Atlite: Convert weather data to energy systems data
Atlite is a free software, xarray-based Python library for converting weather data (such as wind speeds, solar radiation, temperature and runoff) into power systems data (such as wind power, solar power, hydro power and heating demand time series). It is designed to work with big datasets as is common with weather reanalysis, while maintaining low computational requirements.
The spatial and time resolution of the obtainable power time series depends on the resolutions of the original weather reanalysis dataset. E.g. using our recommended dataset ERA5 we can obtain time-series with hourly resolution on a 30 km x 30 km grid.
Atlite is currently maintained by volunteers from different institutions with no dedicated funding for developing this package.
Atlite was initially developed by the Renewable Energy Group at FIAS to carry out simulations for the CoNDyNet project, financed by the German Federal Ministry for Education and Research (BMBF) as part of the Stromnetze Research Initiative.
Atlite was originally conceived as a light-weight version of the Aarhus University RE Atlas (original publication doi:10.1016/j.energy.2015.09.071). It has since been extended to use weather datasets simulated with projected climate change and to compute other time series, such as hydro power, solar thermal collectors and heating demand.
Atlite is released and licensed under the GPLv3.