PyWAsP#

Wind resource assessment and energy yield prediction in Python

PyWAsP provides a Python API for the WAsP flow model - the industry-standard software for wind resource assessment and siting of wind turbines developed at DTU Wind Energy.

Key Features#

Terrain Effects

Estimate the effects of terrain on the flow, including speed-up, turning, and directional effects using the WAsP IBZ model.

Wind Resource Assessment

Extrapolate known wind climates to new locations using the generalization and downscaling routines from WAsP.

AEP Estimation

Calculate annual energy production (AEP) of wind turbines, accounting for wakes (via PyWake), losses, and uncertainty.

Choose Your Path#

New to PyWAsP?

Start here if you’re new to PyWAsP. Learn the basics of installation, key concepts, and run your first calculation.

Recommended for beginners

Getting Started
Coming from WAsP GUI?

Already familiar with WAsP? Learn how PyWAsP concepts map to what you already know from the WAsP graphical interface.

For WAsP users

From WAsP to PyWAsP
Python Developer?

Experienced Python developer? Jump straight into the data structures and learn about xarray/WindKit integration.

For developers

Working With Xarray and WindKit
Learn WindKit

WindKit is the foundation of PyWAsP. Master its data structures, I/O functions, and spatial operations to work effectively with PyWAsP.

Essential foundation

https://docs.wasp.dk/windkit
Hands-on Tutorials

Follow step-by-step tutorials covering complete PyWAsP workflows, from basic WRA to advanced topics.

Guided learning

Tutorials

References#

[1]

Rogier Floors, Peter Enevoldsen, Neil Davis, Johan Arnqvist, and Ebba Dellwik. From lidar scans to roughness maps for wind resource modelling in forested areas. Wind Energy Sci., 3(1):353–370, jun 2018. URL: https://www.wind-energ-sci.net/3/353/2018/, doi:10.5194/wes-3-353-2018.

[2]

Rogier Floors and Morten Nielsen. Estimating Air Density Using Observations and Re-Analysis Outputs for Wind Energy Purposes. Energies, 12(11):2038, may 2019. URL: https://www.mdpi.com/1996-1073/12/11/2038, doi:10.3390/en12112038.

[3]

Rogier Ralph Floors, Ib Troen, and Mark C Kelly. Implementation of large-scale average geostrophic wind shear in WAsP12.1. Technical Report, E-0169, DTU Wind Energy, Roskilde, Denmark, 2018. URL: https://orbit.dtu.dk/en/publications/implementation-of-large-scale-average-geostrophic-wind-shear-in-w.

[4]

Niels G. Mortensen, Morten Nielsen, and Hans" Ejsing Jørgensen. Offshore creyap part 2 final results. In EWEA Technology Workshop. Helsinki, Finland, June 2015. URL: https://orbit.dtu.dk/en/publications/offshore-creyap-part-2-final-results.

[5]

M. R. Raupach. Simplified expressions for vegetation roughness length and zero-plane displacement as functions of canopy height and area index. Boundary-Layer Meteorol., 71(1-2):211–216, oct 1994. doi:10.1007/BF00709229.