Functions

This section lists important functions for running a time series simulation. It introduces the time series main function and the auxiliary methods for preparing a time series simulation. Furthermore, various internal functions are listed.

Run Function

run_timeseries(net, time_steps=None, continue_on_divergence=False, verbose=True, **kwargs)

Time Series main function

Execution of pipe flow calculations for a time series using controllers. Optionally other functions than pipeflow can be called by setting the run function in kwargs.

Note

Refers to pandapower power flow.

Parameters:
  • net (pandapipesNet) – The pandapipes format network

  • time_steps (list or tuple, default None) – Time steps to calculate as list or tuple (start, stop). If None, all time steps from provided data source are simulated.

  • continue_on_divergence (bool, default False) – If True, time series calculation continues in case of errors.

  • verbose (bool, default True) – Prints progress bar or if logger.level == Debug, it prints debug messages

  • kwargs (dict) – Keyword arguments for run_control and runpp

Returns:

No output

Functions for Preparation

To prepare a time series simulation, classes/ methods of pandapower are accessed. DFData is derived from the DataSource class. The controller ConstControl is also required and can be found in chapter Controller. In the following all functions for the preparation are listed:

Further Functions

The following functions are called within run_timeseries.

init_time_series(net, time_steps, continue_on_divergence=False, verbose=True, **kwargs)

Initializes the time series calculation.

Creates the dict ts_variables, which includes necessary variables for the time series / control function.

Parameters:
  • net (pandapipesNet) – The pandapipes format network

  • time_steps (list or tuple) – Time steps to calculate as list or tuple (start, stop). If None, all time steps from provided data source are simulated.

  • continue_on_divergence (bool, default False) – If True, time series calculation continues in case of errors.

  • verbose (bool, default True) – Prints progress bar or logger debug messages

  • kwargs (dict) – Keyword arguments for run_control and runpp

Returns:

ts_variables, kwargs

Return type:

dict, dict

control_diagnostic(net, respect_in_service=True)

Diagnostic function to find obvious mistakes in control data

run_loop(net, ts_variables, run_control_fct=<function run_control>, output_writer_fct=<function _call_output_writer>, **kwargs)

runs the time series loop which calls pp.runpp (or another run function) in each iteration

Parameters:
net - pandapower net
ts_variables - settings for time series
run_time_step(net, time_step, ts_variables, run_control_fct=<function run_control>, output_writer_fct=<function _call_output_writer>, **kwargs)

Time Series step function Is called to run the PANDAPOWER AC power flows with the timeseries module

INPUT:

net - The pandapower format network

time_step (int) - time_step to be calculated

ts_variables (dict) - contains settings for controller and time series simulation. See init_time_series()

cleanup(net, ts_variables)