flasc.utilities.floris_tools.get_all_dependent_turbines

flasc.utilities.floris_tools.get_all_dependent_turbines#

flasc.utilities.floris_tools.get_all_dependent_turbines(fm_in, wd_array=array([0., 2., 4., 6., 8., 10., 12., 14., 16., 18., 20., 22., 24., 26., 28., 30., 32., 34., 36., 38., 40., 42., 44., 46., 48., 50., 52., 54., 56., 58., 60., 62., 64., 66., 68., 70., 72., 74., 76., 78., 80., 82., 84., 86., 88., 90., 92., 94., 96., 98., 100., 102., 104., 106., 108., 110., 112., 114., 116., 118., 120., 122., 124., 126., 128., 130., 132., 134., 136., 138., 140., 142., 144., 146., 148., 150., 152., 154., 156., 158., 160., 162., 164., 166., 168., 170., 172., 174., 176., 178., 180., 182., 184., 186., 188., 190., 192., 194., 196., 198., 200., 202., 204., 206., 208., 210., 212., 214., 216., 218., 220., 222., 224., 226., 228., 230., 232., 234., 236., 238., 240., 242., 244., 246., 248., 250., 252., 254., 256., 258., 260., 262., 264., 266., 268., 270., 272., 274., 276., 278., 280., 282., 284., 286., 288., 290., 292., 294., 296., 298., 300., 302., 304., 306., 308., 310., 312., 314., 316., 318., 320., 322., 324., 326., 328., 330., 332., 334., 336., 338., 340., 342., 344., 346., 348., 350., 352., 354., 356., 358.]), change_threshold=0.001, limit_number=None, ws_test=9.0)[source]#

Get all dependent turbines for each turbine in the farm.

Wrapper for get_dependent_turbines_by_wd() that loops over all turbines in the farm and packages their dependencies as a pandas dataframe.

Parameters:

  • fm_in (FlorisModel) -- FLORIS object of the farm of interest.

  • wd_array ([np.array]) -- Wind directions at which to determine dependencies. Defaults to [0, 2, ... , 358].

  • change_threshold (float) -- Fractional change in power needed to denote a dependency. Defaults to 0. (any change in power is marked as a dependency)

  • limit_number (int | NoneType) -- Number of turbines that a turbine can have as dependencies. If None, returns all turbines that depend on each turbine. Defaults to None.

  • ws_test (float) -- Wind speed at which FLORIS model is run to determine dependencies. Defaults to 9. m/s.

Returns:

A Pandas Dataframe in which each row

contains a wind direction, each column is a turbine, and each entry is the turbines that depend on the column turbine at the row wind direction. Dependencies can be extracted as: For wind direction wd, the turbines that depend on turbine T are df_out.loc[wd, T]. Dependencies are ordered, with strongest dependencies appearing first.

Return type:

df_out (pd.Dataframe)