PyWake#

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Examples

PyWake is an open-source wind farm simulation tool developed by DTU Wind Energy. It provides fast and flexible wake modeling capabilities for wind farm flow and power estimation, supporting both time series and probabilistic (Weibull) wind resource inputs.

Configuration Options#

PyWake-specific options are configured in the analysis.yaml file:

Wake Deficit Model:

wind_deficit_model:
  name: Bastankhah2014  # Options: Jensen, Bastankhah2014, SuperGaussian, TurbOPark, FUGA
  wake_expansion_coefficient:
    k_a: 0.0            # TI-dependent coefficient: k = k_a * TI + k_b
    k_b: 0.04           # Base wake expansion
    free_stream_ti: false
  ceps: 0.2             # Epsilon parameter (Bastankhah models)
  use_effective_ws: true

Deflection Model:

deflection_model:
  name: Jimenez         # Options: None, Jimenez
  beta: 0.1             # Jimenez deflection coefficient

Turbulence Model:

turbulence_model:
  name: CrespoHernandez  # Options: None, STF2005, STF2017, CrespoHernandez
  c1: 1.0                # STF model coefficients (if applicable)
  c2: 1.0

Superposition Model:

superposition_model:
  ws_superposition: Linear   # Options: Linear, Squared
  ti_superposition: Squared  # Options: Linear, Squared

Rotor Averaging:

rotor_averaging:
  name: center           # Options: center, avg_deficit
  grid: grid
  n_x_grid_points: 4
  n_y_grid_points: 4

Blockage Model:

blockage_model:
  name: None             # Options: None, SelfSimilarityDeficit2020, FUGA
  ss_alpha: 0.888        # SelfSimilarity parameter

API Reference#

Usage#

Command Line:

wifa_pywake path/to/system.yaml

Python:

from wifa.pywake_api import run_pywake

# Run PyWake simulation
aep = run_pywake("path/to/system.yaml")

# Or pass a pre-loaded dictionary
aep = run_pywake(system_dict, output_dir="results")

wifa.pywake_api.run_pywake(yamlFile, output_dir='output')#

Run a PyWake simulation from WindIO input.

Parameters:

yamlFile (str or dict) – Path to WindIO YAML file or pre-loaded dictionary
output_dir (str) – Output directory (overridden by YAML if specified)

Returns:

Annual Energy Production in GWh

Return type:

float

Example:

from wifa.pywake_api import run_pywake

aep = run_pywake("system.yaml")
print(f"AEP: {aep:.2f} GWh")

Supported Input Formats#

Time series: NetCDF with time dimension for wind speed/direction
Weibull distribution: NetCDF with sector probabilities and Weibull parameters
Turbine-specific data: Per-turbine wind conditions with wind_turbine dimension

Outputs#

turbine_data.nc: Power and effective wind speed per turbine
FarmFlow.nc: Flow field (wind speed, TI) on specified grid
output.yaml: Summary of simulation configuration