PYPOWER 3.2.0b1

Power flow and optimal power flow solver

PYPOWER is a power flow and Optimal Power Flow (OPF) solver. It is a port of MATPOWER to the Python programming language. Current features include:

• DC and AC (Newton’s method & Fast Decoupled) power flow and

• DC and AC optimal power flow (OPF)

Installation

PYPOWER depends upon:

• Python 2.5 or later and

• SciPy 0.7 or later.

It can be installed using setuptools:

$ easy_install PYPOWER

Alternatively, download and unpack the tarball and install:

$ tar zxf PYPOWER-4.0.X.tar.gz
$ python setup.py install

Using PYPOWER

Installing PYPOWER creates pf and opf commands. To list the command options:

$ pf -h

PYPOWER includes a selection of test cases. For example, to run a power flow on the IEEE 14 bus test case:

$ pf -c case14

Alternatively, the path to a PYPOWER case data file can be specified:

$ pf /path/to/case14.py

The opf command has the same calling syntax. For example, to solve an OPF and write the solved case to file:

$ opf -c case14 --solvedcase=out.py

For further information please refer to http://rwl.github.io/PYPOWER and the API documentation.

Support

Questions and comments regarding PYPOWER should be directed to the mailing list:

[e-mail]

License & Copyright

Copyright (C) 1996-2011 Power System Engineering Research Center

Copyright (C) 2010-2011 Richard Lincoln

This program is licensed under the Apache License, Version 2.0; you may not use this file except in compliance with this License.

Links

• MATPOWER from PSERC (Cornell)

• MatDyn by Stijn Cole

• PSAT by Federico Milano

• OpenDSS from EPRI

• GridLAB-D from PNNL

• PyCIM