CLEO is a xarray-based Python library for converting data from the Global Wind Atlas to wind resource assessment. CLEO can produce data such as
in the high, native spatial resolution of the Global Wind Atlas. CLEO also supports some geospatial operations such as reprojecting to EPSG-coordinate reference systems and clipping to geopandas geometries.
At the moment, CLEO is usable only from its GitHub repo.
pip install git+https://github.com/sebwehrle/cleo.git
In a later release we aim to improve installation.
CLEO's functions are documented in-line. We are working towards an improved documentation.
To get started, initialize a Atlas
-class object via
from cleo.classes import Atlas
atlas = Atlas("path/to/base/dir", "XYZ", "epsg:1234")
where XYZ
is a 3-digit ISO country code as used by the GWA API and epsg:1234
specifies a coordinate reference system.
Upon initialization, the class will download data for XYZ
.
The class wraps two xarray.Dataset
s, one for wind resources and one for further spatial characteristics.
The corresponding data is accessible through atlas.wind.data
and atlas.landscape.data
, respectively
An Atlas
-object has the following properties:
path
: the atlas base-pathcountry
: 3-digit ISO code of the country to assessregion
: (optional) the Latin name of a EU NUTS-region within a country
. crs
: coordinate reference system of the WindResourceAtlas
' spatial data.wind_turbines
: list of wind turbine models to process. Must be set by the user to allow wind resource assessment.
Further turbines can be added as a list. Additional turbines require a data file in the /resources
-directory.The WindAtlas
-subclass provides several methods, including:
compute_wind_shear()
: computes wind shear coefficientcompute_air_density_correction()
: computes air density correction factor alphacompute_weibull_pdf()
: computes a Weibull pdf of wind speedssimulate_capacity_factors()
: simulate capacity factors of the wind turbines in atlas.wind_turbine
.
Before simulating capacity factors, properly named (manufacturer.model.power.yml
) yaml
-file in /resources
for all
wind turbines in atlas.wind_turbine
must be loaded with atlas.load_powercurves()
. compute_lcoe()
: calculates LCOE for each pixel and each wind turbine in atlas.wind_turbines
based on the
cost-assumptions in /resources/cost_assumptions.yml
. By default, overnight cost of wind turbines are estimated with
the Rinne et al. cost model, which is implemented in turbine_overnight_cost()
in cleo.assess
.Copyright (c) 2024 Sebastian Wehrle
MIT License