sarajcev / pss-ml

Machine learning for power system stability analysis

PSS-ML

Machine learning for the power system transient stability analysis

Ensemble learning, using a voting classifier, for the electrical power system transient stability analysis. Model is built using the scikit-learn Python library. Dataset has been produced from the numerical simulations of the IEEE New England benchmark test case, using the MATLAB Simulink environment and statistically post-processed for extracting appropriate features. This repository serves as an accompanying code-base for a conference paper.

Jupyter Notebook rendered on nbviewer: PSS-ML

A. Kunac and P. Sarajcev, "Ensemble Learning Approach to Power System Transient Stability Assessment," 2020 5th International Conference on Smart and Sustainable Technologies (SpliTech), 2020, pp. 1-6, doi: 10.23919/SpliTech49282.2020.9243849.

pss-ml's Issues

Dataset

Decision boundary

@akunac Dodao sam vizualni prikaz granice odluke za SVM u slučaju da se koriste samo dvije najbolje značajke koje vrati GB klasifikator. Ovo možemo ponoviti i za neke druge klasifikatore koje koristimo.

PR