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

• Classical resource assessment step-by-step
  • Introduction
  • The situation
  • Working with WAsP to provide a prediction
  • Import packages
  • Observed wind climate
  • Topography data
    • Creating topography map
    • Displaying terrain and roughness data
    • Output Locations
    • Site effects
  • The generalized wind climate calculation
  • Estimating wind power
  • Estimating wind farm production

Calculate a resource grid

• PyWAsP: 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
• Horizontal transects of power density
• Vertical profile of power density
• Changing properties of the landcover data

Importing a WAsP workspace

• PyWAsP: 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

Losses and uncertainties

• PyWAsP: modeling losses and uncertainty of AEP
  • Introduction
  • The situation
  • Import packages
  • Wind farm production: from predicted wind climate to potential AEP
  • From potential AEP to net AEP (P50) at PCC (Point of Connection)
  • Summary overview of a loss table
  • The total loss and total loss factor
  • Obtaining the P50
  • From net AEP (P50) to AEP Gaussian distribution
  • Summary overview of an uncertainty table
  • The sensitivity factor
  • Total uncertainty factor
  • Obtaining a Px AEP value

Working with polygon and line maps

• Working with polygon and line maps
  • Acquire a CORINE polygon map
  • Visualizing the outputs: Raster
  • Visualizing the outputs: Vector
  • Reprojection and Benchmarking
  • Handling Partial Metadata: Roughness-only and ID-only
  • Topological Edge Case: Polygons with Holes
  • Topological Edge Case: Overlapping Polygons
  • Topological Edge Case: Missing Vertices (Snapping)
  • Disconnected Polygons and Site Effects
  • Using an external roughness length
  • When to use check_errors

Generalized wind climate interpolation

• Generalized wind climate interpolation
  • Prepare Generalized Wind climate cuboid
  • GWC interpolation for the windkit spatial structures
  • Performance
  • Case study using WRF data