1. HIL API¶

Module: typhoon.api.hil

HIL API is collections of functions that allow users to real-time control HIL simulation process from the Python scripts.

Functions are divided into four groups:

Functions for controlling and initializing simulation process (function for loading model, starting/stopping simulation…)
Functions for setting and changing the state of the simulation (various set_ functions)
Functions for getting information from the simulation (get_ functions including Capture functionality)
Various utility functions

In order to correctly control HIL simulation process, simulation model (and connected HIL itself) should be initialized by loading compiled Schematic Editor model (.cpd file) with load_model() function.

Note

Many functions cannot be used correctly if simulation model is not initialized. In case you try to use these functions before model is initialized, you will get Model was not loaded. Command ignored! message.

After simulation model was initialized you should set model parameters (Sources, Machines, Contactors… by using appropriate set_ functions) and then start simulation with the start_simulation() function.

Note

Simulation parameters also can be changed after simulation is started.

Simulation can be stopped at any time by calling stop_simulation() function.

Bellow you can find example which demonstrates use of the Capture functionality after simulation is initialized.

Example script:

import typhoon.api.hil as hil

# first we need to load model
hil.load_model(file= r'C:\Typhoon HIL Control Center\examples\models\power electronics\3ph_rectifier Target files\3ph_rectifier.cpd')

# after model is loaded we could open existing settings file which will initialize model parameters...
hil.load_settings_file(file=r'C:\Typhoon HIL Control Center\examples\models\power electronics\3ph_rectifier Target files\settings.runx')

# ...or manually set desired model parameters
# input files
hil.set_source_arbitrary_waveform('Va',file=r'D:\input variables\phase_a_110V_60Hz.isg')
hil.set_source_arbitrary_waveform('Vb',file=r'D:\input variables\phase_b_110V_60Hz.isg')
hil.set_source_arbitrary_waveform('Vc',file=r'D:\input variables\phase_c_110V_60Hz.isg')

# switching blocks
hil.set_pe_switching_block_control_mode(blockName = "3ph_inverter 1",switchName = "Sa_top",swControl = True)
hil.set_pe_switching_block_software_value(blockName = "3ph_inverter 1",switchName = "Sa_top",value = 1)

# analog channels
hil.set_analog_output(5,"V( Va )",scaling=150.00,offset=5.00)

# digital channels
hil.set_digital_output(1,name="digital input 1",invert=True,swControl=False,value=0)

# machine
hil.set_machine_constant_torque(name="machine 1",value=2.5)
hil.set_machine_linear_torque(name="machine 1",value=5.0)
hil.set_machine_square_torque(name="machine 1",value=6.0)
hil.set_machine_constant_torque_type(name="machine 1",frictional=True)
hil.set_machine_initial_angle(name="machine 1",angle=3.14)
hil.set_machine_initial_speed(name="machine 1",speed=100.0)
hil.set_machine_inc_encoder_offset(name="machine 1",offset=3.14)
hil.set_machine_sin_encoder_offset(name="machine 1",offset=1.57)

# after we set model parameters we can start simulation
hil.start_simulation()

# decimation,numberOfChannels,numberOfSamples
captureSettings = [1,3,1e5]
# triggerType,triggerSource,threshold,edge,triggerOffset
triggerSettings = ["Analog",1,0.0,"Rising edge",50.0]
# signals for capturing
channelSettings = ["V( Va )","V( Vb )","V( Vc )"]

# regular python list is used for data buffer
capturedDataBuffer = []

# start capture process and if everything ok continue...
if hil.start_capture(captureSettings,
                     triggerSettings,
                     channelSettings,
                     dataBuffer = capturedDataBuffer,
                     fileName = r'C:\captured_signals\capture_test.mat'):

    # when capturing is finished...
    while hil.capture_in_progress():
        pass

    # unpack data from data buffer
    # (signalsNames - list with names,
    #  yDataMatrix  - 'numpy.ndarray' matrix with data values,
    #  xData        - 'numpy.array' with time data)
    (signalsNames,yDataMatrix,xData) = capturedDataBuffer[0]

    # unpack data for appropriate captured signals
    Va_data = yDataMatrix[0] # first row for first signal and so on
    Vb_data = yDataMatrix[1]
    Vc_data = yDataMatrix[2]

else:

    # if error occured
    print "Unable to start capture process."


# we will stop simulation
hil.stop_simulation()

# and end script
hil.end_script_by_user()

1.1. API references ¶

This module defines the interface with HIL API.

load_model(file='', offlineMode=False, vhil_device=False)¶

Uploads a compiled model to a HIL device.

Parameters:

file (str) – absolute or relative path to the compiled model file (.cpd extension).
offlineMode (bool) – True for activating the offline mode or False to deactivate it.
vhil_device (bool) – If set to True Virtual HIL Device will be used in case a hardware HIL device is not detected.

Note

In the offline mode data will not be sent to the HIL device and some of API functions cannot be used.

Returns:: True if uploading a compiled model succeeded, otherwise returns False.

Availability:

standalone scripts

Example:

# loading model
status =  load_model(
    file=r"./examples/models/3phaseTarget files/3phaseRectifier.cpd")

if status:
    # if loading went successfully we can continue
    ...

load_settings_file(file='')¶

Loads a HIL Control Panel settings file and configures the model accordingly.

Parameters:: file (str) – absolute or relative path to .run/.runx simulation settings file.
Returns:: True if the settings file loaded successfully, otherwise returns False.

Availability:

standalone scripts

Example:

# load HIL Control Panel settings file
hil.load_settings_file(
    file=r"./examples/models/3phase Target files/init.runx")

save_settings_file(filePath)¶

Saves the settings file to a location provided in the argument.

Parameters:: filePath (str) – the file path where the settings file will be saved.
Returns:: True if the settings file is saved successfully, otherwise returns False.

Availability:

standalone scripts

Example:

# save HIL Control Panel settings file
hil.save_settings_file(r"./examples/3phase Target files/init.runx")

save_model_state(save_to)¶

Saves the current model state to the file, from which the model state can be restored any time.

This function can be used in case the test scenario needs to be divided in multiple Python test scripts, when reloading and reconfiguring the model is not an option.

At the end of the first test script, the model state can be saved and at the beginning of another test script, the model state can be loaded again without stopping the simulation.

Parameters:: save_to (str) – the path to a file where the current model state will be saved.
Returns:: True if the model state was successfully saved, otherwise returns False

Availability:

standalone scripts

An example that uses three scripts.

Initialization script:

# load the model by using load_model() function
# ...
# initialize model parameters
# ...
# start the simulation
# ...
# at the end of the script save the model state
# (the name of file is arbitrary)
hil.save_model_state("./model_state.ms")

Configuration script:

# at the beginning load the model state saved at the end of previous
# script
hil.load_model_state("./model_state.ms")
# ...
# change model parameters by the following test scenario
# ...
# at the end of the script save the model state
# (the name of file is arbitrary)
hil.save_model_state("./model_state.ms")

Data analysis script:

# at the beginning load model state saved at the end of the previous
# script
hil.load_model_state("./model_state.ms")
# ...
# capture data
# ...
# analyze data
# ...
# stop the simulation

load_model_state(load_from)¶

Loads the HIL model state from a file and connects to the HIL device.

This function can be used in case the test scenario needs to be divided in multiple Python test scripts when reloading and reconfiguring of the model is not an option.

At the end of the first test script, the model state can be saved and at the beginning of another test script, the model state can be loaded again without stopping the simulation.

Note

Model state is not going to be synchronized with the connected HIL device.

Parameters:: load_from (str) – the path to a file with the saved HIL model state.
Returns:: True if the model state was successfully restored, otherwise returns False

An example that uses three scripts.

Initialization script:

# load the model by using load_model() function
# ...
# initialize model parameters
# ...
# start the simulation
# ...
# at the end of script save model state (the name of file is arbitrary)
hil.save_model_state("./model_state.ms")

Configuration script:

# at the beginning load the model state saved at the end of
# the previous script
hil.load_model_state("./model_state.ms")
# ...
# change model parameters by the following test scenario
# ...
# at the end of the script save the model state
# (the name of file is arbitrary)
hil.save_model_state("./model_state.ms")

Data analysis script:

# at the beginning load the model state saved at the end of
# the previous script
hil.load_model_state("./model_state.ms")
# ...
# capture data
# ...
# analyze data
# ...
# stop the simulation

upload_standalone_model(model_location)¶

Upload already loaded Model as standalone model to the HIL device on specified model location.

Note

Standalone configuration can be uploaded only after Model is loaded with load_model() function and simulation is not running.

Parameters:: model_location (int) – upload model to selected model location slot. There are 8 available slots for standalone models.
Returns:: True if everything ok, otherwise returns False.
Return type:: status (bool)

Availability:

standalone scripts

model_write(model_variable, new_value)¶

Sets new value of Model variable with name model_variable.

Parameters:

model_variable (str) –
the name of Model variable that need to be changed. The Model variable name’s components can be divided with different separators. Currently supported separators are: “.”, “/”

Example of different separators:
```
# name of a Model variable with default '.' separator
model_write("Vgrid.rms" , 25)

# name of a Model variable with '/' separator
model_write("Vgrid/rms" , 25)
```
Note

The list of all available Model variables and theirs attributes can be acquired by calling get_model_variables() function.
new_value (int, float, list) – new Model variable value

Returns:

None

Raises:

HILAPIException – in case Model variable with model_variable cannot be found
HILAPIException – in case Model variable with model_variable is read only variable and cannot be changed.
HILAPIException – in case new_value argument is invalid
HILAPIException – in case Model variable value cannot be changed for any other reasons.

model_read(model_variable)¶

Reads value of Model variable with name model_variable.

Parameters:

model_variable (str) –

the name of Model variable that we want to read. The Model variable name’s components can be divided with different separators. Currently supported separators are: “.”, “/”

Example of different separators:

# name of a Model variable with default '.' separator
model_read("Vgrid.rms")

# name of a Model variable with '/' separator
model_read("Vgrid/rms")

Note

The list of all available Model variables and theirs attributes can be acquired by calling get_model_variables() function.

Returns:

Model variable value

Return type:

variable value (int, float)

Raises:

HILAPIException – in case Model variable with model_variable name cannot be found
HILAPIException – in case Model variable with model_variable name is write only variable and cannot be read.
HILAPIException – in case Model variable value cannot be acquired for any reason.

add_data_logger(name, signals, data_file, use_suffix=True)¶

Adds one logger to the model that will collect signals data and store them to the specified data file.

Note

Only streaming analog and digital signals can be continuously logged to the data file.

Note

Data logger will start to collect data only after simulation and data logger are started.

Note

Each time data logger is started it will overwrite old data file in case use_suffix=False otherwise it will create new file with the current data and time suffix.

Parameters:

name (of given data file) – the name of the data logger
signals (list) –
list of streaming analog or digital signals’ names

Note

Only streaming signals that works on the same execution rates are supported to be logged in one data logger.
data_file (string) –
file path to the data file where collected data are going to be saved.

Note

Comma Separated Values (.csv), and HDF5 (.h5), and MDF (.mf4) data files formats are supported.

Note

It is not recommended to use .csv data format for high data transfer rates.
use_suffix (bool) – suffix with date and time will be added to the end
name –

Returns:

True if data logger is successfully added, otherwise returns False

Return type:

status (bool)

Availability:

standalone scripts

Example:

# add data logger
status = hil.add_data_logger(
    name='data_logger_1',
    signals=["Probe1[0]", "Probe1[1]",
             "Digital Probe1[0]", "Digital Probe1[1]"],
    data_file="./data_data_logger_1.csv",
    use_suffix=False)

# start data logger
# (it won't start to collect data because simulation is not started)
status = hil.start_data_logger(name='data_logger_1')

# start simulation
# (data logger will immediately start to collect data because
# is already started)
hil.start_simulation()

# ... do something

# stop data logger
status = hil.stop_data_logger(name='data_logger_1')

Example:

# to open and parse saved data files you can use excellent
# Python Pandas library
import pandas as pd

# read *.csv file (you will get pandas DataFrame object)
pandas_data_frame = pd.read_csv("./data_data_logger_1.csv")

# read *.h5 file (you will get pandas DataFrame object)
pandas_data_frame = pd.read_hdf("./data_data_logger_1.h5")

remove_data_logger(name)¶

Removes data logger with the given name from the model. In case the name is given as a list of loggers names, all loggers from the list will be removed at the same time.

Parameters:

name (str or list) – the name of one data logger or list of data loggers names that need to be removed.

Returns:

True if data logger is successfully removed,: otherwise returns False

Return type:

status (bool)

Example:

# add data loggers
status = hil.add_data_logger(
    name='data_logger_1',
    signals=["Probe1[0]", "Probe1[1]",
             "Digital Probe1[0]", "Digital Probe1[1]"],
    data_file="./data_data_logger_1.csv")

status = hil.add_data_logger(
    name='data_logger_2',
    signals=["Probe1[0]", "Probe1[1]", "Digital Probe1[0]",
             "Digital Probe1[1]"],
    data_file="./data_data_logger_2.csv")

# ... do something

# remove data loggers one by one from the model
status = hil.remove_data_logger(name='data_logger_1')
status = hil.remove_data_logger(name='data_logger_2')

# ...or
status = hil.remove_data_logger(
    name=['data_logger_1', 'data_logger_2'])

start_data_logger(name)¶

Starts data logger with the given name from the model. In case the name is given as a list of loggers names, all loggers from the list will be started at the same time.

Parameters:

name (str or list) – the name of one data logger or list of data loggers names that need to be started.

Returns:

True if data logger is successfully started,: otherwise returns False

Return type:

status (bool)

Example:

# add data loggers
status = hil.add_data_logger(
    name='data_logger_1',
    signals=["Probe1[0]", "Probe1[1]",
             "Digital Probe1[0]", "Digital Probe1[1]"],
    data_file="./data_data_logger_1.csv")

status = hil.add_data_logger(
    name='data_logger_2',
    signals=["Probe1[0]", "Probe1[1]",
             "Digital Probe1[0]", "Digital Probe1[1]"],
data_file="./data_data_logger_2.csv")

# ... do something

# start data loggers one by one
status = hil.start_data_logger(name='data_logger_1')
status = hil.start_data_logger(name='data_logger_2')

# ...or
status = hil.start_data_logger(name=['data_logger_1', 'data_logger_2'])

stop_data_logger(name)¶

Stops data logger with the given name from the model. In case the name is given as a list of loggers names, all loggers from the list will be stopped at the same time.

Parameters:

name (str or list) – the name of one data logger or list of data loggers names that need to be stopped.

Returns:

True if data logger is successfully stopped,: otherwise returns False

Return type:

status (bool)

Example:

# add data loggers
status = hil.add_data_logger(
    name='data_logger_1',
    signals=["Probe1[0]", "Probe1[1]", "Digital Probe1[0]",
             "Digital Probe1[1]"],
    data_file="./data_data_logger_1.csv")

status = hil.add_data_logger(
    name='data_logger_2',
    signals=["Probe1[0]", "Probe1[1]", "Digital Probe1[0]",
             "Digital Probe1[1]"],
    data_file="./data_data_logger_2.csv")

# ... do something

# stop data loggers one by one
status = hil.stop_data_logger(name='data_logger_1')
status = hil.stop_data_logger(name='data_logger_2')

# ...or
status = hil.stop_data_logger(name=['data_logger_1', 'data_logger_2'])

update_sources(sources, executeAt=None)¶

Updates (activates) previously prepared source waveforms.

Parameters:

sources (list) – a list that contains sources’ names.
executeAt (int, float) – executes this command at a specified simulation time. If executeAt is not specified (or executeAt == None) the command will be executed immediately.

Returns:

True if waveforms are updated/activated, otherwise returns False.

Availability:

standalone scripts
macro scripts

Example:

# get the simulation step
simulationStep = hil.get_sim_step()

# calculate the update (execution) times
executeAt1 = simulationStep * 100000 # execute after 100000 sim cycles
executeAt2 = simulationStep * 200000

# prepare arbitrary waveforms for three sources
hil.prepare_source_arbitrary_waveform(
    "Va", file=r"./examples/inputs/sources/230V_50Hz_phase_a.isg")
hil.prepare_source_arbitrary_waveform(
    "Vb", file=r"./examples/inputs/sources/230V_50Hz_phase_b.isg")
hil.prepare_source_arbitrary_waveform(
    "Vc", file=r"./examples/inputs/sources/230V_50Hz_phase_c.isg")

# update 'Va' and 'Vb' source at the same time
hil.update_sources(["Va", "Vb"], executeAt=executeAt1)

# update 'Vc' source at a different time
hil.update_sources(["Vc"], executeAt=executeAt2)

prepare_source_arbitrary_waveform(name, file='')¶

Assigns an arbitrary waveform file (isg) to a given independent voltage/current source(s). Arbitrary waveform data will be sent to a HIL device, but will not be activated.

To activate the uploaded waveform use the update_sources() function.

Note

Only one waveform can be queued for update. Further calls to this function will overwrite the previously prepared waveform.

Parameters:

name (str, list) – source name or a list of source names that need to be prepared.
file (str, list) – absolute or relative path to the waveform file (isg extension) or list of paths to waveform files.

Returns:

True if waveform assignment succeeded, otherwise returns False.

Availability:

standalone scripts
macro scripts

Example:

# prepare one by one
hil.prepare_source_arbitrary_waveform(
    "Va", file=r"./examples/inputs/sources/230V_50Hz_phase_a.isg")
hil.prepare_source_arbitrary_waveform(
    "Vb", file=r"./examples/inputs/sources/230V_50Hz_phase_b.isg")
hil.prepare_source_arbitrary_waveform(
    "Vc", file=r"./examples/inputs/sources/230V_50Hz_phase_c.isg")

# or prepare all of them
hil.prepare_source_arbitrary_waveform(
    name=["Va", "Vb", "Vc"],
    file=[r"./examples/inputs/sources/230V_50Hz_phase_a.isg",
          r"./examples/inputs/sources/230V_50Hz_phase_b.isg",
          r"./examples/inputs/sources/230V_50Hz_phase_c.isg"])

prepare_source_constant_value(name, value=0)¶

Sets a constant value to a given independent voltage/current source(s). The new value will be sent to a HIL device, but it will not be activated.

To activate the prepared value use the update_sources() function.

Note

Only one value change can be queued for update. Further calls to this function will overwrite the previously prepared value.

Parameters:

name (str, list) – source name or a list of source names.
value (float, list) – the constant value or list of constant values that need to be prepared.

Returns:

True if setting the constant value succeeded, otherwise returns False.

Availability:

standalone scripts
macro scripts

Example:

# prepare one source
hil.prepare_source_constant_value("Vdc", value=200)

# or prepare multiple sources
hil.prepare_source_constant_value(["Vdc", "Vab"], value=[200, 100])

prepare_source_sine_waveform(name, rms=None, frequency=None, phase=None, harmonics=None, harmonics_pu=None)¶

Assigns a sinusoidal signal to a given independent voltage/current source(s). The sinusoidal signal will be sent to a HIL device, but it will not be activated.

To activate the uploaded waveform data use the update_sources() function.

Note

Only one signal change can be queued for update. Further calls to this function will overwrite the previously prepared signal change.

Parameters:

name (str, list) – source name or a list of source names.
rms (float, list) – rms value or list of rms values.
frequency (float, list) – frequency (default 50Hz) or list of frequency values.
phase (float, list) – phase (in degrees) or list of phase values.
harmonics (list) –
list of harmonics, which should be specified as follows:

list[(harmonic_number_1,rms_1,phase_1),
…, (harmonic_number_n,rms_n,phase_n)].
harmonics_pu (list) –
list of per-unit harmonics, which should be specified as follows:

list[(harmonic_number_1,rms_p_u_1,phase_1),
…, (harmonic_number_n,rms_p_u_n,phase_n)]

where:

rms_p_u_n value is harmonic rms given in a relative unit between 0 and 1.

Note

harmonics argument was left for the compatibility purposes. Old type of harmonics will be automatically converted to the new per-unit harmonics.

Returns:: True if the sinusoidal signal is assigned successfully, otherwise returns False

Availability:

standalone scripts
macro scripts

Example:

# list of harmonics
harmonics = []

# tuples that contains harmonic settings
# (harmonic_number,rms,phase)
harmonic1 = (2, 23, 2)
harmonic2 = (2, 2, 0)
harmonic3 = (20, 5, 5)

# store harmonics
harmonics.append(harmonic1)
harmonics.append(harmonic2)
harmonics.append(harmonic3)

# prepare one
hil.prepare_source_sine_waveform("Vb", rms=220, frequency=50,
                                 phase=120, harmonics=harmonics)

# or prepare multiple sources
hil.prepare_source_sine_waveform(["Va", "Vb"],
                                 rms=[220, 230],
                                 frequency=[50, 60],
                                 phase=[120, 100],
                                 harmonics=harmonics)

enable_ao_limiting(channel, lower_limit, upper_limit, device=0)¶

Enables Analog output current/voltage limiting features and sets new lower and upper limits, which is necessary to activate the protection for a model created with +/-5.0 AO range on devices with +/-10.0 AO range.

Args

channel (int): analog output channel number.

lower_limit (float): lover limiting value.

upper_limit (float): upper limiting value

device (int): on which device you want to set analog output.

Returns:

True if everything ok, otherwise returns False.

Availability:

standalone scripts
macro scripts

Example:

hil.enable_ao_limiting(
    1, lower_limit=-1.0, upper_limit=1.0, device=0)

disable_ao_limiting(channel, device=0)¶

Disables Analog output current/voltage limiting features and set lover and upper limits to the default value.

Args

channel (int): analog output channel number.

device (int): on which device you want to set analog output.

Returns:

True if everything ok, otherwise returns False.

Availability:

standalone scripts
macro scripts

Example:

hil.disable_ao_limiting(1, device=1)

set_boot_configuration(boot_opt, model_location=None, digital_settings=None)¶

Sets standalone configuration boot options.

Parameters:

boot_opt (int) – there is three supported boot options listed bellow
model_location (int) –
in case boot option Boot using selected model is used, this argument specify which uploaded model slot is used.
digital_settings (list) –
in case Boot using model selected by digital inputs is used, this argument specify digital signal settings used for selecting uploaded model location slot.

..note:
digital_settings argument should be list of three elements, where each element is int number of digital signal used for configuration in range [1, number of digital outputs].

BOOT OPTIONS	MEANING
1	Disable standalone boot
2	Boot using selected model
3	Boot using model selected by digital inputs

Returns:: True if everything ok, otherwise returns False.
Return type:: status (bool)

Availability:

standalone scripts

set_source_arbitrary_waveform(name, file)¶

Assigns an arbitrary waveform file (isg) to a given independent voltage/current source(s).

Parameters:

name (str, list) – source name or a list of source names that need to be set.
file (str, list) – absolute or relative path to the waveform file (isg extension) or list of paths to waveform files.

Returns:

True if an arbitrary waveform file is successfully assigned, otherwise returns False.

Availability:

standalone scripts
macro scripts

Example:

# prepare one by one
hil.set_source_arbitrary_waveform(
    "Va", file=r"./examples/inputs/sources/230V_50Hz_phase_a.isg")
hil.set_source_arbitrary_waveform(
    "Vb", file=r"./examples/inputs/sources/230V_50Hz_phase_b.isg")
hil.set_source_arbitrary_waveform(
    "Vc", file=r"./examples/inputs/sources/230V_50Hz_phase_c.isg")

# or set all of them
hil.set_source_arbitrary_waveform(
    name=["Va", "Vb", "Vc"],
    file=[r"./examples/inputs/sources/230V_50Hz_phase_a.isg",
          r"./examples/inputs/sources/230V_50Hz_phase_b.isg",
          r"./examples/inputs/sources/230V_50Hz_phase_c.isg"])

set_source_constant_value(name, value=0, executeAt=None, ramp_time=0, ramp_type='lin')¶

Sets a constant value to a given independent voltage/current source(s).

Parameters:

name (str, list) – source name or a list of source names.
value (float, list) – the constant value or list of constant values that need to be set.
executeAt (int, float) – executes this command at a specified simulation time. If executeAt is not specified (or executeAt == None) the command will be executed immediately.
ramp_time (int) – defines the period over which the transition is applied
ramp_type (str) – defines the transition shape. Supported values are ‘lin’ (linear interpolation) and ‘exp’ (first order system response - ramp time equals to 7 tau)

Returns:

True if a constant value is set successfully, otherwise returns False.

Availability:

standalone scripts
macro scripts

Example:

# set one source
hil.set_source_constant_value("Vdc", value=200)

# or set multiple sources
hil.prepare_source_constant_value(["Vdc", "Vab], value=[200, 100])

set_source_sine_waveform(name, rms=None, frequency=None, phase=None, harmonics=None, harmonics_pu=None, executeAt=None, ramp_time=0, ramp_type='lin')¶

Assigns a sinusoidal signal to a given independent voltage/current source(s).

Parameters:

name (str, list) – source name or a list of source names.
rms (float, list) – rms value or list of rms values.
frequency (float, list) – frequency (default 50Hz) or list of frequency values.
phase (float, list) – phase (in degrees) or list of phase values.
harmonics (list) –
list of harmonics defined in absolute units, specified as follows:

list[(harmonic_number_1,rms_1,phase_1),
…, (harmonic_number_n,rms_n,phase_n)].
harmonics_pu (list) –
list of harmonics defined in relative units, specified as follows:

list[(harmonic_number_1,rms_pu_1,phase_1),
…, (harmonic_number_n,rms_pu_n,phase_n)]

where

rms_pu_n value is harmonic rms given in relative units between 0 and 1.
executeAt (int, float) – executes this command at a specified simulation time. If executeAt is not specified (or executeAt == None) the command will be executed immediately.
ramp_time (int) – defines the period over which the transition is applied
ramp_type (str) – defines the transition shape. Supported values are ‘lin’ (linear interpolation) and ‘exp’ (first order system response - ramp time equals to 7 tau)

Note

harmonics argument is left for compatibility purposes. For all new development purposes, it is strongly recommended to use the harmonics_pu attribute instead.

Note

It is strongly recommended to use the harmonics_pu argument for specifying higher harmonic content.

Note

executeAt option is not available if the harmonics or harmonics_pu arguments are used.

Returns:: True if a sinusoidal signal is successfully assigned, otherwise returns False.

Availability:

standalone scripts
macro scripts

Example:

# list of harmonics
harmonics_pu = []

# tuples that contains harmonic settings
# (harmonic_number,rms,phase)
harmonic1 = (3, 0.1, 0)
harmonic2 = (5, 0.05, 90)
harmonic3 = (7, 0.03, 270)

# store harmonics
harmonics_pu.append(harmonic1)
harmonics_pu.append(harmonic2)
harmonics_pu.append(harmonic3)

# set one source
hil.set_source_sine_waveform("Vb", rms=220, frequency=50,
                             phase= 120, harmonics_pu=harmonics_pu)

# or set multiple sources
hil.set_source_sine_waveform(["Va", "Vb"],
                             rms=[220, 230],
                             frequency=[50, 60],
                             phase=[120, 100],
                             harmonics_pu=harmonics_pu)

set_source_scaling(name, scaling, executeAt=None, ramp_time=0, ramp_type='lin')¶

Set the source scaling factor.

Note

In case any source parameter is changed, the scaling value will be reset to 1.0.

Parameters:

name (str) – source name or a list of source names.
scaling (float, list) – new scaling factor (float value or a list of float values)
executeAt (int, float) – executes this command at specified simulation time. If executeAt is not specified (or executeAt == None) the command will be executed immediately.
ramp_time (int) – defines the period over which the transition is applied
ramp_type (str) – defines the transition shape. Supported values are ‘lin’ (linear interpolation) and ‘exp’ ( first order system response - ramp time equals to 7 tau)

Returns:

True if the source scaling factor was set successfully, otherwise returns False.

Availability:

standalone scripts
macro scripts

Example:

# get simulation step
simulationStep = hil.get_sim_step()

# calculate update (execution) times
executeAt1 = simulationStep * 100000 # execute after 100000 sim cycles

# set one source
hil.set_source_scaling("Vb", 5.0, executeAt=executeAt1)

# or set multiple sources
hil.set_source_scaling(["Vb", "Vb"], [5.0, 6], executeAt=executeAt1)

set_pv_input_file(name, file, illumination=0.0, temperature=0.0, isc=10.0, voc=100.0)¶

Assigns an IV curve to a given photovoltaic panel.

Parameters:

name (str) – name of the photovoltaic
file (str) – absolute or relative path to the PV file (.ipv or .ipvx extension).
illumination (float) – illumination value of the PV panel (float value).
temperature (float) – temperature value of the PV panel (float value).
isc (float) – current scaling factor value of PV panel (float value).
voc (float) – voltage scaling factor value of PV panel (float value).

Note

If you load a PV file with .ipv extension you will not be able to change illumination and temperature parameters. Changing these parameters is only available by loading a new version of the PV file with .ipvx extension.

Returns:: True if an IV curve was successfully assigned, otherwise returns False.

Availability:

standalone scripts
macro scripts

Example:

# setting PV using an .ipv PV file
# (in this case changing 'illumination' and 'temperature' values will
# have no effect)
hil.set_pv_input_file(
    "PV_panel",
    file=r"./examples/inputs/photovoltaics/PVFN_pv_200_wpms_20c.ipv")

# setting PV using an .ipvx PV file
# (in this case you can change 'illumination' and 'temperature' values)
hil.set_pv_input_file(
    "PV_panel",
    file=r"./examples/inputs/photovoltaics/Jinko_JKM200M-72.ipvx",
    illumination=1000.0,
    temperature=25.0)

# setting PV using an .ipvx PV file
# (in this case you can change 'isc' and 'voc' values)
hil.set_pv_input_file(
    "PV_panel",
    file=r"./examples/inputs/photovoltaics/IV_Normalized.ipvx",
    isc=10.0,
    voc=25.0)

set_pv_amb_params(name, illumination=None, temperature=None, isc=None, voc=None, executeAt=None, ramp_time=0, ramp_type='lin')¶

Change ambiental parameters of the PV panel with a given name.

Note

Before changing a PV panel’s ambiental settings you need to initialize the PV panel with an .ipvx PV settings file. To initialize a PV panel, call the set_pv_input_file() function.

Note

You can change both illumination and temperature at the same time, or only one of them. If you change only one parameter, the last set value will be used for the second parameter.

Note

In case you are using the timed command (executeAt != None), you need to wait for the first command to execute before setting the next timed command. Successive use of a timed command in this function will overwrite illumination and temperature values scheduled in the previously set timed command.

Parameters:

name (str) – name of the photovoltaic.
illumination (float) – illumination value of a PV panel (float value).
temperature (float) – temperature value of a PV panel (float value).
isc (float) – current scaling factor value of PV panel (float value).
voc (float) – voltage scaling factor value of PV panel (float value).
executeAt (int, float) – executes this command at specified simulation time. If executeAt is not specified (or ``executeAt``==None) the command will be executed immediately.
ramp_time (float) – defines the period over which the transition is applied
ramp_type (str) – defines the transition shape. Supported values are ‘lin’ (linear interpolation) and ‘exp’ (first order system response - ramp time equals to 7 tau).

Returns:

tuple(status, tuple(Imp,Vmp))

status: True if everything ok, otherwise returns False.
Imp: maximal power current.
Vmp: maximal power voltage.

Availability:

standalone scripts
macro scripts

Example:

# initialize PV using an .ipvx PV file and set the initial
# illumination and temperature values
status = hil.set_pv_input_file(
    "PV_panel",
    file=r"./examples/inputs/photovoltaics/Jinko_JKM200M-72.ipvx",
    illumination=1000.0,
    temperature=25.0)

# change both illumination and temperature parameters
(status, (Imp, Vmp)) = hil.set_pv_amb_params(
    "PV_panel", illumination = 1500.0, temperature = 30.0)

# change only illumination
# (last set temperature value will be used -> 30.0)
(status, (Imp, Vmp)) = hil.set_pv_amb_params(
    "PV_panel", illumination=1800.0)

# change only the temperature parameter
# (last set illumination value will be used -> 1800.0)
(status, (Imp, Vmp)) = hil.set_pv_amb_params(
    "PV_panel", temperature=35.0)

# change both isc and voc parameters
(status, (Imp, Vmp)) = hil.set_pv_amb_params(
    "PV_panel", isc=1500.0, voc=30.0)

# change only isc (last set voc value will be used -> 30.0)
(status, (Imp, Vmp)) = hil.set_pv_amb_params("PV_panel", isc=1800.0)

# change only the voc parameter
# (last set isc value will be used -> 1800.0)
(status, (Imp, Vmp)) = hil.set_pv_amb_params("PV_panel", voc=35.0)

# change both isc and voc parameters gradually
(status, (Imp, Vmp)) = hil.set_pv_amb_params(
    "PV_panel", isc=1500.0, voc=30.0, ramp_time=1)

# get the simulation step
simulationStep = hil.get_sim_step()

# calculate the execution time
executeAt1 = simulationStep * 100000 # execute after 100000 sim cycles

# change illumination at a specified simulation time
(status, (Imp, Vmp)) = hil.set_pv_amb_params(
    "PV_panel", illumination=2000.0, executeAt=executeAt1)

set_analog_output(channel, name=None, scaling=None, offset=None, device=0)¶

Defines signal assignment, scaling and offset for a given analog output.

Parameters:

channel (int) – analog output channel number.
name (str) – name of the analog signal.
scaling (float) – scaling value.
offset (float) – offset value.
device (int) – specifies on which device you want to set the analog output.

Returns:

True if the assignment was successful, otherwise returns False.

Availability:

standalone scripts
macro scripts

Example:

hil.set_analog_output(1, "V( V0 )", scaling=100, offset=0)

set_analog_output_signal(channel, name, device=0)¶

Defines signal assignment for a given analog output.

Parameters:

channel (int) – analog output channel number.
name (str) – name of the analog signal.
device (int) – specifies on which device you want to set the analog output signal.

Returns:

True if the assignment was successful, otherwise returns False.

Availability:

standalone scripts
macro scripts

Example:

hil.set_analog_output_signal(1,"V( V0 )")

set_analog_output_scaling(channel, scaling=0.0, device=0)¶

Defines signal scaling for a given analog output.

Parameters:

channel (int) – analog output channel number.
scaling (float) – scaling value.
device (int) – specifies on which device you want to set the analog output scaling.

Returns:

True if scaling was successfully defined, otherwise returns False.

Availability:

standalone scripts
macro scripts

Example:

hil.set_analog_output_scaling(1, scaling=100)

set_analog_output_offset(channel, offset=0.0, device=0)¶

Defines offset value for a given analog output.

Parameters:

channel (int) – analog output channel number.
offset (float) – offset value.
device (int) – specifies on which device you want to set the analog output offset.

Returns:

True if offset value was defined successfully, otherwise returns False.

Availability:

standalone scripts
macro scripts

Example:

hil.set_analog_output_offset(1, offset=0)

set_digital_output(channel, name=None, invert=None, swControl=None, value=None, device=0)¶

Defines all properties of a given digital output.

Parameters:

channel (int) – digital output channel number.
name (str) – name of assigned digital signal.
invert (bool) – if True digital output is inverted.
swControl (bool) – Defines the control mode. If True (software mode) the digital output value is defined by a value argument, otherwise the value is defined by the assigned signal (hardware mode).
value (int) – software defined value 0/1.
device (int) – specifies on which device you want to set the digital output.

Note

Invert logic will have no effect instantly if the software control mode is selected for a given digital output. Once software control is disabled, invert logic will be applied on the assigned digital signal.

Note

Changing software value will have no effect instantly if the hardware control mode is selected for a given digital output. Once hardware control is disabled, the software value will be set on the given digital output.

Returns:: True if all properties have been successfully defined, otherwise returns False.

Availability:

standalone scripts
macro scripts

Example:

hil.set_digital_output(1, name='machine encoder A',
                       invert=False, swControl=False, value=0)

set_digital_output_signal(channel, name, device=0)¶

Defines signal assignment for a given digital output.

Parameters:

channel (int) – digital output channel number.
name (str) – name of the assigned digital signal.
device (int) – specifies on which device you want to set the digital output signal.

Note

This function will have no effect instantly if the software control mode is selected for a given digital output. Once software control is disabled, the assigned digital signal will be activated.

Returns:: True if signal assignment was performed successfully, otherwise returns False.

Availability:

standalone scripts
macro scripts

Example:

hil.set_digital_output_signal(1, name='machine encoder A')

set_digital_output_inverting(channel, invert=False, device=0)¶

Defines signal inverting for a given digital output.

Parameters:

channel (int) – digital output channel number.
invert (bool) – if True the digital output is inverted.
device (int) – specifies on which device you want to set the analog output inverting state.

Note

This function will have no effect instantly if the software control mode is selected for a given digital output. Once software control is disabled, invert logic will be applied on the assigned digital signal.

Returns:: True if signal inverting process was successful, otherwise returns False.

Availability:

standalone scripts
macro scripts

Example:

hil.set_digital_output_inverting(1, invert=False)

set_digital_output_sw_control(channel, swControl=False, device=0)¶

Defines the control mode for a given digital output.

Parameters:

channel (int) – digital output channel number.
swControl (bool) – Defines the control mode. If True (software mode) the digital output value is defined by the value argument, otherwise the value is defined by the assigned signal (hardware mode).
device (int) – specifies on which device you want to set the analog output software control state.

Returns:

True if the control mode was set successfully, otherwise returns False.

Availability:

standalone scripts
macro scripts

Example:

hil.set_digital_output_sw_control(1, swControl=False)

set_digital_output_software_value(channel, value=0, device=0)¶

Specifies the value on a given digital output.

Parameters:

channel (int) – digital output channel number (from 1 to 32).
value (int) – software defined value 0/1.
device (int) – specifies on which device you want to set the analog output software value.

Note

This function will have no effect instantly if the hardware control mode is selected for a given digital output. Once hardware control is disabled, the software value will be set on the given digital output.

Returns:: True if the value was specified successfully, otherwise returns False.

Availability:

standalone scripts
macro scripts

Example:

hil.set_digital_output_software_value(1, value=0)

set_contactor(name, swControl=None, swState=None, executeAt=None)¶

Selects the control mode and defines the SW state for a given contactor.

Parameters:

name (str) – contactor name.
swControl (bool) – Defines the control mode. If True (software mode) the contactor state is defined by the swState argument. Otherwise, the contactor is controlled from the assigned digital input (hardware mode).
swState (bool) – Defines the contactor state in the SW control mode. True closed, False open.
executeAt (int, float) – executes this command at a specified simulation time. If executeAt is not specified (or executeAt == None) the command will be executed immediately.

Returns:

True if the control mode and state were successfully set, False if an error occurred.

Availability:

standalone scripts
macro scripts

Example:

# get the simulation step
simulationStep = hil.get_sim_step()

# calculate the execution time
executeAt1 = simulationStep * 100000 # execute after 100000 sim cycles

# execute the command immediately
hil.set_contactor('contactor_disch', swControl=True, swState=True)

# execute the command at a specified time
hil.set_contactor('contactor_disch', swControl=True,
                  swState=True, executeAt=executeAt1)

set_contactor_control_mode(name, swControl=False, executeAt=None)¶

Selects the control mode for a given contactor.

Parameters:

name (str) – contactor name.
swControl (bool) – Defines the control mode. If True (software mode) the contactor state is defined by the software value (see the set_contactor_state() function). Otherwise, the contactor is controlled from the assigned digital input (hardware mode).
executeAt (int, float) – executes this command at a specified simulation time. If executeAt is not specified (or ``executeAt``==None) the command will be executed immediately.

Returns:

True if the control mode was selected successfully, False if an error occurred.

Availability:

standalone scripts
macro scripts

Example:

# get the simulation step
simulationStep = hil.get_sim_step()

# calculate the execution time
executeAt1 = simulationStep * 100000 # execute after 100000 sim cycles

# execute the command immediately
hil.set_contactor_control_mode('contactor_disch', swControl = True)

# execute the command at a specified time
hil.set_contactor_control_mode('contactor_disch', swControl=True,
                               executeAt=executeAt1)

set_contactor_state(name, swState=False, executeAt=None)¶

Defines the SW state for a given contactor.

Parameters:

name (str) – contactor name.
swState (bool) – Defines the contactor state in the SW control mode.
closed (True) –
open. (False -) –
executeAt (int, float) – executes this command at a specified simulation time. If executeAt is not specified (or ``executeAt``==None) the command will be executed immediately.

Note

Changing the contactor SW state will only have effect if the contactor control mode was set to software mode (see the set_contactor_control_mode() function).

Returns:: True if the SW state was selected successfully, False if an error occurred.

Availability:

standalone scripts
macro scripts

Example:

# get the simulation step
simulationStep = hil.get_sim_step()

# calculate the execution time
executeAt1 = simulationStep * 100000 # execute after 100000 sim cycles

# execute the command immediately
hil.set_contactor_state('contactor_disch', swState = True)

# execute the command at a specified time
hil.set_contactor_state('contactor_disch',
                        swState=True, executeAt=executeAt1)

set_machine_constant_torque(name='', value=0.0, executeAt=None)¶

Sets the constant load torque for the machine in the model

Parameters:

name (str) – machine name in the model.
value (float) – constant load torque value - value unit is [Nm].
executeAt (int, float) – executes this command at a specified simulation time. If executeAt is not specified (or ``executeAt``==None) the command will be executed immediately.

Returns:

True if the load torque was set successfully, otherwise returns False.

Availability:

standalone scripts
macro scripts

Example:

# get the simulation step
simulationStep = hil.get_sim_step()

# calculate the execution time
executeAt1 = simulationStep * 100000 # execute after 100000 sim cycles

# execute the command immediately
hil.set_machine_constant_torque(name="Induction_machine1", value=5.0)

# execute the command at a specified time
hil.set_machine_constant_torque(name="Induction_machine1",
                                value=5.0, executeAt=executeAt1)

set_machine_linear_torque(name='', value=0.0, executeAt=None)¶

Sets linear load torque coefficient for the machine in the model.

Parameters:

name (str) – machine name in the model.
value (float) – linear load torque coefficient value - value unit is [Nm*s].
executeAt (int, float) – executes this command at a specified simulation time. If executeAt is not specified (or ``executeAt``==None) the command will be executed immediately.

Returns:

True if linear load torque coefficient was set successfully, otherwise returns False.

Availability:

standalone scripts
macro scripts

Example:

# get the simulation step
simulationStep = hil.get_sim_step()

# calculate the execution time
executeAt1 = simulationStep * 100000 # execute after 100000 sim cycles

# execute the command immediately
hil.set_machine_linear_torque(name="Induction_machine1", value=0.1)

# execute the command at a specified time
hil.set_machine_linear_torque(name="Induction_machine1",
                              value=0.1, executeAt=executeAt1)

set_machine_square_torque(name='', value=0.0, executeAt=None)¶

Sets square load torque coefficient for the machine in the model.

Parameters:

name (str) – machine name in the model.
value (float) – square load torque coefficient value - value unit is [Nm*s^2].
executeAt (int, float) – executes this command at a specified simulation time. If executeAt is not specified (or ``executeAt``==None) the command will be executed immediately.

Returns:

True if square load torque coefficient was set successfully, otherwise returns False.

Availability:

standalone scripts
macro scripts

Example:

# get the simulation step
simulationStep = hil.get_sim_step()

# calculate the execution time
executeAt1 = simulationStep * 100000 # execute after 100000 sim cycles

# execute the command immediately
hil.set_machine_square_torque(name="Induction_machine1", value=0.01)

# execute the command at a specified time
hil.set_machine_square_torque(name="Induction_machine1",
                              value=0.01, executeAt=executeAt1)

set_machine_load_source(name='', software=True)¶

Sets load torque source for the machine in the model (software or external).

Parameters:

name (str) – machine name in the model.
software (bool) – True if you want to use software control of the machine load torque, otherwise False for external load torque control.

Returns:

True if load torque source was set successfully, otherwise returns False.

Availability:

standalone scripts
macro scripts

Example:

hil.set_machine_load_source(name="Induction_machine1", software=True)

set_machine_external_torque_type(name='', frictional=True)¶

Sets the type of the external torque load for a machine in the model (frictional or potential).

Note

Changing external torque type is only available when the load torque source is set to ‘External’.

Parameters:

name (str) – machine name in the model.
frictional (bool) – True if you want to use the frictional type, otherwise False for the potential type.

Returns:

True if the type of the external torque load is set successfully, otherwise returns False.

Availability:

standalone scripts
macro scripts

Example:

hil.set_machine_external_torque_type(name="Induction_machine1",
                                     frictional=True)

set_machine_constant_torque_type(name='', frictional=True)¶

Sets the type of the constant load for a machine in the model (frictional or potential).

Parameters:

name (str) – machine name in the model.
frictional (bool) – True if you want to use the frictional type, otherwise ‘False’ for the potential type. The direction of frictional load is always opposite in regard to machine rotation (direction), and the direction of potential load is always the same regardless of machine rotation.

Returns:

True if the type of the constant load is set successfully, otherwise returns False.

Availability:

standalone scripts
macro scripts

Example:

hil.set_machine_constant_torque_type(name="Induction_machine1",
                                     frictional=True)

set_machine_load_type(name='', torque=True)¶

Sets the load type for a machine in the model (torque or speed).

Parameters:

name (str) – machine name in the model.
torque (float) – True if you want to use the ‘torque’ load type, otherwise False for the ‘speed’ load type.

Note

Setting the speed load type will reset all torque load types values to their initial state.

Returns:: True if the load type was set successfully, otherwise returns False

Availability:

standalone scripts
macro scripts

Example:

# set 'speed' load type
hil.set_machine_load_type(name="Induction_machine1", torque=False)

set_machine_speed(name='', speed=0.0, executeAt=None)¶

Sets the machine speed. The speed is given in rad/s.

Parameters:

name (str) – machine name in the model.
speed (float) – machine speed value given as a float value.
executeAt (int, float) – executes this command at a specified simulation time. If executeAt is not specified (or ``executeAt``==None) the command will be executed immediately.

Note

Setting the machine speed value is only possible if the machine load type is set to Speed and the machine load source is set to Software.

Returns:: True if the machine speed was set successfully, otherwise returns False.

Availability:

standalone scripts
macro scripts

Example:

# get the simulation step
simulationStep = hil.get_sim_step()

# calculate the execution time
executeAt1 = simulationStep * 100000 # execute after 100000 sim cycles

# execute the command immediately
hil.set_machine_speed(name="Induction_machine1", speed=314)

# execute the command at a specified time
hil.set_machine_speed(name="Induction_machine1",
                      speed=314, executeAt=executeAt1)

set_machine_initial_angle(name='', angle=0.0)¶

Sets the machine initial angle.

Parameters:

name (str) – machine name in the model.
angle (float) – machine angle initial value - value unit is [rad].

Returns:

True if the machine initial angle was set successfully, otherwise returns False.

Availability:

standalone scripts
macro scripts

Example:

import math
hil.set_machine_constant_torque_type(name="Induction_machine1",
                                     angle=math.pi)

set_machine_initial_speed(name='', speed=0.0)¶

Sets the machine initial speed.

Parameters:

name (str) – machine name in the model.
speed (float) – machine speed initial value - value unit is [rad/s].

Returns:

True if the machine initial speed was set successfully, otherwise returns False.

Availability:

standalone scripts
macro scripts

Example:

import math
speed_rpm = 1000
speed_init = (2*math.pi/60)*speed_rpm
hil.set_machine_initial_speed(name="Induction_machine1",
                              speed=speed_init)

set_machine_inc_encoder_offset(name='', offset=0.0)¶

Sets the incremental encoder offset in the machine model.

Note

This function now calls the set_machine_encoder_offset() function and will be deprecated soon. Please use set_machine_encoder_offset() instead.

Parameters:

name (str) – machine name in the model.
offset (float) – incremental encoder offset value.

Returns:

True if the incremental encoder offset is set successfully, otherwise returns False.

Availability:

standalone scripts
macro scripts

Example:

hil.set_machine_inc_encoder_offset(name="Induction_machine1",
                                   offset=0.0)

set_machine_sin_encoder_offset(name='', offset=0.0)¶

Sets the machine’s sinusoidal encoder and the resolver offset.

Note

This function now calls the set_machine_resolver_offset() function and will be deprecated soon. Please use set_machine_encoder_offset() or set_machine_resolver_offset() instead.

Parameters:

name (str) – machine name in the model.
offset (float) – machine’s sinusoidal encoder and the resolver offset value.

Returns:

True if the machine’s sinusoidal encoder and the resolver offset are set successfully, otherwise returns False.

Availability:

standalone scripts
macro scripts

Example:

hil.set_machine_sin_encoder_offset(name="Induction_machine1",
                                   offset=0.0)

set_machine_encoder_offset(name='', offset=0.0)¶

Sets both incremental and sinusoidal encoder offset relative to the machine’s zero angle.

Parameters:

name (str) – machine name in the model.
offset (float) – encoder offset value in radians.

Returns:

True if everything ok, otherwise returns False.

Availability:

standalone scripts
macro scripts

Example:

hil.set_machine_encoder_offset(name="Induction_machine1", offset=0.0)

set_machine_resolver_offset(name='', offset=0.0)¶

Sets resolver offset relative to the machine’s zero angle.

Parameters:

name (str) – machine name in the model.
offset (float) – machine’s resolver offset value in radians.

Returns:

True if everything ok, otherwise returns False.

Availability:

standalone scripts
macro scripts

Example:

hil.set_machine_resolver_offset(name="Induction_machine1", offset=0.0)

set_pe_switching_block_control_mode(blockName='', switchName='', swControl=True, executeAt=None)¶

Defines the control mode for a single switch in a given power electronics switching block.

Parameters:

blockName (str) – name of the power electronics switching block.
switchName (str) – switch name.
swControl (bool) – Defines the control mode. If True (software mode) the switch is controlled from software (see set_pe_switching_block_software_value() function), otherwise the value is defined by the assigned digital input (hardware mode).
executeAt (int, float) – executes this command at a specified
specified (simulation time. If executeAt is not) –
immediately. ((or ``executeAt``==None) the command will be executed) –

Returns:

True if everything ok, otherwise returns False.

Availability:

standalone scripts
macro scripts

Example:

# get the simulation step
simulationStep = hil.get_sim_step()

# calculate the execution time
executeAt1 = simulationStep * 100000 # execute after 100000 sim cycles

# execute the command immediately
hil.set_pe_switching_block_control_mode(
    blockName="3ph_inverter 1", switchName="Sa_top", swControl=True)

# execute the command at a specified time
hil.set_pe_switching_block_control_mode(
    blockName="3ph_inverter 1", switchName="Sa_top", swControl=True,
    executeAt=executeAt1)

set_pe_switching_block_software_value(blockName='', switchName='', value=0, executeAt=None)¶

Sets the state of a single switch in a given power electronics switching block.

Parameters:

blockName (str) – name of the power electronics switching block.
switchName (str) – switch name.
value (float) – software defined value (0 - switch open, 1 - switch closed).
executeAt (int, float) – executes this command at a specified
specified (simulation time. If executeAt is not) –
immediately. ((or ``executeAt``==None) the command will be executed) –

Note

This function will have no effect if the hardware control mode is selected for a given switch.

Returns:: True if the state of a single switch is set successfully, otherwise returns False.

Availability:

standalone scripts
macro scripts

Example:

# get the simulation step
simulationStep = hil.get_sim_step()

# calculate the execution time
executeAt1 = simulationStep * 100000 # execute after 100000 sim cycles

# execute the command immediately
hil.set_pe_switching_block_software_value(
    blockName="3ph_inverter 1", switchName="Sa_top", value=1)

# execute the command at a specified time
hil.set_pe_switching_block_software_value(
    blockName="3ph_inverter 1", switchName="Sa_top", value=1,
    executeAt=executeAt1)

set_initial_battery_soc(batteryName, initialValue)¶

Sets the initial value for the battery state of charge.

Note

The initial state of charge will be set on each simulation start. Changing state of charge during the simulation will have no effect.

Parameters:

batteryName (str) – battery name
initialValue (float) – state of charge initial value.

Returns:

True if the initial value for the battery state of charge is set successfully, otherwise returns False.

Availability:

standalone scripts
macro scripts

Example:

# first set the initial state of charge...
hil.set_initial_battery_soc("Ebatt", 90.0)

# ... then start the simulation (on simulation start,
# the initial state of charge will be applied)
hil.start_simulation()

set_scada_input_value(scadaInputName, value)¶

Sets the SCADA Input value.

Parameters:

scadaInputName (str) – SCADA Input name whose value you want to change
value (int, float) – the value to be set.

Returns:

True if the SCADA Input value was set successfully, otherwise returns False.

Availability:

standalone scripts
macro scripts

Example:

hil.set_scada_input_value("Sconst1.Pref", 32.00)

set_cp_input_value(cpCategory, cpGroup, cpInputName, value)¶

Sets the CP Input value.

Note

This function will be soon deprecated. Please use the set_scada_input_value() function instead.

Parameters:

cpCategory (str) – CP Input category name
cpGroup (str) – CP Input group name
cpInputName (str) – CP Input name whose value we want to change
value (int, float) – the value to be set.

Returns:

True if the CP Input value was set successfully, otherwise returns False.

Availability:

standalone scripts
macro scripts

Example:

hil.set_cp_input_value('Power load/source', "Sconst1", 'Pref', 32.00)

set_text_mode(mode)¶

Sets the mode of text messages which come from the API library (warnings,errors…).

Note

These modes do not affect messages from user scripts.

Parameters:: mode (str) – the text mode to be used.

Available modes:

RM_EMBEDDED - all text from API will be HTML text.
RM_SYSTEM - all text from API will be plain text.

The default mode is RM_EMBEDDED.

Availability:

standalone scripts

Example:

hil.set_text_mode(hil.RM_EMBEDDED)

set_debug_level(level=0)¶

Sets the level of console printing.

Parameters:

level (str) –

indicates the debug level

1 - only print messages from user scripts

2 - level 1 + print API messages

3 - level 1 + level 2 + print communication messages

Availability:

standalone scripts

start_capture(cpSettings, trSettings, chSettings, dataBuffer=None, fileName='', executeAt=None, timeout=None)¶

Starts the capture process that will in the background collect data, return them and, if fileName is specified, the data will be stored in the specified file with the appropriate extension (.mat , .h5 , .tdms, .csv…)

Note

You cannot start another capture process if the previous one has not finished.

To check if the previously started capture process has finished, use the capture_in_progress() function.

Parameters:

cpSettings (list) –
list[decimation, numberOfChannels, numberOfSamples, enableDigitalCapture]
- decimation (int): capture down-sampling value.
- numberOfChannels (int): the number of captured analog
  channels (number_of_used_hil_devices *
  
  max_number_of_analog_channels_per_hil
  >= numberOfChannels >= 1, int value).
  
  Note
  
  max_number_of_analog_channels_per_hil depends on the connected HIL device and can be 16, 32 or 64 channels. The maximum number of channels that can be captured on one HIL device must be <= max_number_of_analog_channels_per_hil.
- numberOfSamples (int): the number of captured points per
  one channel or hil.MAX_NO_SAMPLES.
  
  Note
  
  numberOfSamples per one channel depends on numberOfChannels and must be divisible by 2. The minimum number for samples per channel is 256 and the maximum number is max_number_of_samples_per_hil / numberOfChannels.
  
  Note
  
  The max_number_of_samples_per_hil depends on the connected HIL device and can be 32e6 or 64e6 samples.
  
  Note
  
  In case numberOfSamples == hil.MAX_NO_SAMPLES, maximal the number of samples will be used.
- enableDigitalCapture (bool): Enable digital signal capturing.
  
  Note
  
  In case digital capture is enabled, the max_number_of_analog_channels_per_hil is reduced by one, so that max_number_of_analog_channels = max_number_of_analog_channels_per_hil - 1.
  
  See the numberOfChannels for more info.
trSettings (list) –
list[triggerType, triggerSource, threshold, edge, triggerOffset, useFirstTriggerOccurrence]
- triggerType (str): type of trigger
(“Analog” , “Digital” or “Forced”)
Note

If you use the “Forced” triggerType you do not need to pass other triggerType’s parameters, for example:
# if we use regular "triggerType" # triggerType="Analog"... triggerSettings= ["Analog",1,80.0,"Rising edge",0.0] #...or triggerSettings= ["Analog", "V( Va )", 80.0, "Rising edge",50.0] # triggerType="Digital"... triggerSettings=["Digital", 1, 0, "Rising edge"] #...or # The unit will trigger to the digital input # 1 of the first HIL device. triggerSettings= ["Digital", "HIL0 digital input 1", 0, "Rising edge", 0] #...or # The unit will trigger to the digital input 1 # of the first HIL device. triggerSettings= ["Digital", "HIL0 digital input 1", 0, "Rising edge", 0] #..or # The unit will trigger to the digital input 1 # of the second HIL device. triggerSettings= ["Digital", "HIL1 digital input 1", 0, "Rising edge", 0] # ... and if we use 'Forced' triggerSettings=["Forced"]
- triggerSource (int, str): the channel or the name of
  a signal that will be used for triggering (int value or string value)
  Note
  
  In case triggerType == ‘Analog’:
  
  triggerSource (int): the value can be > 0
  and <= numberOfChannels if we enter the channel number.
  
  triggerSource (string): the value is
  the Analog signal name that we want to use for the trigger source. Analog Signal name must be one of the signal names from the list of signals that we want to capture (chSettings list, see below).
  
  In case triggerType == ‘Digital’:
  
  triggerSource (int): the value must be > 0
  
  triggerSource (string): the value is
  a Digital signal name that we want to use for the trigger source.
  
  In both cases:
  
  The selected trigger source must be a signal that is in the list of signals for capturing!
- threshold (float): trigger threshold.
  
  Note
  
  threshold is only used for the “Analog” type of trigger. If you use the “Digital” type of trigger, you still need to provided this parameter (for example 0.0 )
- edge (str): trigger on “Rising edge” or “Falling edge”
- triggerOffset (str): Defines the number of samples in
  percentage to capture before the trigger event (for example 20, if the numberOfSamples is 100k, 20k samples before and 80k samples after the trigger event will be captured)
- useFirstTriggerOccurrence (bool) - Defines a trigger
  behaviour when an offset is set (False - any trigger occurrence will be ignored until the offset is satisfied True - the first trigger occurrence will be used despite the desired offset)
chSettings (list) –
list[[analog signals names], [digital signals names]], list that contains the string name of Analog and Digital signals that we want to capture.

Note

The number of Analog signals that we capture (and specify in [analog signals names] list) must be equal to numberOfChannels.

The number of Digital signals that we capture (and specify in [digital signals names] list) must be <= 32.
dataBuffer (list, Queue.Queue) –
the buffer that will hold names of signals that were captured and the captured data

Note

The default type of ‘dataBuffer’ is the Python Queue.Queue() type of buffer (more details on http://docs.python.org/2/library/queue.html?highlight=queue#Queue.Queue)

The second supported type is the regular Python list. For info how you need to use this type of buffer, please see the examples below.
fileName (str) –
the desired name of file. If you do not specify this parameter, the captured data will not be written at all.

Note

For now the following file formats are supported: csv, mat, h5 (HDF5 - table format), tdms, mf4 (ASAMMDF) and cff (COMTRADE).
executeAt (int, float) – executes this command at a specified simulation time. If executeAt is not specified (or ``executeAt``==None) the command will be executed immediately.
timeout (int) – Starts a counter to abort the capture process after n seconds. When not defined, the timeout will be inf.

Returns:

in the background collected data will be saved in the file
(only if fileName is specified)
put tuple in the dataBuffer in the form:
tuple(captured_signal_names, captured_data, timeData) where arguments are:
- captured_signal_names - a regular Python list with
  string names
- captured_data - numpy.ndarray
  (more details on http://docs.scipy.org/doc/numpy/reference/generated/numpy.ndarray.html) the data matrix where the first row contains captured data for the first signal in the ‘captured_signal_names’ list, and so on.
- timeData - numpy.array that holds time data for x-axis
return True if everything ws OK and the capture process
started successfully, otherwise return False if an error occurred.

Availability:

standalone scripts

Example (using regular python list for data buffer):

import typhoon.api.hil as hil

# before starting the capture process, load the model and do
# necessary configurations

# decimation,numberOfChannels,numberOfSamples
captureSettings = [1, 3, 1e5]

# triggerType,triggerSource,threshold,edge,triggerOffset
triggerSettings = ["Analog", 1, 0.0, "Rising edge", 50.0]

# signals for capturing
channelSettings = ["V( Va )", "V( Vb )", "V( Vc )"]

# regular Python list is used for data buffer
capturedDataBuffer = []

# start capture process and if everything is ok continue...
if hil.start_capture(
    captureSettings,
    triggerSettings,
    channelSettings,
    dataBuffer=capturedDataBuffer,
    fileName=r'C:/captured_signals/capture_test.mat'):

    # when capturing is finished...
    while hil.capture_in_progress():
        pass

    # unpack data from the data buffer
    # (signalsNames - list with names,
    #  yDataMatrix  - 'numpy.ndarray' matrix with data values,
    #  xData        - 'numpy.array' with time data)
    (signalsNames, yDataMatrix, xData) = capturedDataBuffer[0]

    # unpack data for the appropriate captured signals
    Va_data = yDataMatrix[0] # first row for first signal and so on
    Vb_data = yDataMatrix[1]
    Vc_data = yDataMatrix[2]

Example (using the regular Python list for data buffer with the FirstTriggerOccurrence parameter set):

import typhoon.api.hil as hil

# before starting the capture process, load the model and do
# necessary configurations

# decimation,numberOfChannels,numberOfSamples
captureSettings = [1, 3, 1e5]

# triggerType,triggerSource,threshold,edge,triggerOffset,
# useFirstTriggerOccurrence
# useFirstTriggerOccurrence parameter is optional, and
# the default value is False
triggerSettings = ["Analog", 1, 0.0, "Rising edge", 50.0, True]

# signals for capturing
channelSettings = ["V( Va )", "V( Vb )", "V( Vc )"]

# regular Python list is used for data buffer
capturedDataBuffer = []

# start the capture process and if everything is OK continue...
if hil.start_capture(
    captureSettings,
    triggerSettings,
    channelSettings,
    dataBuffer=capturedDataBuffer,
    fileName=r'C:/captured_signals/capture_test.mat'):

    # when capturing is finished...
    while hil.capture_in_progress():
        pass

    # unpack data from the data buffer
    # (signalsNames - list with names,
    #  yDataMatrix  - 'numpy.ndarray' matrix with data values,
    #  xData        - 'numpy.array' with time data)
    (signalsNames, yDataMatrix, xData) = capturedDataBuffer[0]

    # unpack data for the appropriate captured signals
    Va_data = yDataMatrix[0] # first row for first signal and so on
    Vb_data = yDataMatrix[1]
    Vc_data = yDataMatrix[2]

Example (using regular Python list for the data buffer with stop_capture() executed):

import typhoon.api.hil as hil

# before starting the capture process, load the model and
# do necessary configurations

# decimation,numberOfChannels,numberOfSamples
captureSettings = [1, 3, 1e5]

# triggerType,triggerSource,threshold,edge,triggerOffset
triggerSettings = ["Analog", 1, 0.0, "Rising edge", 50.0]

# signals for capturing
channelSettings = ["V( Va )", "V( Vb )", "V( Vc )"]

# the regular Python list is used for the data buffer
capturedDataBuffer = []

# start the capture process and if everything is OK continue...
if hil.start_capture(
    captureSettings,
    triggerSettings,
    channelSettings,
    dataBuffer=capturedDataBuffer,
    fileName=r'C:/captured_signals/capture_test.mat'):

    # some other processing
    sleep(Time)
    # force the capture to stop
    hil.stop_capture()

    # unpack data from the data buffer
    # (signalsNames - list with names,
    #  yDataMatrix  - 'numpy.ndarray' matrix with data values,
    #  xData        - 'numpy.array' with time data)
    (signalsNames, yDataMatrix, xData) = capturedDataBuffer[0]

    # unpack data for the appropriate captured signals
    Va_data = yDataMatrix[0] # first row for first signal and so on
    Vb_data = yDataMatrix[1]
    Vc_data = yDataMatrix[2]

Example with digital signals (using regular Python list for the data buffer):

import typhoon.api.hil as hil

#  before starting the capture process, load the model and do
# necessary configurations

# decimation, numberOfChannels, numberOfSamples,
# enableDigitalCapture
captureSettings = [1, 3, 1e5, True]

# triggerType,triggerSource,threshold,edge,triggerOffset
triggerSettings = ["Digital", 1, 0.0, "Rising edge", 50.0]

# signals for capturing
channelSettings = [
    ["V( Va )", "V( Vb )", "V( Vc )"],
    ["HIL0 digital input 1", "HIL0 digital input 2",
     "HIL0 digital input 3"]]

# the regular Python list is used for the data buffer
capturedDataBuffer = []

# start the capture process and if everything is OK continue...
if hil.start_capture(
    captureSettings,
    triggerSettings,
    channelSettings,
    dataBuffer=capturedDataBuffer,
    fileName=r'C:/captured_signals/capture_test.mat'):

    # when capturing is finished...
    while hil.capture_in_progress():
        pass

    # unpack data from the data buffer
    # (signalsNames - list with names,
    #  yDataMatrix  - 'numpy.ndarray' matrix with data values,
    #  xData        - 'numpy.array' with time data)
    (signalsNames, yDataMatrix, xData) = capturedDataBuffer[0]

    # unpack data for the appropriate captured signals
    Va_data = yDataMatrix[0] # first row for first signal and so on
    Vb_data = yDataMatrix[1]
    Vc_data = yDataMatrix[2]
    Digital1_data = yDataMatrix[3]
    Digital2_data = yDataMatrix[4]
    Digital3_data = yDataMatrix[5]

Example when capturing only digital signals (using regular Python list for the data buffer):

import typhoon.api.hil as hil

#  before starting the capture process, load the model and
# do necessary configurations

# decimation, numberOfChannels, numberOfSamples,
# enableDigitalCapture
captureSettings = [1, 1, 1e5, True]

# triggerType,triggerSource,threshold,edge,triggerOffset
triggerSettings = ["Digital", 1, 0.0, "Rising edge", 50.0]
# signals for capturing
channelSettings = [
    ["V( Va )"],
    ["HIL0 digital input 1", "HIL0 digital input 2",
     "HIL0 digital input 3"]]

# the regular Python list is used for the data buffer
capturedDataBuffer = []

# start the capture process and if everything is OK continue...
if hil.start_capture(
    captureSettings,
    triggerSettings,
    channelSettings,
    dataBuffer=capturedDataBuffer,
    fileName=r'C:/captured_signals/capture_test.mat'):

    # when capturing is finished...
    while hil.capture_in_progress():
        pass

    # unpack data from the data buffer
    # (signalsNames - list with names,
    #  yDataMatrix  - 'numpy.ndarray' matrix with data values,
    #  xData        - 'numpy.array' with time data)
    (signalsNames,yDataMatrix,xData) = capturedDataBuffer[0]

    # unpack data for the appropriate captured signals
    Va_data=yDataMatrix[0] # first row for first signal and so on
    Digital1_data = yDataMatrix[1]
    Digital2_data = yDataMatrix[2]
    Digital3_data = yDataMatrix[3]

Note

When using paralleled HILs (multi-HIL model), the digital signals can be defined as:

# in this case, the digital input 1 and digital input 2 will
# be captured from the first HIL and the digital input 3
# will be captured from the second HIL
# HIL numeration : 1st HIL (HIL 0), 2nd HIL (HIL 1) etc.
channelSettings = [
    ["V( Va )", "V( Vb )", "V( Vc )"],
    ["HIL0 digital input 1", "HIL1 digital input 2",
     "HIL1 digital input 3"]]


# in this case, the digital input 1 will be captured from
the first HIL while the digital input 2 and digital input 3
# will be captured from the second HIL
# HIL numeration : 1st HIL (HIL 0), 2nd HIL (HIL 1) etc.
channelSettings = [
    ["V( Va )", "V( Vb )", "V( Vc )"],
    ["HIL0 digital input 1", "HIL1 digital input 2",
     "HIL1 digital input 3"]]

Example (using Queue.Queue() for data buffer):

import typhoon.api.hil as hil
from Queue import Queue

#  before starting the capture process, load the model and
# do necessary configurations

# decimation,numberOfChannels,numberOfSamples
captureSettings = [1, 3, 1e5]

# triggerType,triggerSource,threshold,edge,triggerOffset
triggerSettings = ["Analog", 1, 0.0, "Rising edge", 50.0]

# signals for capturing
channelSettings = ["V( Va )", "V( Vb )", "V( Vc )"]

# Queue.Queue() is used for data buffer
capturedDataBuffer = Queue()

# start the capture process and if everything is OK continue...
if hil.start_capture(
    captureSettings,
    triggerSettings,
    channelSettings,
    dataBuffer=capturedDataBuffer,
    fileName=r'C:/captured_signals/capture_test.mat'):

    # when capturing is finished...
    while hil.capture_in_progress():
        pass

    # unpack data from the data buffer
    # (signalsNames - list with names,
    #  yDataMatrix  - 'numpy.ndarray' matrix with data values,
    #  xData        - 'numpy.array' with time data)
    (signalsNames, yDataMatrix, xData) =
        capturedDataBuffer.get_nowait()

    # unpack data for the appropriate captured signals
    Va_data = yDataMatrix[0] # first row for first signal and so on
    Vb_data = yDataMatrix[1]
    Vc_data = yDataMatrix[2]

Example (using executeAt):

# calculate the execution time
# execute after 100000 simulation cycles
executeAt1 = simulationStep * 100000

# execute the start capture command at a specified time
if hil.start_capture(
    captureSettings,
    triggerSettings,
    channelSettings,
    dataBuffer=capturedDataBuffer,
    fileName=r'C:/captured_signals/capture_test.mat',
    executeAt=executeAt1):

    # when capturing is finished...
    while hil.capture_in_progress():
        pass

Example (using timeout):

# the capture process will be aborted after 5 seconds.
if hil.start_capture(
    captureSettings,
    triggerSettings,
    channelSettings,
    dataBuffer=capturedDataBuffer,
    fileName=r'C:/captured_signals/capture_test.mat',
    timeout=5):

    # when capturing is finished...
    while hil.capture_in_progress():
        pass

Note

If the trigger is set to “Forced”, the timeout value will be ignored even if it is entered.

stop_capture()¶

Stops the capture process.

Note

All data that was captured by a HIL device prior capture process is stopped and are going to be downloaded.

Returns:: True if capture stopped successfully, otherwise if an error occurred returns False.

Availability:

standalone scripts

Example:

# start capture...

# ...do some configuration after the capture process is started...

# ...stop the capture process
hil.stop_capture()

start_simulation()¶

Starts the simulation process.

Returns:: True if the simulation started successfully, otherwise if an error occurred returns False.

Availability:

standalone scripts

Example:

# load model...

# ...do some configuration before we start the simulation...

# ...start the simulation...
hil.start_simulation()

# ...do some configuration after the simulation process is started...

stop_simulation()¶

Stops the simulation.

Returns:: True if the simulation stopped successfully, otherwise if an error occurred returns False.

Availability:

standalone scripts

Example:

# start simulation...

# ...do some configuration after simulation process is started...

# ...stop the simulation
hil.stop_simulation()

is_simulation_running()¶

Returns:

True if simulation is running otherwise return False.
In case model is not loaded None will be returned.

Availability:

standalone scripts
macro scripts
signal monitoring expressions

check_hil_hwid()¶

Check hardware IDs of all connected HIL devices.

Returns:

True if all HWIDs of all connected HILs are correct: otherwise False will be returned.

Return type:

status (bool)

Availability:

standalone scripts
macro scripts
signal monitoring expressions

capture_in_progress()¶

Returns:: True if the capture process is still in progress.

Availability:

standalone scripts

timeout_occurred()¶

Returns:: True if the capture is timed out, otherwise returns False.

Availability:

standalone scripts

read_pv_iv_curve(name, voltage)¶

Gets the current and power value from the PV panel I-V curve that corresponds to a given voltage value.

Note

Current and power values are only available after the PV panel is initialized. Therefore, before using this function, you need to initialize the PV panel with an .ipvx or .ipv PV settings file. To initialize the PV panel, call the set_pv_input_file() function.

Parameters:

name (str) – name of the photovoltaic.
voltage (float) – voltage value

Returns:

tuple(status, tuple(I,P)).

status - True if everything ok, otherwise returns False.
I - I-V current.
P - I-V power voltage.

Availability:

standalone scripts
macro scripts
signal monitoring expressions

Example:

# initialize a PV using an .ipvx PV file and set the initial
# illumination and temperature values
status = hil.set_pv_input_file(
    "PV_panel",
    file=r"./examples/inputs/photovoltaics/Jinko_JKM200M-72.ipvx",
    illumination=1000.0,
    temperature=25.0)

# get the current and power when voltage = 30
(status,(I,P)) = hil.read_pv_iv_curve("PV_panel",30)

read_analog_signal(name='')¶

Reads the selected analog signal value from HIL.

Parameters:: name (str) – name of the analog signal.
Returns:: Signal value (floating point), in case of a read error returns None.

Availability:

standalone scripts
macro scripts
signal monitoring expressions

Example:

sigVal = hil.read_analog_signal(name = "V( Vab )")

read_analog_signals(signals=())¶

Reads the selected analog signals values from HIL.

Parameters:: signals (list) – list of the analog signals names.
Returns:: list with signal values (floating point), in case of a read error returns None.

Availability:

standalone scripts
macro scripts
signal monitoring expressions

Example:

# return a list with requested signal values
# [V( Vab ) value, V (Vbc) value, I (Ib) value]
signalValues = hil.read_analog_signals(
    signals=["V( Vab )", "V (Vbc)", "I (Ib)"])

read_digital_signal(name='', device=None)¶

Reads the selected digital signal value from HIL.

Parameters:

name (str) – name of the digital signal.
device (int) – specifies from which device you want to read digital signal. By default, the signal will be searched on all devices.

Returns:

Signal value (int type), in case of a read error returns None.

Availability:

standalone scripts
macro scripts
signal monitoring expressions

Example:

# read 'HIL0 digital input 1' digital signal (it will be searched
# on all devices)
sigVal=hil.read_digital_signal(name="HIL0 digital input 1")

# now read the machine encoder A from the device with "device id"==1
sigVal = hil.read_digital_signal(name="machine encoder A", device=1)

read_digital_signals(signals=())¶

Reads the selected digital signals values from the HIL device.

Parameters:: signals (list) – list of digital signal names.
Returns:: A list with signal values (int type), in case of a read error returns None.

Availability:

standalone scripts
macro scripts
signal monitoring expressions

Example:

# return a list with the requested signal values
signalValues = hil.read_digital_signals(
    signals=["HIL0 digital input 1", "machine encoder A",
             "HIL1 digital input 13"])

read_digital_input(pinNum=1, device=0)¶

Reads the selected digital input value from the HIL device.

Parameters:

pinNum (int) – pin number (the channel number from 1 to 32).
device (int) – specifies from which device you want to read the digital input.

Returns:

The digital input value (int value), in case of a read error returns None.

Availability:

standalone scripts
macro scripts
signal monitoring expressions

Example:

digVal = hil.read_digital_input(pinNum = 23)

read_streaming_signals(signals, from_last_index=0)¶

Reads data from last selected index of selected streaming signals values from HIL.

Parameters:

signals (list) – of streaming signals names.
from_last_index (int) –
from which index reading should start

Note

from_last_index arg in some case can be overwritten.

Note

All signals specified must have the same execution rate.

Returns:

Pandas (DataFrame) with signal names as keys and signal values(floating point) and time column with simulation time, and index of last read data. In case of read error returns None.

Example:

# read
data, last_index = hil.read_streaming_signals(['streaming_signal_name',
'streaming signal_name2'])
# get values from pandas DataFrame
streaming_signal_name_value = data['streaming_signal_name']
streaming_signal_name_2_value = data['streaming_signal_name2']

Availability:

standalone scripts
macro scripts
signal monitoring expressions

load_signal_gen_data(filename: str) → dict¶

Loads data from a file and prepares it for a signal generator. :param filename: file path.

Returns: Dictionary with a data loaded from a file.

create_signal_stimulus(signal_data)¶

Create signal generator object. :param signal_data: data used for a signal reproduction.

Signal names are represented as dictionary keys and signal values are represented as list of numbers. Time axis is defined with dictionary key ‘Time’ and time values are represented as list of ascending numbers. All signals values need to have the same size.

Returns: ObjectHandle for created signal generator.

prepare_signal_stimulus(signal_stimulus)¶

Prepare initial data for signal stimulus. It is necessary to call this function before starting signal stimulation. For creating signal_stimulus data, create_signal_stimulus() can be used.

Parameters:: signal_stimulus (Dictionary) – stimulus to prepare.
Returns:: True if everything ok, otherwise returns False.
Return type:: status (bool)

start_signal_stimulus(signal_stimulus)¶

Start desired signal stimulus. :param signal_stimulus: signal stimulus object. :type signal_stimulus: ItemHandle

Returns:: True if everything ok, otherwise returns False.
Return type:: status (bool)

Example:

# read

stimulus_example = hil.create_signal_stimulus(

{‘Time’[data_array],: ‘signal_name1’:[data_array], ‘signal_name2’:[data_array]}

)

hil.prepare_signal_stimulus(stimulus_example) hil.start_simulation() hil.start_signal_stimulus(stimulus_example)

stop_signal_stimulus(signal_stimulus)¶

Stop desired signal stimulus. :param signal_stimulus: signal stimulus object. :type signal_stimulus: ItemHandle

Returns:: True if everything ok, otherwise returns False.
Return type:: status (bool)

Example:

# previous created stimulus 'stimulus_example'

hil.stop_signal_stimulus(stimulus_example) hil.stop_simulation()

pause_signal_stimulus(signal_stimulus)¶

Pause desired signal stimulus. :param signal_stimulus: signal stimulus object. :type signal_stimulus: ItemHandle

Returns:: True if everything ok, otherwise returns False.
Return type:: status (bool)

Example:

# previous created stimulus ‘stimulus_example’ hil.pause_signal_stimulus(stimulus_example) hil.stop_simulation()

reboot_hil()¶

Reboots all connected HIL devices.

Note

After rebooting a HIL, model (.cpd file) should be loaded again.

Returns:: True if everything ok, otherwise returns False.
Return type:: status (bool)

Availability:

standalone scripts

wait_sec(sec)¶

Waits for a specified time in seconds.

Availability:

standalone scripts
macro scripts

Example:

# ...some code

# pause execution for 3 seconds
hil.wait_sec(3)

# ...code after wait_sec() command will be executed after
# 'waiting' period is expired

wait_msec(msec)¶

Waits for a specified time in milliseconds.

Availability:

standalone scripts
macro scripts

Example:

# ...some code

# pause execution for 500 milliseconds
hil.wait_msec(500)

# ...code after wait_msec() command will be executed after
# 'waiting' period is expired

wait_on_user()¶

Waits on a user action - ‘ENTER’ needs to be pressed to continue with the script execution.

Availability:

standalone scripts

Example:

# ...some code

# pause execution until the user presses 'ENTER'
hil.wait_on_user()

# ...code after wait_on_user() command will be executed immediately
# after user presses 'ENTER'

end_script_by_user()¶

Terminates the script execution by pressing ‘ENTER’.

Availability:

standalone scripts

Example:

# ...some code

# ends the execution of the current script by pressing 'ENTER'
hil.end_script_by_user()

# after the user presses 'ENTER', the script execution will
# be terminated...and any commands after end_script_by_user()
# command will not be executed

reset_flag_status(flag, device=0)¶

Resets the status of a given flag.

Parameters:

flag (str) – name of the flag whose status you want to reset.
device (int) – specifies on which device you want to reset the flag status.

Supported flags (which can be used in the flaq parameter) and their description is listed below.

Flag constant	Description
FL_ARITHMETIC_OVERFLOW	Indicates that some values from the model being simulated were out of the HIL device’s numerical range. It may be followed by erratic model behavior.
FL_DEAD_TIME	Indicates a shoot-through condition on a phase lag caused by gate drive digital inputs.
FL_SP_EXC_OCCURRED	Indicates that an exception is thrown by the generated code running on either System or User CPU.
FL_COMP_INT_OVERRUN	Indicates that SP computation time exceeded the reserved time slot.

Returns:: True if the flag is reset successfully , otherwise returns False.

Availability:

standalone scripts
macro scripts
signal monitoring expressions

Example:

import typhoon.api.hil as hil

# reset Dead Time flag status
status = hil.reset_flag_status(hil.FL_DEAD_TIME)

get_model_variables(name_separator='.')¶

Returns all Model variables and theirs Attributes values from loaded Model.

Parameters:

name_separator (str) –

separator used to divide Model variable name’s components. All Model variables’ names will use this separator. Currently supported separators are: “.”, “/”

Example:

# name of a Model variable with default '.' separator
{"PV_panel.illumination": {
    "att_value_type": "float",
    "att_access_rights": "write_only",
    "att_hil_device": 0},
"Vgrid.rms": {
    "att_value_type": "float",
    "att_access_rights": "write_only",
    "att_hil_device": 0},
...
}

# name of a Model variable with '/' separator
{"PV_panel/illumination": {
    "att_value_type": "float",
    "att_access_rights": "write_only",
    "att_hil_device": 0},
"Vgrid/rms": {
    "att_value_type": "float",
    "att_access_rights": "write_only",
    "att_hil_device": 0},
...
}

Returns:

dictionary in format:

{"variable_name_1": {
    "attribute_name_1": attribute_value_1,
    "attribute_name_2": attribute_value_2, ...}
}
"variable_name_2": {
    "attribute_name_1": attribute_value_1,
    "attribute_name_2": attribute_value_2, ...}
}, ...}

Return type:

variable dictionary (dict)

Raises:

HILAPIException – in case information about available Model variables cannot be acquired.
HILAPIException – in case unsupported separator was given.

get_cp_output_value(cpCategory, cpGroup, cpOutputName)¶

Gets, i.e. reads, the CP Output value.

Note

This function will be soon deprecated. Please use the get_scada_output_value() instead.

Parameters:

cpCategory (str) – CP Output category name
cpGroup (str) – CP Output group name
cpOutputName (str) – CP Output name whose value you want to read

Returns:

The value read from the CP Output if everything is OK, otherwise returns None.

Availability:

standalone scripts
macro scripts
signal monitoring expressions

Example:

hil.get_cp_output_value('Power load/source','Sconst1",'Active power')

get_scada_output_value(scadaOutputName)¶

Gets the SCADA Output value.

Parameters:: scadaOutputName (str) – SCADA Output name whose value you want to read
Returns:: The value read from the SCADA Output if everything is OK, otherwise returns None.

Availability:

standalone scripts
macro scripts
signal monitoring expressions

Example:

value = hil.get_scada_output_value('Sconst1.Active power')

get_battery_soc(batteryName)¶

Gets, i.e. reads, the battery’s state of charge.

Note

The state-of-charge value will be returned in a range between 0.0 and 1.0.

Parameters:: batteryName (str) – battery name
Returns:: The state-of-charge value if everything is OK, otherwise returns None.

Availability:

standalone scripts
macro scripts
signal monitoring expression

Example:

# get the battery's state of charge
hil.get_battery_soc("Ebatt")

get_pv_mpp(name)¶

Gets, i.e. reads, the maximal power current and voltage for the given photovoltaic panel.

Note

The maximal power and current are only available after the PV panel is initialized. Therefore, before using this function you need to initialize the PV panel with an .ipvx or .ipv PV settings file. To initialize the PV panel, call the set_pv_input_file() function.

Parameters:

name (str) – name of the photovoltaic.

Returns:

tuple(status, tuple(Imp,Vmp)).

status - True if everything is OK, otherwise returns
False.
Imp - maximal power current.
Vmp - maximal power voltage.

Availability:

standalone scripts
macro scripts
signal monitoring expressions

Example:

# initializes the PV using an .ipvx PV file and sets the initial
# illumination and temperature values
status = hil.set_pv_input_file(
    "PV_panel",
    file = r"./examples/inputs/photovoltaics/Jinko_JKM200M-72.ipvx",
    illumination = 1000.0,
    temperature = 25.0)

# changes both the illumination and temperature parameters
(status,(Imp,Vmp)) = hil.get_pv_mpp("PV_panel")

get_num_of_connected_hils()¶

Returns the number of currently connected HIL devices.

Returns:: int

get_sim_step(device=0)¶

Gets the simulation time step of the active model.

Parameters:: device (int) – specifies for which device you want to get the simulation time step
Returns:: The simulation time step in seconds (floating value). If an error occurred None will be returned instead.

Availability:

standalone scripts
macro scripts
signal monitoring expressions

Example:

simulationStep = get_sim_step()

get_sim_time(device=0)¶

Gets the simulation time. The simulation time is read as a number of elapsed simulation steps (cycles) multiplied with the model simulation step.

Parameters:: device (int) – specifies for which device you want to get the simulation time
Returns:: The simulation time value (float value), in case of an error returns None.

Availability:

standalone scripts
macro scripts
signal monitoring expressions

Example:

simulationTime = get_sim_time()

get_device_cfg_list()¶

Returns the list of available devices and their FW configurations.

Returns:: Dictionary of available devices (keys) with a list of their FW configurations (values).

Availability:

standalone scripts
macro scripts
signal monitoring expressions

get_sw_version()¶

Returns a string which contains the Typhoon software version.

Returns:: A string that contains the current software version

Availability:

standalone scripts
macro scripts
signal monitoring expressions

get_hil_calibration_date(device_id=0)¶

Returns the calibration date of the connected HIL device.

Parameters:: device_id (int) – specifies for which device you want to get the calibration date. By default, the calibration date is returned for the device with device_id == 0.
Returns:: A string that contains the HIL device calibration date or ‘’None’’ if the device does not exist.

Availability:

standalone scripts
macro scripts
signal monitoring expressions

get_device_features(device=None, conf_id=None, feature=None)¶

Provides information about the features of the selected HIL device.

Parameters:

device (str) – HIL device name (in format ‘HIL604’, ‘HIL402’…)
conf_id (int) – HIL configuration id
feature (str) – feature name whose value will be returned. If feature is not provided, information about all features will be returned.

Note

In case either the parameter device or conf_id is not specified, unspecified parameter(s) will be auto-detected from the connected HIL device.

Returns:

If feature is not defined, returns a dictionary with all available features (keys) and their values. However, if feature is defined, it returns the value of the specific feature.

In case an error occurred, None will be returned.

The format of the returned dictionary is displayed below.

Availability:

standalone scripts
macro scripts
signal monitoring expressions

get_hw_info()¶

Gets hardware information of the connected HIL unit.

Note

This function will return information about connected HIL device only if it is called after model is loaded.

Returns:

tuple(product ID, device ID, configuration ID,

Firmware release date).

If an error occurred None will be returned instead.

product ID (str): product ID in the format “HIL402, HIL604…”.
device ID (int): HIL device ID.
configuration ID (int): HIL configuration ID.
Firmware release date (str): Firmware release date in
the “year-month-day” format .

Availability:

standalone scripts
macro scripts
signal monitoring expressions

Example:

(productID, deviceID, configurationID, fwReleaseDate) =
    hil.get_hw_info()

get_flag_status(flag, device=0)¶

Reads and returns the status of the given flag from the HIL device.

Parameters:

flag (str) – name of the flag whose status you want to read.
device (int) – specifies from which device you will read the flag.

Supported flags and their descriptions are listed below.

Flag constant	Description
FL_ARITHMETIC_OVERFLOW	Indicates that some values from the model being simulated were out of HIL device numerical range. It may be followed by erratic model behavior.
FL_DEAD_TIME	Indicates shoot through condition on a phase lag caused by gate drive digital inputs.
FL_SERIAL_LINK	Indicates that serials link between HIL devices is down.
FL_COMP_INT_OVERRUN	Indicates that SP computation time exceeded the reserved time slot.
FL_SP_CPU_STALLED	Indicates that SP CPU is stalled during execution.
FL_SP_EXC_OCCURRED	Indicates that an exception is thrown by the generated code running on either System or User CPU.
FL_PSU_STATUS	Indicates status of the externally available power supply outputs.

Returns:: True if a flag is raised, otherwise returns False. In case an error occurred, an appropriate message will be displayed and None will be returned.

Availability:

standalone scripts
macro scripts
signal monitoring expressions

Example:

import typhoon.api.hil as hil

# get the dead time violation flag status
dtv_flag = hil.get_flag_status(hil.FL_DEAD_TIME)

get_sources()¶

Returns the list of all independent voltage/current sources in the model.

Returns:: List of source names grouped by HIL device if everything is OK, otherwise returns an empty list.

Note

The returned list will be in the following format: [[device 0 sources], [device 1 sources], …[device N sources]] where [device N sources] is [source_1_name, source_2_name, … source_n_name]

Availability:

standalone scripts
macro scripts
signal monitoring expressions

Example:

import typhoon.api.hil as hil

# get the list of all source names in the loaded model
sources = hil.get_sources()

get_pvs()¶

Returns the list of all photovoltaic panels in the model.

Returns:: List of pvs names grouped by HIL device if everything is OS, otherwise returns an empty list.

Note

The returned list will be in the following format: [[device 0 pvs], [device 1 pvs], …[device N pvs]] where [device N pvs] is [pvs_1_name, pvs_2_name, … pvs_n_name]

Availability:

standalone scripts
macro scripts
signal monitoring expressions

Example:

import typhoon.api.hil as hil

# get the list of all pvs names in the loaded model
pvs = hil.get_pvs()

get_analog_signals()¶

Returns the list of all analog signals in the model.

Returns:: List of analog signal names grouped by HIL device if everything is OK, otherwise returns an empty list.

Note

The returned list will be in the following format: [[device 0 analog signals], [device 1 analog signals], … [device N analog signals]] where [device N analog signals] is [a_sig_1_name, a_sig_2_name, … a_sig_n_name]

Availability:

standalone scripts
macro scripts
signal monitoring expressions

Example:

import typhoon.api.hil as hil

# get the list of all analog signal names in the loaded model
analogSignals = hil.get_analog_signals()

get_digital_signals()¶

Returns the list of all digital signals in the model.

Returns:: List of digital signal names grouped by HIL device if everything is OK, otherwise returns an empty list.

Note

The returned list will be in the following format: [[device 0 digital signals], [device 1 digital signals], … [device N digital signals]] where [device N digital signals] is [d_sig_1_name, d_sig_2_name, … d_sig_n_name]

Availability:

standalone scripts
macro scripts
signal monitoring expressions

Example:

import typhoon.api.hil as hil

# get the list of all digital signal names in the loaded model
digitalSignals = hil.get_digital_signals()

get_streaming_analog_signals()¶

Returns the list of all streaming analog signals in the model.

Returns:

of streaming analog signals names grouped by HIL: device if everything ok, otherwise returns empty list.

Return type:

signals (list)

Note

Returned list will be in the format:

[[device 0 streaming analog signals],: [device 1 streaming analog signals], …, [device N streaming analog signals]]

where [device N streaming analog signals] is [a_sig_1_name, a_sig_2_name, … a_sig_n_name]

Availability:

standalone scripts
macro scripts
signal monitoring expressions

Example:

import typhoon.api.hil as hil

# get list of all streaming analog signals names in the loaded model
streaming_analog_signals = hil.get_streaming_analog_signals()

get_streaming_digital_signals()¶

Returns the list of all streaming digital signals in the model.

Returns:: of streaming digital signals names grouped by HIL device if everything ok, otherwise returns empty list.
Return type:: signals (list)

Note

Returned list will be in the format:

[[device 0 streaming digital signals],: [device 1 streaming digital signals], …, [device N streaming digital signals]]

where [device N streaming digital signals] is [d_sig_1_name, d_sig_2_name, … d_sig_n_name]

Availability:

standalone scripts
macro scripts
signal monitoring expressions

Example:

import typhoon.api.hil as hil

# get list of all streaming digital signals names in the loaded model
streaming_digital_signals = hil.get_streaming_digital_signals()

get_contactors()¶

Returns the list of all contactors in the model.

Returns:: List of contactor names grouped by HIL device if everything is OK, otherwise returns an empty list.

Note

The returned list will be in the following format: [[device 0 contactors], [device 1 contactors], [device N contactors]] where [device N contactors] is [cont_1_name, cont_2_name, … cont_n_name]

Availability:

standalone scripts
macro scripts
signal monitoring expressions

Example:

import typhoon.api.hil as hil

# get the list of all contactor names in the loaded model
contactors = hil.get_contactors()

get_machines()¶

Returns the list of all machines in the model.

Returns:: List of machine names grouped by HIL device if everything is OK, otherwise returns an empty list.

Note

The returned list will be in the following format: [[device 0 machines], [device 1 machines], …[device N machines]] where [device N machines] is [mch_1_name, mch_2_name, … mch_n_name]

Availability:

standalone scripts
macro scripts
signal monitoring expressions

Example:

import typhoon.api.hil as hil

# get the list of all machine names in the loaded model
machines = hil.get_machines()

get_pe_switching_blocks()¶

Returns the list of all software controllable power electronics switching blocks in the model.

Returns:: List of software controllable power electronics switching block names grouped by HIL device if everything is OK, otherwise returns an empty list.

Note

The returned list will be in the following format: [[device 0 sw_blocks], [device 1 sw_blocks], …[device N sw_blocks]] where [device N sw_blocks] is [swch_1_name, swch_2_name, … swch_n_name]

Availability:

standalone scripts
macro scripts
signal monitoring expressions

Example:

import typhoon.api.hil as hil

# get the list of all switching block names in the loaded model
switchingBlocks = hil.get_pe_switching_blocks()

get_scada_inputs()¶

Returns the list of all SCADA inputs in the model.

Returns:: List of SCADA input names grouped by HIL device if everything is OK, otherwise returns an empty list.

Note

The returned list will be in the following format: [[device 0 scada_inputs], [device 1 scada_inputs], …, [device N scada_inputs]] where [device N scada_inputs] is [scada_input_1_name, scada_input_2_name, … scada_input_n_name]

Availability:

standalone scripts
macro scripts
signal monitoring expressions

Example:

import typhoon.api.hil as hil

# get the list of all SCADA input names in the loaded model
scada_inputs = hil.get_scada_inputs()

get_scada_outputs()¶

Returns the list of all SCADA outputs in the model.

Returns:: List of SCADA output names grouped by HIL device if everything is OK, otherwise returns an empty list.

Note

The returned list will be in the following format: [[device 0 scada_outputs], [device 1 scada_outputs], …, [device N scada_outputs]] where [device N scada_outputs] is [scada_output_1_name, scada_output_2_name, … scada_output_n_name]

Availability:

standalone scripts
macro scripts
signal monitoring expressions

Example:

import typhoon.api.hil as hil

# get the list of all SCADA output names in the loaded model
scada_outputs = hil.get_scada_outputs()

get_source_settings(name)¶

Returns the settings parameters of the source with the given name.

Parameters:: name (str) – Name of a source
Returns:: Dictionary with the source settings or None if the source with the given name cannot be found.

Dictionary key	Meaning	Value
“source_type”	Type of Source	string (“One Phase Source”, “Two Phase Source” or “Three Phase Source”)
“input_type”	Type of Source input	string (“Arbitrary”, “Constant” or “Sine”)
“scaling_value”	Source scaling value	float

Depending on the source_type and input_type, additional settings parameters are:

One Phase Source source

Arbitrary input type

Dictionary key

Meaning

Value

“file”

Full path to a waveform file

string

Constant input type

Dictionary key

Meaning

Value

“value”

Constant value

float

Sine input type

Dictionary key

Meaning

Value

“rms”

Signal RMS value

float

“frequency”

Signal frequency

float

“phase”

Signal phase

float

“harmonics_active”

Are harmonics active?

bool

“harmonics”

List of harmonics defined in absolute units

list [(harmonic_number_1,rms_1,phase_1),…(harmonic_number_n,rms_n,phase_n)].

“harmonics_pu”

List of harmonics defined in relative units

list [(harmonic_number_1,rms_pu_1,phase_1),…(harmonic_number_n,rms_pu_n,phase_n)]

Two Phase Source and Three Phase Source source type have
the same settings parameters as when the One Phase Source with Sine input type is used

Availability:

standalone scripts
macro scripts
signal monitoring expressions

Example:

# list of harmonics
harmonics_pu = []

# tuples that contains harmonic settings
# (harmonic_number,rms,phase)
harmonic1 = (3, 0.1, 0)
harmonic2 = (5, 0.05, 90)
harmonic3 = (7, 0.03, 270)

# store harmonics
harmonics_pu.append(harmonic1)
harmonics_pu.append(harmonic2)
harmonics_pu.append(harmonic3)

# set a three-phase source
hil.set_source_sine_waveform(
    "Vb", rms=250, frequency=50, phase=120, harmonics_pu=harmonics_pu)

# get source settings parameters
source_settings = hil.get_source_settings("Vb")

# unpack parameters from dictionary
source_type = source_settings["source_type"]
input_type = source_settings["input_type"]
rms = source_settings["rms"]
frequency = source_settings["frequency"]
phase = source_settings["phase"]
harmonics_active = source_settings["harmonics_active"]
harmonics = source_settings["harmonics"]
harmonics_pu = source_settings["harmonics_pu"]

get_pv_panel_settings(name)¶

Returns the settings parameters of the PV panel with the given name.

Parameters:

name (str) – Name of a PV panel

Returns:

Dictionary with the PV panel settings, or None if the PV panel with: the given name cannot be found.

Dictionary key	Meaning	Value
“file”	Full path to the PV panel initialization file (old .ipv or new .ipvx)	string
“illumination”	Illumination value of the PV panel	float
“temperature”	Temperature value of the PV panel	float
“isc”	current scaling factor value of PV panel \| float
“voc”	voltage scaling factor value of PV pane \| float

Availability:

standalone scripts
macro scripts
signal monitoring expressions

Example:

# initialize the PV using an .ipvx PV file and set the initial
# illumination and temperature values
status = hil.set_pv_input_file(
    "PV_panel",
    file=r"./examples/inputs/photovoltaics/Jinko_JKM200M-72.ipvx",
    illumination=1000.0,
    temperature=25.0)

# or use this for IV normalized generator
 status = hil.set_pv_input_file(
    "PV_panel",
    file=r"./examples/inputs/photovoltaics/IV_Normalized.ipvx",
    isc=10.0,
    voc=25.0)

# get the PV panel settings parameters
pv_settings = hil.get_pv_panel_settings("PV_panel")

# unpack the parameters from the dictionary
pv_file = pv_settings["file"]
illumination = pv_settings["illumination"]
temperature = pv_settings["temperature"]
voc = pv_settings["voc"]
isc = pv_settings["isc"]

get_machine_settings(name)¶

Returns settings parameters of a machine with the given name.

Parameters:: name (str) – Name of a machine
Returns:: Dictionary with the machine settings or None if the machine with the given name cannot be found.

Dictionary key	Meaning	Value
“load_source”	Machine torque load source	String (“Software” or “External”)
“load_type”	Machine load type	String (“Torque” or “Speed”)
“external_torque_type”	Machine external torque load type	String ( “Frictional” or “Potential”)
“speed”	Machine speed	float
“constant_torque”	Machine constant load torque	float
“constant_torque_type”	Machine constant load torque type	String ( “Frictional” or “Potential”)
“linear_torque”	Machine linear load torque coefficient	float
“square_torque”	Machine square load torque coefficient	float
“initial_angle”	Machine initial angle	float
“initial_speed”	Machine initial speed	float
“inc_encoder_offset”	Machine incremental encoder offset	float
“sin_encoder_offset”	Machine sinusoidal encoder and resolver offset	flaot

Availability:

standalone scripts
macro scripts
signal monitoring expressions

Example:

# initialize the machine
hil.set_machine_load_source(name="machine 1", software=True)
hil.set_machine_load_type(name="machine 1", torque=True)
hil.set_machine_constant_torque(name="machine 1", value=2.5)
hil.set_machine_constant_torque_type(name="machine 1", frictional=True)
hil.set_machine_linear_torque(name="machine 1", value=5.0)
hil.set_machine_square_torque(name="machine 1", value=6.0)
hil.set_machine_initial_angle(name="machine 1", angle=3.14)
hil.set_machine_initial_speed(name="machine 1", speed=100.0)
hil.set_machine_encoder_offset(name="machine 1", offset=3.14)
hil.set_machine_sin_encoder_offset(name="machine 1", offset=1.57)

# get the machine settings parameters
machine_settings = hil.get_machine_settings("machine 1")

# unpack the parameters from the dictionary
load_source = machine_settings["load_source"]
load_type = machine_settings["load_type"]
external_torque_type = machine_settings["external_torque_type"]
speed = machine_settings["speed"]
constant_torque = machine_settings["constant_torque"]
constant_torque_type = machine_settings["constant_torque_type"]
linear_torque = machine_settings["linear_torque"]
square_torque = machine_settings["square_torque"]
initial_angle = machine_settings["initial_angle"]
initial_speed = machine_settings["initial_speed"]
inc_encoder_offset = machine_settings["inc_encoder_offset"]
sin_encoder_offset = machine_settings["sin_encoder_offset"]

get_pe_switching_block_settings(blockName='', switchName='')¶

Returns settings parameters of a single switch in a given power electronics switching block.

Parameters:

blockName (str) – name of the power electronics switching block.
switchName (str) – the name of the switch .

Returns:

Dictionary with the switch settings, or None if the switch with the given name cannot be found.

Dictionary key	Meaning	Value
“software_control_enabled”	Is software mode for a single switch in a power electronics switching block active?	boolean
“software_value”	State of a single switch in a power electronics switching block	int

Availability:

standalone scripts
macro scripts
signal monitoring expressions

Example:

# initialize switching blocks
hil.set_pe_switching_block_control_mode(
    blockName="3ph_inverter 1", switchName="Sa_top", swControl=True)
hil.set_pe_switching_block_software_value(
    blockName="3ph_inverter 1", switchName="Sa_top", value=1)

# get the switch settings parameters
switch_settings = hil.get_pe_switching_block_settings(
    blockName="3ph_inverter 1", switchName="Sa_top")

# unpack the parameters from the dictionary
software_control_enabled = switch_settings["software_control_enabled"]
software_value = switch_settings["software_value"]

get_contactor_settings(name)¶

Returns settings parameters of a contactor with the given name.

Parameters:: name (str) – Name of a contactor
Returns:: Dictionary with the contactor settings, or None if the contactor with given name cannot be found.

Dictionary key	Meaning	Value
“software_control_enabled”	Is contactor software control mode active?	boolean
“software_value”	Contactor software state	string (“Opened” or “Closed”)

Availability:

standalone scripts
macro scripts
signal monitoring expressions

Example:

# initialize the contactor
hil.set_contactor_control_mode(
    'contactor_disch', swControl=True, swState=True)

# get contactor settings parameters
contactor_settings=hil.get_contactor_settings('contactor_disch')

# unpack the parameters from the dictionary
software_control_enabled =
    contactor_settings["software_control_enabled"]
software_value = contactor_settings["software_value"]

get_analog_output_settings(channel, device=0)¶

Returns settings parameters of an analog output channel.

Parameters:

channel (int) – Analog output channel number
device (int) – HIL device ID to which the desired analog output channel belongs

Returns:

Dictionary with the analog output channel settings, or None if the analog output channel cannot be found.

Dictionary key	Meaning	Value
“signal_name”	Assigned analog signal name	string or None if signal is not assigned
“scaling”	Scaling value	float
“offset”	Offset value	float

Availability:

standalone scripts
macro scripts
signal monitoring expressions

Example:

# initialize the analog output channel
hil.set_analog_output(1, "V( V0 )", scaling=100, offset=0, device=0)

# get the analog output settings parameters
channel_settings = hil.get_analog_output_settings(channel=1, device=0)

# unpack the parameters from the dictionary
signal_name = channel_settings["signal_name"]
scaling = channel_settings["scaling"]
offset = channel_settings["offset"]

get_digital_output_settings(channel, device=0)¶

Returns settings parameters of a digital output channel.

Parameters:

channel (int) – Digital output channel number
device (int) – HIL device ID to which the desired digital output channel belongs

Returns:

Dictionary with the digital output channel settings, or None if the digital output channel cannot be found.

Dictionary key	Meaning	Value
“signal_name”	Assigned digital signal name	string
“inverted”	Is digital output inverted?	boolean
“software_control_enabled”	Is software control mode active?	boolean
“software_value”	Digital output software defined value	int

Availability:

standalone scripts
macro scripts
signal monitoring expressions

Example:

# initialize the digital output channel
hil.set_digital_output(
    1, name='machine encoder A', invert=False,
    swControl=False, value=0)

# get the digital output settings parameters
channel_settings = hil.get_digital_output_settings(channel=1, device=0)

# unpack the parameters from the dictionary
signal_name = channel_settings["signal_name"]
inverted = channel_settings["inverted"]
software_control_enabled = channel_settings["software_control_enabled"]
software_value = channel_settings["software_value"]

get_cp_input_settings(cpCategory, cpGroup, cpInputName)¶

Returns the settings parameters of a Control Panel Input (CP Input).

Note

This function will soon be deprecated. Please use the get_scada_input_settings() instead.

Parameters:

cpCategory (str) – CP Input category name
cpGroup (str) – CP Input group name
cpInputName (str) – CP Input name

Returns:

Dictionary with the CP input settings, or None if the CP input cannot be found.

Dictionary key	Meaning	Value
“input_value”	Control Panel input value	int or float

Availability:

standalone scripts
macro scripts
signal monitoring expressions

Example:

# initialize the CP Input
hil.set_cp_input_value('Power load/source', "Sconst1", 'Pref', 32.00)

# get the CP Input settings parameters
cp_input_settings = hil.get_cp_input_settings(
    'Power load/source', "Sconst1", 'Pref',)

# unpack the parameters from the dictionary
input_value = cp_input_settings["input_value"]

get_scada_input_settings(scadaInputName)¶

Returns the settings parameters of a SCADA Input.

Parameters:

scadaInputName (str) – SCADA Input name

Returns:

Dictionary with the SCADA Input settings, or None if
the SCADA Input cannot be found.

Dictionary key	Meaning	Value
“input_value”	SCADA input value	int or float

Availability:

standalone scripts
macro scripts
signal monitoring expressions

Example:

# initialize the SCADA Input
hil.set_scada_input_value("Sconst1.Pref", 32.00)

# get the SCADA Input settings parameters
scada_input_settings = hil.get_scada_input_settings("Sconst1.Pref")

# unpack the parameters from the dictionary
input_value = scada_input_settings["input_value"]

get_hil_serial_number()¶

Returns the serial numbers of all connected HIL devices.

Note

Serial numbers will be returned as a list sorted by HIL device ID: [device_with_id_0_serial, device_with_id_1_serial, …

device_with_id_N_serial]

Note

In case multiple HIL devices with the same device ID are connected, the returned list will be unsorted

Returns:

list of serial numbers sorted by the HIL device ID. In case
an error occurs, an empty list will be returned or an appropriate exception will be raised

Availability:

standalone scripts
macro scripts
signal monitoring expressions

Example:

import typhoon.api.hil as hil

# get the list of serial numbers of all connected HIL
serialNumbers = hil.get_hil_serial_number()

get_ns_var(var_name)¶

Returns the value of the Schematic Editor namespace variable named var_name.

Parameters:: var_name (str) – Namespace variable name.
Returns:: Data stored in the variable var_name or None if the variable with the name var_name cannot be found or if an error occurred.

Availability:

standalone scripts
macro scripts
signal monitoring expressions

get_ns_vars()¶

Gets names of all variables in the Schematic Editor namespace.

Returns:: List with all variable names in the namespace, or None if an error occurred.

Availability:

standalone scripts
macro scripts
signal monitoring expressions

get_data_logger_status(name)¶

Returns a status of the data logger with given name.

Parameters:

name (str) – The name of data logger whose status we want to obtain.

Returns:

(status, status_message) where status can be: True or False depending if everything is ok or some error occurs.

Return type:

status (tuple)

get_model_file_path()¶

Returns loaded HIL Model file path.

Returns:

Full path to loaded .cpd file.: In case model is not loaded None will be returned.

Return type:

path (str or None)

Availability:

standalone scripts
macro scripts
signal monitoring expressions

get_sp_monitors_values()¶

Returns values and other information (current value, maximum achieved value, CPU stalled flag status…) of all SP Monitors in loaded model.

Returns:

None if error occurs or sp monitors’ data organized like:

[
    {
        # ("System CPU", "User 'Nth' CPU", "Communication CPU")
        "SP Monitor type": "System CPU",

        # [0 , (number_of_device-1)]
        "HIL Device": 0,

        # (True, False)
        "CPU Stalled": False,

        "Execution rates": [
            {
                # execution rate value
                "Execution rate": 1e-5,

                # [0%, 100%]
                "Current value": 56.8,

                # [0%, 100%]
                "Maximum achieved": 80
            },
            {
                # another execution rate data
            }
        ]
    },

    {
        # another SP Monitor data
    }
]

Return type:

sp monitors’ data (list)

Availability:

standalone scripts
macro scripts
signal monitoring expressions

available_sources()¶

Displays the list of all independent voltage/current sources in the model.

Returns:: True if everything is OK, otherwise returns False.

Availability:

standalone scripts

available_pvs()¶

Displays the list of all photovoltaic panels in the model.

Note

This function is deprecated and it will be removed from the HIL API.

Returns:: True if everything is OK, otherwise returns False.

Availability:

standalone scripts

available_analog_signals()¶

Displays the list of all analog signals in the model.

Note

This function is deprecated and it will be removed from the HIL API.

Returns:: True if everything is OK, otherwise returns False.

Availability:

standalone scripts

available_digital_signals()¶

Displays the list of all digital signals that can be assigned to digital outputs.

Note

This function is deprecated and it will be removed from the HIL API.

Returns:: True if everything is OK, otherwise returns False.

Availability:

standalone scripts

available_contactors()¶

Displays the list of all contactors in the model.

Note

This function is deprecated and it will be removed from the HIL API.

Returns:: True if everything is OK, otherwise returns False.

Availability:

standalone scripts

available_machines()¶

Displays the list of all machines in the model.

Note

This function is deprecated and it will be removed from the HIL API.

Returns:: True if everything is OK, otherwise returns False.

Availability:

standalone scripts

available_pe_switching_blocks()¶

Displays the list of all software-controllable power electronics switching blocks in the model.

Note

This function is deprecated and it will be removed from the HIL API.

Returns:: True if everything is OK, otherwise returns False.

Availability:

standalone scripts

1. HIL API¶

1.1. API references ¶

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Dictionary key	Meaning	Value
“rms”	Signal RMS value	float
“frequency”	Signal frequency	float
“phase”	Signal phase	float
“harmonics_active”	Are harmonics active?	bool
“harmonics”	List of harmonics defined in absolute units	list [(harmonic_number_1,rms_1,phase_1),…(harmonic_number_n,rms_n,phase_n)].
“harmonics_pu”	List of harmonics defined in relative units	list [(harmonic_number_1,rms_pu_1,phase_1),…(harmonic_number_n,rms_pu_n,phase_n)]

1. HIL API¶

1.1. API references¶

1.1. API references ¶