ams.routines.pypower.PFlow1#

class ams.routines.pypower.PFlow1(system, config, **kwargs)[source]#

Power Flow using PYPOWER.

This routine provides a wrapper for running power flow analysis using the PYPOWER. It leverages PYPOWER's internal power flow solver and maps results back to the AMS system.

Notes

  • This class does not implement the AMS-style power flow formulation.

  • For detailed mathematical formulations and algorithmic details, refer to the MATPOWER User's Manual, section on Power Flow.

  • Fast-Decoupled (XB version) and Fast-Decoupled (BX version) algorithms are not fully supported yet.

Added in version 1.0.10.

__init__(system, config, **kwargs)[source]#

Initialize the routine.

Parameters:
systemOptional[Type]

The system object associated with the routine.

configOptional[dict]

Configuration dictionary for the routine.

Methods

addConstrs(name, e_str[, info])

Add a Constraint to the routine at runtime.

addRParam(name[, tex_name, info, src, unit, ...])

Add RParam to the routine.

addService(name, value[, tex_name, unit, ...])

Add ValueService to the routine.

addVars(name[, model, shape, tex_name, ...])

Add a variable to the routine.

dc2ac([kloss])

Convert the DC-based results with ACOPF.

disable(name)

Disable a constraint by name.

doc([max_width, export])

Retrieve routine documentation as a string.

enable(name)

Enable a constraint by name.

export_csv([path])

Export scheduling results to a csv file.

export_json([path])

Export scheduling results to a json file.

formulation_summary([return_rows])

Print (or return) a per-item table of the live formulation source.

get(src, idx[, attr, horizon])

Get the value of a variable or parameter.

init(**kwargs)

Initialize the routine.

load_json(path)

Load scheduling results from a json file.

run(**kwargs)

Run the power flow using PYPOWER.

set(src, idx[, attr, value])

Set the value of an attribute of a routine parameter.

solve(**kwargs)

Solve by PYPOWER.

summary(**kwargs)

Summary interface

unpack(res, **kwargs)

Unpack results from PYPOWER.

update([params, build_mats])

Update the values of Parameters in the optimization model.

Attributes

class_name