Tutorials

Here you can find html-rendered PyWAsP notebooks/tutorials to help you get started with PyWAsP. The notebooks themselves (and associated data) can be found here: https://gitlab.windenergy.dtu.dk/WAsP/pywasp-examples.

Classical WAsP step-by-step

• PyWAsP tutorial 4 PyWAsP - PyWake integration
  • Introduction
  • The situation
  • Working with WAsP to provide a prediction
  • Import packages
  • Observed wind climate
  • Topography data
    • Loading terrain and roughness data
    • Creating topography map
    • Output Locations
    • Site effects
  • The generalized wind climate calculation
  • Estimating wind power
  • Estimating wind farm production

Calculate a resource grid

• PyWAsP tutorial 1 From observed wind climate to resource map
  • Introduction
  • Import packages
  • Observed wind climate
  • Topography data
    • Terrain data (SRTM)
    • Roughness data (CORINE LandCover)
  • SITE EFFECTS
    • Create TopographyMap object
    • Roughness Rose
    • Output Locations
    • Site Effects Calculation
      • Plotting z0meso
      • Plotting Roughness Change Speedups
  • Generalization and downscaling with PyWAsP
  • Predicted Wind Climates

Experiment with the response of WAsP’s Roughness Change model

• Experiment with response of WAsP’s Roughness Change modelling
  • Create single-contour map of roughness change
  • Setup the test cases
  • Create a column of “speedups”
  • Examine the speedup results

Evaluating roughness maps at Østerild

• Evaluating roughness maps at Østerild
  • Reading Østerild wind data
• Preparing map files
• Using landcover (LC) maps
• Roughness and landcover around masts
• Exploring roughness around a point: the roughness rose
• Comparison of observed and modelled wind, per roughness maps
• Vertical profile of power density
• Changing properties of the landcover data

Importing a WAsP workspace

• PyWAsP tutorial 5 Importing objects from a WAsP workspace (WWH file)
  • Importing an OWC from the workspace
  • Importing a GWC from the workspace
  • Importing vector maps from the WAsP workspace
    • (re-)calculating predicted wind climates
      • creating a grid of locations
      • calculating predicted wind climates over the grid
      • Get turbine hub positions (x,y,z) from the workspace, and predict wind climates for them