power_quantities_three_phase

typhoon.test.IEC61000.power_quantities_three_phase(voltages_samples: DataFrame, currents_samples: DataFrame, nominal_grid_freq: float, line_voltage: bool = True, reference_split=None)

This method measures power quantities in Three-phase systems under non-sinusoidal conditions (general case) according to IEEE Std 1459-2010. This method is applied only in grids with a nominal frequency of 50.0 Hz or 60.0 Hz.

Parameters:

  • voltages_samples (pandas.DataFrame) – Voltage points vector.

  • currents_samples (pandas.DataFrame) – Current points vector.

  • nominal_grid_freq (float) – Nominal frequency of the voltage signal; 50 Hz or 60 Hz.

  • line_voltage (bool) – Type of voltage; line-to-line or line-to-neutral voltage.

  • reference_split (list, optional) – List of indices to split the sample in windows. If None, the samples will be split according to the zero-crossings of the voltage signal.

Returns:

df_measurements – With the follow columns:

  • Active power: The measured active power of the input data in W.

  • Fundamental active power: The measured active power in W only considering the fundamental component of the input data.

  • Non-fundamental active power: The measured active power in W subtracting the fundamental component of the input data.

  • Effective voltage: The measured effective voltage of the input data in V.

  • Fundamental effective voltage: The measured effective voltage in V considering the fundamental component of the input data.

  • Non-fundamental effective voltage: The measured effective voltage in V subtracting the fundamental component of the input data.

  • Effective current: The measured effective current of the input data in A.

  • Fundamental effective current: The measured effective current in A considering the fundamental component of the input data.

  • Non-fundamental effective current: The measured effective current in A subtracting the fundamental component of the input data.

  • Effective apparent power: The measured apparent power of the input data in VA.

  • Fundamental effective apparent power: The measured apparent power in VA only considering the fundamental component of the input data.

  • Non-fundamental effective apparent power: The measured apparent power in VA subtracting the fundamental component of the input data.

  • Harmonic apparent power: Evaluates the amount of VA caused by harmonic distortion.

  • Non-active power: The measured non active power of the input data in VAr.

  • Current distortion power: The apparent power caused by current distortion in relation to the fundamental voltage component.

  • Voltage distortion power: The apparent power caused by voltage distortion in relation to the fundamental current component.

  • Power factor: The measured power factor of the input data.

  • Harmonic pollution factor: This power factor quantifies the overall amount of harmonic pollution delivered or absorbed by a load.

  • Fundamental positive active power: The measured active power in W considering only the fundamental component of the positive-sequence of the input data.

  • Fundamental positive reactive power: The measured reactive power in VAr only considering the fundamental component of the positive-sequence of the input data.

  • Fundamental positive apparent power: The measured apparent power in VA only considering the fundamental component of the positive-sequence of the input data.

  • Fundamental unbalanced power: Evaluates the amount of VA caused by an unbalanced system.

  • Fundamental positive power factor: The measured power factor only considering the fundamental component of the positive-sequence of the input data.

  • Load unbalance: The estimated load unbalance between the phases, considering the fundamental active and reactive power and the THD measured on the system.

  • Harmonic distortion power: The measured non active power in VAr considering the harmonic components of the input data.

Return type:

pandas.DataFrame

Examples

>>> from typhoon.test.signals import pandas_3ph_sine
>>> from typhoon.test.IEC61000 import power_quantities_three_phase
>>>
>>> frequency = 60.0
>>> line_to_line_voltage = True
>>> voltage_samples = pandas_3ph_sine(phase=0, frequency=frequency)
>>> current_samples = pandas_3ph_sine(phase=90, frequency=frequency)
>>>
>>> df_measurements = power_quantities_three_phase(voltage_samples, current_samples, frequency, line_to_line_voltage)

You can type df_measurements.columns to check the name of each one. Or you can use df_measurements.iloc[:, i] where i is the column number desired. To select each one of the columns in a pandas.Series:

>>> active_power = df_measurements['Active power']
>>> fundamental_active_power = df_measurements['Fundamental active power']
>>> nonfundamental_active_power = df_measurements['Non-fundamental active power']
>>> effective_voltage = df_measurements['Effective voltage']
>>> fundamental_effective_voltage = df_measurements['Fundamental effective voltage']
>>> nonfundamental_effective_voltage = df_measurements['Non-fundamental effective voltage']
>>> effective_current = df_measurements['Effective current']
>>> fundamental_effective_current = df_measurements['Fundamental effective current']
>>> nonfundamental_effective_current = df_measurements['Non-fundamental effective current']
>>> effective_apparent_power = df_measurements['Effective apparent power']
>>> fundamental_effective_apparent_power = df_measurements['Fundamental effective apparent power']
>>> nonfundamental_effective_apparent_power = df_measurements['Non-fundamental effective apparent power']
>>> harmonic_apparent_power = df_measurements['Harmonic apparent power']
>>> non_active_power = df_measurements['Non-active power']
>>> current_distortion_power = df_measurements['Current distortion power']
>>> voltage_distortion_power = df_measurements['Voltage distortion power']
>>> power_factor = df_measurements['Power factor']
>>> harmonic_pollution_factor = df_measurements['Harmonic pollution factor']
>>> fundamental_positive_active_power = df_measurements['Fundamental positive active power']
>>> fundamental_positive_reactive_power = df_measurements['Fundamental positive reactive power']
>>> fundamental_positive_apparent_power = df_measurements['Fundamental positive apparent power']
>>> fundamental_unbalanced_power = df_measurements['Fundamental unbalanced power']
>>> fundamental_positive_power_factor = df_measurements['Fundamental positive power factor']
>>> load_unbalance = df_measurements['Load unbalance']
>>> harmonic_distortion_power = df_measurements['Harmonic distortion power']
Raises:

ValueError – When the nominal_grid_freq is different from 50 Hz or 60 Hz:

See also

typhoon.test.IEC61000.power_quantities