CLEO

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

wind shear coefficient
air density correction
mean wind speed at various heights
capacity factor of wind turbines at their hub height
levelized cost of electricity (LCOE) of wind turbines with a given power curve

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.

Installation

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.

Documentation

CLEO's functions are documented in-line. We are working towards an improved documentation.

How to get started

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.Datasets, one for wind resources and one for further spatial characteristics. The corresponding data is accessible through atlas.wind.data and atlas.landscape.data, respectively

Properties

An Atlas-object has the following properties:

path: the atlas base-path
country: 3-digit ISO code of the country to assess
region: (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.

Methods

The WindAtlas-subclass provides several methods, including:

compute_wind_shear(): computes wind shear coefficient
compute_air_density_correction(): computes air density correction factor alpha
compute_weibull_pdf(): computes a Weibull pdf of wind speeds
simulate_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.

Author and Copyright

License

MIT License