https://github.com/mcosovic/matgrid
MATGRID is an easy-to-use power system simulation tool for researchers and educators provided as a MATLAB package.
https://github.com/mcosovic/matgrid
bad-data data-set gauss-newton-method least-absolute-value measurements newton-raphson observability outlier-detection phasor-measurement-unit power-flow power-systems state-estimation weighted-least-squares
Last synced: about 1 month ago
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MATGRID is an easy-to-use power system simulation tool for researchers and educators provided as a MATLAB package.
- Host: GitHub
- URL: https://github.com/mcosovic/matgrid
- Owner: mcosovic
- License: mit
- Created: 2017-02-19T17:21:31.000Z (over 8 years ago)
- Default Branch: master
- Last Pushed: 2019-04-22T15:18:42.000Z (about 6 years ago)
- Last Synced: 2025-04-16T11:03:09.130Z (about 1 month ago)
- Topics: bad-data, data-set, gauss-newton-method, least-absolute-value, measurements, newton-raphson, observability, outlier-detection, phasor-measurement-unit, power-flow, power-systems, state-estimation, weighted-least-squares
- Language: MATLAB
- Homepage:
- Size: 45.3 MB
- Stars: 31
- Watchers: 7
- Forks: 16
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
## MATGRID
MATGRID is an easy-to-use simulation tool for researchers and educators provided as a MATLAB package, with source code released under MIT License. MATGRID is inspired by Matpower and allows a variety of display and manipulation options.
We have tested and verifed simulation tool using different scenarios to the best of our ability. As a user of this simulation tool, you can help us to improve future versions, we highly appreciate your feedback about any errors, inaccuracies, and bugs. For more information, please visit our [wiki](https://github.com/mcosovic/MATGRID/wiki/MATGRID) site.
The software package provides the solution of the AC and DC power flow, non-linear and DC state estimation, as well as the state estimation with PMUs, with standalone measurement generator.
MATGRID includes, inter alia, the weighted least-squares and least absolute values state estimation, optimal PMU placement, and bad data processing.
### Fast Run Power Flow
```
runpf('ieee14_20', 'nr', 'main', 'flow');
runpf('ieee14_20', 'dc', 'main', 'flow');
```
### Fast Run State Estimation
```
runse('ieee118_186', 'nonlinear', 'estimate');
runse('ieee118_186', 'dc', 'estimate');
runse('ieee14_20', 'pmu', 'pmuOptimal', 'estimate');
```
### Changelog
Major changes:
- 2019-04-21 the DC state estimation with observability analysis and bad data processing optimized for large-scale systems
- 2019-04-08 Added the DC observability analysis with identification of observable islands
- 2019-04-03 Added observability analysis (DC state estimation only , beta version, please treat the results with attention)
- 2019-03-28 Added Gauss-Seidel, decoupled Newton-Raphson and fast decoupled Newton-Raphson algorithm
- 2019-03-21 Added least absolute value (LAV) state estimation
- 2019-03-19 Added bad data processing