We are happy to announce our new version 0.2.1 of Atlite.
Atlite is a light-weight python package for converting reanalysis weather datasets into time series and potentials for energy systems, such as generation data for solar PV, solar thermal collectors, wind turbines, run-of-river power plants, hydro-electric dams, heating demand degree days and heat pump coefficients of performance. It uses reanalysis weather data and computes the dynamic and/or static capacity factors at all sites. We designed the package such that scaling to large areas and time-spans still runs fast, thanks to the nice packages xarray and dask. The newest version also provides fast routines for land-use calculations, i.e. exclusion of areas like natural reserves, industrial areas etc. as provided by the Corine Land Cover database.
We wrote a detailed documentation with multiple usage examples. The source code can be found at https://github.com/PyPSA/atlite.
You can install the package via pypi (`pip install atlite`) or conda (`conda install -c conda-forge atlite`).
If you're already using atlite and upgrading be mindful of the breaking changes introduced with the new version (see the release notes for details).
So far the package may be used with ERA5 reanalysis data (automatic data retrieval provided) and SARAH (manual download required).
We are happy to receive feedback, or even better to get contributions to the code (raise an issue or draft a pull request in the repo). There will be a paper soon that you can cite if you use
(On behalf of the developers)
Thanks to all external contributors.