flasc.utilities.floris_tools.estimate_ws_with_floris

flasc.utilities.floris_tools.estimate_ws_with_floris#

flasc.utilities.floris_tools.estimate_ws_with_floris(df_scada: DataFrame | FlascDataFrame, fm: FlorisModel, verbose: bool = False) → DataFrame | FlascDataFrame[source]#

Estimate the wind speed at the turbine locations using a FLORIS model.

This function estimates the wind speed at the turbine locations using a FLORIS model. The approach follows the example from the RES wind-up method add_ws_est_one_ttype (resgroup/wind-up) by Alex Clerc. However, in this implementation, FLORIS provides the power curves directly rather than their being learned from data. In this way, the estimated wind speed is the speed which would cause FLORIS to predict a power matched to the SCADA data. This will be especially useful in model fitting to avoid any error on un-waked turbines.

Parameters:

  • df_scada (pd.DataFrame | FlascDataFrame) -- Pandas DataFrame with the SCADA data.

  • fm (FlorisModel) -- FLORIS model object.

  • verbose (bool, optional) -- Print warnings and information to the console. Defaults to False.

Returns:

Pandas DataFrame with the estimated wind speed

columns added.

Return type:

pd.DataFrame | FlascDataFrame