windpowerlib.turbine_cluster_modelchain.TurbineClusterModelChain¶
-
class
windpowerlib.turbine_cluster_modelchain.
TurbineClusterModelChain
(power_plant, wake_losses_model='dena_mean', smoothing=False, block_width=0.5, standard_deviation_method='turbulence_intensity', smoothing_order='wind_farm_power_curves', **kwargs)[source]¶ Model to determine the output of a wind farm or wind turbine cluster.
Parameters: - power_plant (
WindFarm
orWindTurbineCluster
) – AWindFarm
object representing the wind farm or aWindTurbineCluster
object representing the wind turbine cluster. - wake_losses_model (str or None) –
- Defines the method for taking wake losses within the farm into
- consideration.
- None - Wake losses are not taken into account.
- ’wind_farm_efficiency’ -
The values of the wind farm power curve(s) are reduced by the wind
farm efficiency, which needs to be set in the
WindFarm
class. Note: The wind farm efficiency has no effect if wake_losses_model is not set to ‘wind_farm_efficiency’. Seewake_losses_to_power_curve()
for more information. - ’dena_mean’ or name of other wind efficiency curve -
The values of the wind speed time series are reduced by the chosen
wind efficiency curve in
run_model()
before the power output calculations. Seereduce_wind_speed()
for more information. Useget_wind_efficiency_curve()
to get a DataFrame of all provided wind efficiency curves and see the provided example on how to plot the wind efficiency curves.
Default: ‘dena_mean’.
- smoothing (bool) –
If True the power curves will be smoothed to account for the distribution of wind speeds over space. Depending on the parameter smoothing_order the power curves are smoothed before or after aggregating wind turbine power curves to one representative power curve of the wind farm or cluster. See
smooth_power_curve()
for more information.Default: False.
- block_width (float) –
Width between the wind speeds in the sum of the equation in
smooth_power_curve()
. This parameter is only used if smoothing is True. To achieve a smooth curve without steps a value not much higher than the step width between the power curve wind speeds should be chosen.Default: 0.5.
- standard_deviation_method (str) –
Method for calculating the standard deviation for the Gauss distribution if smoothing is True.
- ’turbulence_intensity’ -
See
smooth_power_curve()
for more information. - ’Staffell_Pfenninger’ -
See
smooth_power_curve()
for more information.
Default: ‘turbulence_intensity’.
- ’turbulence_intensity’ -
See
- smoothing_order (str) –
Defines when the smoothing takes place if smoothing is True.
- ’turbine_power_curves’ - Smoothing is applied to wind turbine power curves.
- ’wind_farm_power_curves’ - Smoothing is applied to wind farm power curves.
Default: ‘wind_farm_power_curves’.
Other Parameters: - wind_speed_model – See
ModelChain
for more information. - temperature_model – See
ModelChain
for more information. - density_model – See
ModelChain
for more information. - power_output_model – See
ModelChain
for more information. - density_correction – See
ModelChain
for more information. - obstacle_height – See
ModelChain
for more information. - hellman_exp – See
ModelChain
for more information.
-
power_plant
¶ A
WindFarm
object representing the wind farm or aWindTurbineCluster
object representing the wind turbine cluster.Type: WindFarm
orWindTurbineCluster
-
wake_losses_model
¶ Defines the method for taking wake losses within the farm into consideration.
Type: str or None
-
block_width
¶ Width between the wind speeds in the sum of the equation in
smooth_power_curve()
.Type: float
-
standard_deviation_method
¶ Method for calculating the standard deviation for the Gauss distribution.
Type: str
-
power_output
¶ Electrical power output of the wind turbine in W.
Type: pandas.Series
-
power_curve
¶ The calculated power curve of the wind farm.
Type: pandas.Dataframe or None
-
temperature_model
¶ Defines which model is used to calculate the temperature of air at hub height.
Type: str
-
density_correction
¶ Used to set density_correction parameter in
power_curve()
.Type: bool
-
__init__
(power_plant, wake_losses_model='dena_mean', smoothing=False, block_width=0.5, standard_deviation_method='turbulence_intensity', smoothing_order='wind_farm_power_curves', **kwargs)[source]¶ Initialize self. See help(type(self)) for accurate signature.
Methods
__init__
(power_plant[, wake_losses_model, …])Initialize self. assign_power_curve
(weather_df)Calculates the power curve of the wind turbine cluster. calculate_power_output
(wind_speed_hub, …)Calculates the power output of the wind power plant. density_hub
(weather_df)Calculates the density of air at hub height. run_model
(weather_df)Runs the model. temperature_hub
(weather_df)Calculates the temperature of air at hub height. wind_speed_hub
(weather_df)Calculates the wind speed at hub height. - power_plant (