Parse MATPOWER case into pandas DataFrame
Project description
MATPOWER Case Frames
Parse MATPOWER case into pandas DataFrame.
Unlike the tutorial on matpower-pip
, this package support parsing MATPOWER case using re
instead of Oct2Py
and Octave. After that, you can further parse the data into any format supported by your solver.
Installation
pip install matpowercaseframes
Usage
from matpowercaseframes import CaseFrames
case_path = 'case9.m'
cf = CaseFrames(case_path)
print(cf.gencost)
If you have matpower
installed via pip install matpower
(did not require matpower[octave]
), you can easily navigate MATPOWER case using:
import os
from matpower import path_matpower # require `pip install matpower`
from matpowercaseframes import CaseFrames
case_name = 'case9.m'
case_path = os.path.join(path_matpower, 'data', case_name)
cf = CaseFrames(case_path)
print(cf.gencost)
To save all DataFrame
to a single xlsx
file, use:
from matpowercaseframes import CaseFrames
case_path = 'case9.m'
cf = CaseFrames(case_path)
cf.to_excel('PATH/TO/DIR/case9.xlsx')
If you use matpower[octave]
, CaseFrames
also support oct2py.io.Struct
as input using:
from matpower import start_instance
from matpowercaseframes import CaseFrames
m = start_instance()
# support mpc before runpf
mpc = m.loadcase('case9', verbose=False)
cf = CaseFrames(mpc)
print(cf.gencost)
# support mpc after runpf
mpc = m.runpf(mpc, verbose=False)
cf = CaseFrames(mpc)
print(cf.gencost)
m.exit()
Acknowledgment
This repository was supported by the Faculty of Engineering, Universitas Gadjah Mada under the supervision of Mr. Sarjiya. If you use this package for your research, we are very glad if you cite any relevant publication under Mr. Sarjiya's name as thanks (but you are not responsible to cite). You can find his publications in the semantic scholar](https://www.semanticscholar.org/author/Sarjiya/2267414) or IEEE.
This package is a fork and simplification from psst MATPOWER parser, thus we greatly thank psst developers and contributors.
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