Dynamic Security Assessment of Power Systems Using Ensemble Learning Algorithms

Document Type : -

Authors

1 Associate Professor, Shahid Madani University of Azerbaijan, Tabriz, Iran

2 Master's student, Shahid Madani University Azerbaijan, Tabriz, Iran

3 PhD student, Shahid Madani University of Azerbaijan, Tabriz, Iran

Abstract

Considering the importance of dynamic security assessment and the necessity of implementing control measures after a disturbance, online dynamic security assessment has replaced offline assessment. Methods which are commonly used in dynamic security evaluation are not suitable for serious events which have a high rate of occurrence. Therefore, it is essential to perform real time transient stability assessment in order to increase operators opportunity to take remedial actions. For this purpose, in this study, ensemble machine learning methods have been used to evaluate online dynamic security. The investigated problem is a multi-class classification that deals with classifying of system’s dynamic security status. The proposed method has been evaluated on two standard systems. Also, a comparison has been made between the proposed ensemble learning methods and individual algorithms. The results indicate that the proposed method, not only accurate but also has good performance in evaluating online dynamic security.

Keywords

Main Subjects


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https://creativecommons.org/licenses/by/4.0/

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Volume 14, Issue 3 - Serial Number 53
November 2023
Pages 165-178
  • Receive Date: 20 July 2023
  • Revise Date: 05 November 2023
  • Accept Date: 10 November 2023
  • Publish Date: 04 December 2023