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’.
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’.
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:
- 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:
- standard_deviation_method¶
Method for calculating the standard deviation for the Gauss distribution.
- Type:
- power_output¶
Electrical power output of the wind turbine in W.
- Type:
- 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:
- density_correction¶
Used to set density_correction parameter in
power_curve()
.- Type:
- __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]¶
Methods
__init__
(power_plant[, wake_losses_model, ...])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.