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Solves power flow and optimal power flow problems

Project description

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:

It can be installed using pip:

$ pip install PYPOWER

Alternatively, download and unpack the tarball and install:

$ tar zxf PYPOWER-4.x.y.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 for the IEEE Reliability Test System and write the solved case to file:

$ opf -c case24_ieee_rts --solvedcase=rtsout.py

For further information please refer to http://www.pypower.org/ and the API documentation.

Support

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

pypower@googlegroups.com

Changelog

Version 4.1.1 (2014-09-17)

  • [FIX] loadcase.py: Fixed NumPy 1.9 warning about “== None” comparisions.

Version 4.1.0 (2014-05-29)

  • [NEW] Support for Python 3 (3.3 and above).

  • [CHANGE] Updated to MATPOWER 4.1.

  • [REMOVED] Support for Python 2.5 and below.

Version 4.0.1 (2011-07-14)

  • [CHANGE] printpf.py: changed boolean operators from bitwise to logical to fix the output options

  • [FIX] savecase.py: adding indentation to produce valid Python modules

Version 4.0.0 (2011-07-07)

Initial release, port of MATPOWER version 4.0

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