Data for: Maximum Frequency Deviation Assessment with Semi-Supervised Clustering based on Metric Learning

Published: 1 April 2020| Version 3 | DOI: 10.17632/m2f4fvc6bd.3
Contributors:
Changgang Li, Huarui Li, Yutian Liu

Description

This zip file contains data and codes of manuscript "Maximum Frequency Deviation Assessment with Semi-Supervised Clustering based on Metric Learning". It consists of 4 folders: (1) example_system folder: IEEE 39-bus model and simplified provincial power system of China in PSS/E format. (2) codes_to_generate_samples folder: Python codes to generate samples of the two systems in the example_system folder. (3) samples folder: samples generated with codes in the codes_to_generate_samples folder. In the manuscript, 10,000 samples were generated. However, only 1,000 samples are uploaded here to save space. (4) codes_for_machine_learning: codes for implementing the model proposed in this manualscript.

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Categories

Machine Learning, Power System Security Assessment

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