A Novel Feature Selection Method for the Dynamic Security Assessment of Power Systems Based on Multi-Layer Perceptrons

Authors

  • Peyman Beyranvand Istanbul Technical University
  • Cavit Fatih Kucuktezcan Bahcesehir University
  • Zehra Cataltepe Istanbul Technical University, Computer Engineering Department
  • Veysel Murat Istemihan Genc Istanbul Technical University http://orcid.org/0000-0001-7077-8895

DOI:

https://doi.org/10.18201/ijisae.2018637931

Keywords:

dynamic security assessment, feature selection, neural networks

Abstract

In this study, the effect of feature selection methods on the performance of multi-layer perceptrons used for the dynamic security assessment of electric power systems is investigated. The existence of many measurable parameters (features) characterizing the power system security status complicates the use of multi-layer perceptron both in terms of prediction accuracy and training time. In this paper, the dynamic security of a power system subject to a number of critical contingencies is assessed as the critical clearing time of any credible fault is predicted by a multi-layer perceptron. In addition to the study of two different feature selection methods, which are Minimum Redundancy Maximum Relevance (mRMR), and Regressional ReliefF (RReliefF), a novel multi-layer perceptron based feature selection method is proposed to be applied in the prediction of security indices. The performance of the feature selection methods on the dynamic security assessment is investigated on a 16-generator, 68-bus test system.

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Author Biographies

Cavit Fatih Kucuktezcan, Bahcesehir University

Assisstant Professor, Electrical & Electronics Engineering

Zehra Cataltepe, Istanbul Technical University, Computer Engineering Department

Professor,

Veysel Murat Istemihan Genc, Istanbul Technical University

Associate Professor, Department of Electrical Engineering

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Published

29.03.2018

How to Cite

Beyranvand, P., Kucuktezcan, C. F., Cataltepe, Z., & Genc, V. M. I. (2018). A Novel Feature Selection Method for the Dynamic Security Assessment of Power Systems Based on Multi-Layer Perceptrons. International Journal of Intelligent Systems and Applications in Engineering, 6(1), 53–58. https://doi.org/10.18201/ijisae.2018637931

Issue

Section

Research Article