own analysis, not as a generic library that will work out of the box.
Documentation and citation
The approach is described in the following publication. If you use data or the method, please cite this publication.
Tröndle, T., Pfenninger, S., Lilliestam, J., 2019. Home-made or imported: on the possibility for renewable electricity autarky on all scales in Europe. Energy Strategy Reviews 26. https://doi.org/10.1016/j.esr.2019.100388
Getting ready
Installation
The following dependencies are needed to set up an environment in which the analysis can be run and the paper be build:
When these dependencies are installed, you can create a conda environment from within you can run the analysis:
conda env create -f environment.yaml
Don't forget to activate the environment. To see what you can do now, run:
snakemake --list
Data to be retrieved manually
Whenever possible, data is downloaded automatically. As this is not always possible, you will need to retrieve the following data sets manually:
- European Settlement Map 2012, Release 2017, 100m, to be placed at
./data/esm-100m-2017/ - World Exclusive Economic Zones v10, to be placed in
./data/World_EEZ_v10_20180221 - capacity factors from renewable.ninja, to be placed in
./data/capacityfactors/{technology}.ncfor technology in "wind-onshore", "wind-offshore", "rooftop-pv", "open-field-pv"(to run simulations, seeManual stepsbelow)
Run the analysis
snakemake --use-conda
This will run all analysis steps to estimate potentials.
You can also run certain parts only by using other snakemake rules; to get a list of all rules run snakemake --list.
To generate a PDF of the dependency graph of all steps, run:
snakemake --rulegraph | dot -Tpdf > dag.pdf
(needs dot: conda install graphviz).
Run on Euler cluster
To run on Euler, use the following command:
snakemake --use-conda --profile config/euler
If you want to run on another cluster, read snakemake's documentation on cluster execution and take config/euler as a starting point.
Manual steps
At the moment, there is one manual step involved: running renewables.ninja simulations of wind and solar electricity. It is added to the automatic workflow as input data. Should you want to change the simulations, because you want to change parameters of the simulation (see parameters.ninja in the config), you can do that in three steps:
1) Create input files by first changing the config, then running snakemake -s rules/ninja-input.smk.
2) Run the simulations on renewables.ninja.
3) Update the data in data/capacityfactors/{technology}.
Run the tests
snakemake --use-conda test
Repo structure
src: contains the Python source codetests: contains the test codeconfig: configurations used in the studyrules: additional Snakemake rules and workflowsdata: place for raw data, whether retrieved manually and automaticallybuild: will contain all results (does not exist initially)
License
The code in this repo is MIT licensed, see ./LICENSE.md.
Owner
- Name: Calliope
- Login: calliope-project
- Kind: organization
- Website: https://www.callio.pe/
- Repositories: 14
- Profile: https://github.com/calliope-project
A multi-scale energy systems modelling framework
Citation (CITATION.md)
If you use this code or data in an academic publication, please cite the following article: Tröndle, T., Pfenninger, S., Lilliestam, J., 2019. Home-made or imported: on the possibility for renewable electricity autarky on all scales in Europe. Energy Strategy Reviews 26. https://doi.org/10.1016/j.esr.2019.100388
GitHub Events
Total
- Issues event: 1
- Watch event: 1
- Fork event: 1
Last Year
- Issues event: 1
- Watch event: 1
- Fork event: 1
Committers
Last synced: about 2 years ago
Top Committers
| Name | Commits | |
|---|---|---|
| Tim Tröndle | t****e@u****h | 380 |
| brynpickering | b****g@u****h | 35 |
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: about 2 years ago
All Time
- Total issues: 10
- Total pull requests: 15
- Average time to close issues: 9 days
- Average time to close pull requests: about 1 month
- Total issue authors: 2
- Total pull request authors: 2
- Average comments per issue: 3.7
- Average comments per pull request: 3.73
- Merged pull requests: 9
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 0
- Pull requests: 0
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Issue authors: 0
- Pull request authors: 0
- Average comments per issue: 0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- brynpickering (7)
- timtroendle (3)
- FLomb (1)
Pull Request Authors
- brynpickering (14)
- timtroendle (1)
Top Labels
Issue Labels
Pull Request Labels
Dependencies
- pycountry 20.7.3.*
- python 3.6.*
- snakemake-minimal 5.4.*
- geopandas *
- numpy *
- pandas *
- pycountry *
- pyproj *
- shapely *