flasc.model_fitting.turbulence_estimator#

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Classes

ti_estimator

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class flasc.model_fitting.turbulence_estimator.ti_estimator(fm)[source]#

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_reset_outputs()[source]#
set_measurements(P_measured)[source]#

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Parameters:

P_measured (_type_) -- _description_

get_turbine_order()[source]#

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Returns:

_description_

Return type:

_type_

get_turbine_pairs(wake_loss_thrs=0.2)[source]#

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Parameters:

wake_loss_thrs (float, optional) -- _description_. Defaults to 0.20.

Returns:

_description_

Return type:

_type_

plot_flowfield()[source]#

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Returns:

_description_

Return type:

_type_

floris_set_ws_wd_ti(wd=None, ws=None, ti=None)[source]#

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Parameters:
  • wd (_type_, optional) -- _description_. Defaults to None.

  • ws (_type_, optional) -- _description_. Defaults to None.

  • ti (_type_, optional) -- _description_. Defaults to None.

_check_measurements()[source]#
estimate_farmaveraged_ti(Ns=50, bounds=(0.01, 0.5), refine_with_fmin=False, verbose=False)[source]#

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Parameters:
  • Ns (int, optional) -- _description_. Defaults to 50.

  • bounds (tuple, optional) -- _description_. Defaults to (0.01, 0.50).

  • refine_with_fmin (bool, optional) -- _description_. Defaults to False.

  • verbose (bool, optional) -- _description_. Defaults to False.

Returns:

_description_

Return type:

_type_

estimate_local_tis(Ns=50, bounds=(0.01, 0.5), refine_with_fmin=False, verbose=False)[source]#

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Parameters:
  • Ns (int, optional) -- _description_. Defaults to 50.

  • bounds (tuple, optional) -- _description_. Defaults to (0.01, 0.50).

  • refine_with_fmin (bool, optional) -- _description_. Defaults to False.

  • verbose (bool, optional) -- _description_. Defaults to False.

Returns:

_description_

Return type:

_type_

plot_cost_function_farm()[source]#

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plot_cost_functions_turbines()[source]#

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plot_power_bars()[source]#

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Returns:

_description_

Return type:

_type_