WindKit provides core functionalities for working with wind resource data
Project description
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 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.values:.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, .lib, .tab, .rsf, .wrg)
- Map I/O - Read/write elevation, roughness, and landcover maps (raster and vector formats)
- WAsP Integration - Read WAsP Workspace files and WAsP Engineering project files
- Spatial Processing - Clip, reproject, and interpolate spatial data with full CRS support
- Wind Statistics - Calculate mean wind speed, power density, Weibull parameters, and more
- 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.
Project details
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