WindKit

WindKit provides core functionalities for working with wind resource data, built on top of xarray and geopandas.

Installation

pip:

pip install windkit

conda:

conda install -c https://conda.windenergy.dtu.dk/channel/open/ -c conda-forge windkit

Quick Start

import windkit as wk

# Read a binned wind climate
bwc = wk.read_bwc("hovsore.tab")

# Calculate mean wind speed
mean_ws = wk.mean_wind_speed(bwc)
print(f"Mean wind speed: {mean_ws.item():.2f} m/s")

# Fit Weibull distribution and convert to Weibull wind climate
wwc = wk.weibull_fit(bwc)

Features

• Wind Climate I/O - Read/write binned, Weibull, generalized, and time-series wind climates (NetCDF, .tab, .owc, .lib, .gwc, .rsf, .wrg, windIO YAML)
• Map I/O - Read/write elevation, roughness, and landcover maps (raster and vector formats, including WAsP .map)
• WAsP Integration - Read the inputs and results of WAsP workspaces (.wwh) and WAsP Engineering project files, with low-level readers for the WAsP file formats
• Spatial Processing - Clip, reproject, and interpolate spatial data with full CRS support
• Wind Statistics - Calculate mean wind speed, power density, Weibull parameters, and more
• Long-Term Correction - Measure-correlate-predict (MCP) methods for time series
• Losses and Uncertainty - Net AEP and exceedance values (P90) from loss and uncertainty tables
• Plotting - Interactive plots with Plotly, static plots with Matplotlib
• Remote Data Access - Download ERA5 reanalysis data and satellite-derived maps

Documentation

Full documentation: docs.wasp.dk/windkit

Community forum: WAsP Python tools

Contributing

See CONTRIBUTING.md for development setup and guidelines.

License

BSD-3-Clause - see LICENSE for details.