flasc.analysis.expected_power_analysis_by.total_uplift_expected_power_by_ws

flasc.analysis.expected_power_analysis_by.total_uplift_expected_power_by_ws#

class flasc.analysis.expected_power_analysis_by.total_uplift_expected_power_by_ws(a_in: AnalysisInput, uplift_pairs: List[Tuple[str, str]], uplift_names: List[str], test_turbines: List[int], wd_turbines: List[int] | None = None, ws_turbines: List[int] | None = None, use_predefined_wd: bool = False, use_predefined_ws: bool = False, wd_step: float = 2.0, wd_min: float = 0.0, wd_max: float = 360.0, ws_step: float = 1.0, ws_min: float = 0.0, ws_max: float = 50.0, bin_cols_in: List[str] = ['wd_bin', 'ws_bin'], weight_by: str = 'min', df_freq: DataFrame | None = None, use_standard_error: bool = True, N: int = 1, percentiles: List[float] = [2.5, 97.5], remove_any_null_turbine_bins: bool = False, cov_terms: str = 'zero')[source]#

Bases: _total_uplift_expected_power_by_

Compute total uplift using expected power methods by wind speed.

Methods

plot

Plot the total uplift results by wind direction or wind speed.

plot_with_distributions

Plot results by wind direction or wind speed with histograms and distributions.
Parameters:

  • a_in (AnalysisInput)

  • uplift_pairs (List[Tuple[str, str]])

  • uplift_names (List[str])

  • test_turbines (List[int])

  • wd_turbines (List[int])

  • ws_turbines (List[int])

  • use_predefined_wd (bool)

  • use_predefined_ws (bool)

  • wd_step (float)

  • wd_min (float)

  • wd_max (float)

  • ws_step (float)

  • ws_min (float)

  • ws_max (float)

  • bin_cols_in (List[str])

  • weight_by (str)

  • df_freq (DataFrame)

  • use_standard_error (bool)

  • N (int)

  • percentiles (List[float])

  • remove_any_null_turbine_bins (bool)

  • cov_terms (str)