毕业设计&课设-MATGRID是一个易于使用的电力系统仿真工具，以MATLAB包的形式提供给研究人员和教育工作者。.zip

## MATGRID <a href="https://github.com/mcosovic/MATGRID/wiki/MATGRID"><img align="right" width="145" src="/doc/figures/logo.png" /></a> 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. <p align="middle"><a href="https://github.com/mcosovic/MATGRID/wiki/Power-Flow" itemprop="contentUrl" data-size="600x400"> <img src="/doc/figures/modulepf.png" width="110"></a> <a href="https://github.com/mcosovic/MATGRID/wiki/State-Estimation" itemprop="contentUrl" data-size="600x400"> <img src="/doc/figures/modulese.png" width="110"></a> <a href="https://github.com/mcosovic/MATGRID/wiki/Measurement-Generator" itemprop="contentUrl" data-size="600x400"> <img src="/doc/figures/modulemg.png" width="110"></a></p> 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