GridCal.Engine package

Subpackages

Submodules

GridCal.Engine.basic_structures module

class GridCal.Engine.basic_structures.BranchImpedanceMode

Bases: enum.Enum

An enumeration.

Lower = 2
Specified = 0
Upper = 1
class GridCal.Engine.basic_structures.BusMode

Bases: enum.Enum

An enumeration.

NONE = (4,)
PQ = (1,)
PV = (2,)
REF = (3,)
STO_DISPATCH = 5
class GridCal.Engine.basic_structures.CDF(data)

Bases: object

Inverse Cumulative density function of a given array of data

get_at(prob)

Samples a number of uniform distributed points and returns the corresponding probability values given the CDF. @param prob: probability from 0 to 1 @return: Corresponding CDF value

get_sample(npoints=1)

Samples a number of uniform distributed points and returns the corresponding probability values given the CDF. @param npoints: Number of points to sample, 1 by default @return: Corresponding probabilities

plot(ax=None)

Plots the CFD @param ax: MatPlotLib axis to plot into @return:

class GridCal.Engine.basic_structures.StatisticalCharacterization(gen_P, load_P, load_Q)

Bases: object

Object to store the statistical characterization It is useful because the statistical characterizations can be: - not grouped - grouped by day - grouped by hour

get_sample(load_enabled_idx, gen_enabled_idx, npoints=1)

Returns a 2D array containing for load and generation profiles, shape (time, load) The profile is sampled from the original data CDF functions

@param npoints: number of sampling points @return: PG: generators profile S: loads profile

plot(ax)

Plot this statistical characterization @param ax: matplotlib index @return:

GridCal.Engine.basic_structures.classify_by_day(t: pandas.core.indexes.datetimes.DatetimeIndex)

Passes an array of TimeStamps to an array of arrays of indices classified by day of the year @param t: Pandas time Index array @return: list of lists of integer indices

GridCal.Engine.basic_structures.classify_by_hour(t: pandas.core.indexes.datetimes.DatetimeIndex)

Passes an array of TimeStamps to an array of arrays of indices classified by hour of the year @param t: Pandas time Index array @return: list of lists of integer indices

GridCal.Engine.grid_analysis module

class GridCal.Engine.grid_analysis.TimeSeriesResultsAnalysis(numerical_circuit: GridCal.Engine.Core.numerical_circuit.NumericalCircuit, results: GridCal.Engine.Simulations.PowerFlow.time_series_driver.TimeSeriesResults)

Bases: object

GridCal.Engine.plot_config module