def kwargs(cls, model=None):
kwarg_dict = super().kwargs()
kwarg_dict['path_to_feeder_file'] = Kwarg(
default=None,
description='Path to feeder.txt',
parser=None,
choices=None,
nargs=None,
action=None)
kwarg_dict['path_to_switching_devices_file'] = Kwarg(
default=None,
description='Path to switching_devices.dss',
parser=None,
choices=None,
nargs=None,
action=None)
kwarg_dict['switch_to_recloser'] = Kwarg(
default=False,
description='If True does the switch to recloser post-processing',
parser=None,
choices=None,
nargs=None,
action=None)
kwarg_dict['center_tap_postprocess'] = Kwarg(
default=False,
description=
'If True the phases downstream of center tap transformer are reorganized to reflect the phase of the transformer',
parser=None,
choices=None,
nargs=None,
action=None)
return kwarg_dict
return kwarg_dict
def kwargs(cls, model=None):
kwarg_dict = super().kwargs()
kwarg_dict['powerflow_file'] = Kwarg(
default=None,
description='list of powerflow values for each node in the network',
parser=None,
choices=None,
nargs=None,
action=None)
kwarg_dict['threshold'] = Kwarg(
default=None,
description=
'threshold below which the load value needs to be reduced',
parser=None,
choices=None,
nargs=None,
action=None)
kwarg_dict['scale_factor'] = Kwarg(
default=None,
description='Amount to divide the load by when reducing',
parser=None,
choices=None,
nargs=None,
action=None)
return kwarg_dict
def kwargs(cls, model=None):
kwarg_dict = super().kwargs()
kwarg_dict['base_dir'] = Kwarg(default=None, description='Base directory for argument paths.')
kwarg_dict['substation_folder'] = Kwarg(default=None,
description="Defaults to this layer's resources folder",
parser=None, choices=None,nargs=None, action=None)
return kwarg_dict
def kwargs(cls, model=None):
kwarg_dict = super().kwargs()
kwarg_dict['lowpoint'] = Kwarg(
default=None,
description='Voltage point in PT when the capacitor switches on',
parser=None,
choices=None,
nargs=None,
action=None)
kwarg_dict['highpoint'] = Kwarg(
default=None,
description='Voltage point in PT when the capacitor switches off',
parser=None,
choices=None,
nargs=None,
action=None)
kwarg_dict['delay'] = Kwarg(default=None,
description='PT ratio of the element',
parser=None,
choices=None,
nargs=None,
action=None)
return kwarg_dict
def kwargs(cls, model=None):
kwarg_dict = super().kwargs()
kwarg_dict['current_rating'] = Kwarg(
default=None,
description='Rated current of the fuse',
parser=None,
choices=None,
nargs=None,
action=None)
kwarg_dict['high_current_rating'] = Kwarg(
default=None,
description='Rated current of the fuse on HV lines',
parser=None,
choices=None,
nargs=None,
action=None)
kwarg_dict['fuse_set'] = Kwarg(
default=None,
description=
'Set of the fuse names to apply the controls to. If None provided, controls applied to all fuses',
parser=None,
choices=None,
nargs=None,
action=None)
return kwarg_dict
def kwargs(cls):
kwarg_dict = super().kwargs()
kwarg_dict['base_dir'] = Kwarg(default=None, description='Folder to read json file from',
parser=None, choices=None,
nargs=None, action=None)
kwarg_dict['input_filename'] = Kwarg(default=None, description='Name of json file',
parser=None, choices=None,
nargs=None, action=None)
return kwarg_dict
def kwargs(cls, model=None):
kwarg_dict = super().kwargs()
kwarg_dict['delta_x'] = Kwarg(default=None, description='Shift in the coordinates X position',
parser=None, choices=None,
nargs=None, action=None)
kwarg_dict['delta_y'] = Kwarg(default=None, description='Shift in the coordinates Y position',
parser=None, choices=None,
nargs=None, action=None)
return kwarg_dict
def kwargs(cls, model=None):
kwarg_dict = super().kwargs()
kwarg_dict['output_folder'] = Kwarg(default=None, description='output folder location for figures on number of customers per transformer',
parser=None, choices=None,
nargs=None, action=None)
kwarg_dict['customer_file'] = Kwarg(default=None, description='location of the customer infomration file. Header format of "X, Y, Z, Identifier, voltage level, peak active power, peak reactive power, phases, area, height, energy, coincident active power, coincident reactive power, equivalent users, building type, PV capacity, (empty), (empty), (empty)"',
parser=None, choices=None,
nargs=None, action=None)
return kwarg_dict
def kwargs(cls):
kwarg_dict = super().kwargs()
kwarg_dict['base_dir'] = Kwarg(
default=None, description='Base directory for argument paths.')
kwarg_dict['separate_feeders'] = Kwarg(
default=False,
description=
'Boolean of whether or not to split data folders by feeder_name')
kwarg_dict['separate_substations'] = Kwarg(
default=False,
description=
'Boolean of whther or not to split output data folders by substation_name'
)
return kwarg_dict
def kwargs(cls):
kwarg_dict = super().kwargs()
kwarg_dict['base_dir'] = Kwarg(default=None, description='Base directory for argument paths.',
parser=None, choices=None,
nargs=None, action=None)
kwarg_dict['network_filename'] = Kwarg(default=None, description='Name of the network file',
parser=None, choices=None,
nargs=None, action=None)
kwarg_dict['equipment_filename'] = Kwarg(default=None, description='Name of the equipment file',
parser=None, choices=None,
nargs=None, action=None)
kwarg_dict['load_filename'] = Kwarg(default=None, description='Name of the load file',
parser=None, choices=None,
nargs=None, action=None)
return kwarg_dict
def kwargs(cls, model=None):
kwarg_dict = super().kwargs()
kwarg_dict['output_folder'] = Kwarg(
default=None,
description='Location where tags should be moved to',
parser=None,
choices=None,
nargs=None,
action=None)
kwarg_dict['tag_file'] = Kwarg(default=None,
description='Location of tag txt file',
parser=None,
choices=None,
nargs=None,
action=None)
return kwarg_dict
def kwargs(cls):
kwarg_dict = super().kwargs()
kwarg_dict['excel_output'] = Kwarg(
default=None,
description='path to the output file for xlsx export',
parser=None,
choices=None,
nargs=None,
action=None)
kwarg_dict['json_output'] = Kwarg(
default=None,
description='path to the output file for json export',
parser=None,
choices=None,
nargs=None,
action=None)
return kwarg_dict
def kwargs(cls, model=None):
kwarg_dict = super().kwargs()
kwarg_dict['rnm_name'] = Kwarg(
default=None,
description=
'The prefix used in RNM for Transformers which are regulators',
parser=None,
choices=None,
nargs=None,
action=None)
kwarg_dict['setpoint'] = Kwarg(default=None,
description='The regulator setpoint',
parser=None,
choices=None,
nargs=None,
action=None)
return kwarg_dict
def kwargs(cls, model=None):
kwarg_dict = super().kwargs()
kwarg_dict['file_location'] = Kwarg(
default=None,
description=
'csv file location for list of lines that need regulators added to the end of them',
parser=None,
choices=None,
nargs=None,
action=None)
kwarg_dict['setpoint'] = Kwarg(default=None,
description='The regulator setpoint',
parser=None,
choices=None,
nargs=None,
action=None)
return kwarg_dict
def kwargs(cls, model=None):
kwarg_dict = super().kwargs()
kwarg_dict['filename'] = Kwarg(default=None,
description='Path to LineCoord.txt',
parser=None,
choices=None,
nargs=None,
action=None)
return kwarg_dict
def kwargs(cls, model=None):
kwarg_dict = super().kwargs()
kwarg_dict['source_kv'] = Kwarg(
default=None,
description='kv value for any PowerSource objects',
parser=None,
choices=None,
nargs=None,
action=None)
kwarg_dict['source_names'] = Kwarg(
default=None,
description=
'Names of element to additionally set. Expecting a list',
parser=None,
choices=None,
nargs=None,
action=None)
return kwarg_dict
def kwargs(cls, model=None):
kwarg_dict = super().kwargs()
kwarg_dict['kwarg_name'] = Kwarg(default=None,
description='',
parser=None,
choices=None,
nargs=None,
action=None)
return kwarg_dict
def kwargs(cls, model=None):
kwarg_dict = super().kwargs()
kwarg_dict['dataset'] = Kwarg(
default=None,
description='Dataset being used. Important for the projection',
parser=None,
choices=None,
nargs=None,
action=None)
kwarg_dict['base_folder'] = Kwarg(
default=None,
description='Location of the solar data.',
parser=None,
choices=None,
nargs=None,
action=None)
kwarg_dict['output_folder'] = Kwarg(
default=None,
description=
'location of the csv files to be attached to timeseries models',
parser=None,
choices=None,
nargs=None,
action=None)
kwarg_dict['write_cyme_file'] = Kwarg(
default=True,
description='write the cyme timeseries file',
parser=None,
choices=None,
nargs=None,
action=None)
kwarg_dict['write_opendss_file'] = Kwarg(
default=True,
description='write the many opendss timeseries files',
parser=None,
choices=None,
nargs=None,
action=None)
return kwarg_dict
def kwargs(cls, model=None):
kwarg_dict = super().kwargs()
kwarg_dict['base_dir'] = Kwarg(
default=None,
description='Location to write the json file to',
parser=None,
choices=None,
nargs=None,
action=None)
return kwarg_dict
def kwargs(cls, model=None):
kwarg_dict = super().kwargs()
kwarg_dict['setpoint'] = Kwarg(
default=105,
description='Percentage per unit of LTC regulators',
parser=None,
choices=None,
nargs=None,
action=None)
return kwarg_dict
def kwargs(cls, model=None):
kwarg_dict = super().kwargs()
kwarg_dict['to_replace'] = Kwarg(
default=None,
description=
'List of nameclasses that get replaced with LV triplex lines',
parser=None,
choices=None,
nargs=None,
action=None)
return kwarg_dict
def kwargs(cls, model=None):
kwarg_dict = super().kwargs()
kwarg_dict['random_percent'] = Kwarg(default=None,
description='',
parser=None,
choices=None,
nargs=None,
action=None)
kwarg_dict['scale_factor'] = Kwarg(default=None,
description='',
parser=None,
choices=None,
nargs=None,
action=None)
kwarg_dict['timeseries_path'] = Kwarg(default=None,
description='',
parser=None,
choices=None,
nargs=None,
action=None)
return kwarg_dict
def kwargs(cls):
kwarg_dict = super().kwargs()
kwarg_dict['input_filename'] = Kwarg(
default=None,
description='Name of the CSV input file',
parser=None,
choices=None,
nargs=None,
action=None)
kwarg_dict['output_filename'] = Kwarg(
default=None,
description='Name of the CSV output file',
parser=None,
choices=None,
nargs=None,
action=None)
kwarg_dict['object_name'] = Kwarg(
default=None,
description='Name of the object (ex: Load)',
parser=None,
choices=None,
nargs=None,
action=None)
return kwarg_dict
def kwargs(cls, model=None):
kwarg_dict = super().kwargs()
kwarg_dict['input_folder'] = Kwarg(
default=None,
description=
'path to input folder where file metrics.csv is located',
parser=None,
choices=None,
nargs=None,
action=None)
kwarg_dict['output_folder'] = Kwarg(
default=None,
description=
'path to output folder where report cards and histograms are put',
parser=None,
choices=None,
nargs=None,
action=None)
kwarg_dict['output_name'] = Kwarg(
default=None,
description='Name of the metrics set being used',
parser=None,
choices=None,
nargs=None,
action=None)
kwarg_dict['rscript_folder'] = Kwarg(
default=None,
description='Location of smartdsR-analysis-lite folder',
parser=None,
choices=None,
nargs=None,
action=None)
return kwarg_dict
def kwargs(cls, model=None):
kwarg_dict = super().kwargs()
kwarg_dict['feeder_name'] = Kwarg(
default=None,
description='Name of the feeder being parsed.',
parser=None,
choices=None,
nargs=None,
action=None)
kwarg_dict['output_filename_xlsx'] = Kwarg(
default='./',
description='Path to output the excel metric file.',
parser=None,
choices=None,
nargs=None,
action=None)
kwarg_dict['output_filename_json'] = Kwarg(
default='/',
description='Path to output the JSON metric file.',
parser=None,
choices=None,
nargs=None,
action=None)
return kwarg_dict
def kwargs(cls, model=None):
kwarg_dict = super().kwargs()
kwarg_dict['path_to_feeder_file'] = Kwarg(
default=None,
description='Path to feeder.txt',
parser=None,
choices=None,
nargs=None,
action=None)
kwarg_dict['path_to_no_feeder_file'] = Kwarg(
default=None,
description='Path to nofeeder.txt',
parser=None,
choices=None,
nargs=None,
action=None)
kwarg_dict['compute_metrics'] = Kwarg(
default=False,
description='Triggers the metrics computation if set to True',
parser=None,
choices=None,
nargs=None,
action=None)
kwarg_dict['excel_output'] = Kwarg(
default=None,
description='path to the output file for xlsx export',
parser=None,
choices=None,
nargs=None,
action=None)
kwarg_dict['json_output'] = Kwarg(
default=None,
description='path to the output file for json export',
parser=None,
choices=None,
nargs=None,
action=None)
kwarg_dict['compute_kva_density_with_transformers'] = Kwarg(
default=None,
description=
'Flag to use transformers or loads to compute the kva density metric',
parser=None,
choices=None,
nargs=None,
action=None)
return kwarg_dict
def kwargs(cls, model=None):
kwarg_dict = super().kwargs()
kwarg_dict['cutoff_length'] = Kwarg(default=800, description='length in meters at which the line must have switch added',
parser=None, choices=None,
nargs=None, action=None)
return kwarg_dict
def kwargs(cls, model=None):
kwarg_dict = super().kwargs()
kwarg_dict['customer_file'] = Kwarg(
default=None,
description=
'location of the customer infomration file. Header format of "X, Y, Z, Identifier, voltage level, peak active power, peak reactive power, phases, area, height, energy, coincident active power, coincident reactive power, equivalent users, building type, PV capacity, (empty), (empty), (empty)"',
parser=None,
choices=None,
nargs=None,
action=None)
kwarg_dict['residential_load_data'] = Kwarg(
default=None,
description=
'location of the h5 file defining the total timeseries load information for residential customers (not divided by enduse)',
parser=None,
choices=None,
nargs=None,
action=None)
kwarg_dict['residential_load_metadata'] = Kwarg(
default=None,
description=
'location of the csv file defining the residential timeseries load metadata',
parser=None,
choices=None,
nargs=None,
action=None)
kwarg_dict['commercial_load_data'] = Kwarg(
default=None,
description=
'location of the h5 file defining the total timeseries load information for commercial customers (not divided by enduse)',
parser=None,
choices=None,
nargs=None,
action=None)
kwarg_dict['commercial_load_metadata'] = Kwarg(
default=None,
description=
'location of the csv file defining the commercial timeseries load metadata',
parser=None,
choices=None,
nargs=None,
action=None)
kwarg_dict['output_folder'] = Kwarg(
default=None,
description=
'location of the csv files to be attached to timeseries models',
parser=None,
choices=None,
nargs=None,
action=None)
kwarg_dict['write_cyme_file'] = Kwarg(
default=True,
description='write the cyme timeseries file',
parser=None,
choices=None,
nargs=None,
action=None)
kwarg_dict['write_opendss_file'] = Kwarg(
default=True,
description='write the many opendss timeseries files',
parser=None,
choices=None,
nargs=None,
action=None)
kwarg_dict['dataset'] = Kwarg(
default=True,
description='Which dataset is being used',
parser=None,
choices=None,
nargs=None,
action=None)
return kwarg_dict
def kwargs(cls):
kwarg_dict = super().kwargs()
kwarg_dict['base_dir'] = Kwarg(
default=None, description='Base directory for argument paths')
return kwarg_dict
def kwargs(cls, model=None):
kwarg_dict = super().kwargs()
kwarg_dict['num_customers'] = Kwarg(default=None, description='Number of customers at each load')
return kwarg_dict