windpowerlib.turbine_cluster_modelchain.TurbineClusterModelChain.run_model¶

TurbineClusterModelChain.run_model(weather_df)[source]¶

Runs the model.

Parameters:: weather_df (pandas.DataFrame) – DataFrame with time series for wind speed wind_speed in m/s, and roughness length roughness_length in m, as well as optionally temperature temperature in K, pressure pressure in Pa, density density in kg/m³ and turbulence intensity turbulence_intensity depending on power_output_model, density_model and standard_deviation_model chosen. The columns of the DataFrame are a MultiIndex where the first level contains the variable name (e.g. wind_speed) and the second level contains the height at which it applies (e.g. 10, if it was measured at a height of 10 m). See below for an example on how to create the weather_df DataFrame.
Return type:: self

Examples

>>> import numpy as np
>>> import pandas as pd
>>> my_weather_df = pd.DataFrame(np.random.rand(2,6),
...                           index=pd.date_range('1/1/2012',
...                                               periods=2,
...                                               freq='H'),
...                           columns=[np.array(['wind_speed',
...                                              'wind_speed',
...                                              'temperature',
...                                              'temperature',
...                                              'pressure',
...                                              'roughness_length']),
...                                    np.array([10, 80, 10, 80,
...                                             10, 0])])
>>> my_weather_df.columns.get_level_values(0)[0]
'wind_speed'