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All Journal International Journal of Intelligent Systems and Applications in Engineering
Kucuktezcan, Cavit Fatih
Advanced Technology and Science (ATScience)
Computer Science & IT

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A Novel Feature Selection Method for the Dynamic Security Assessment of Power Systems Based on Multi-Layer Perceptrons Beyranvand, Peyman; Kucuktezcan, Cavit Fatih; Cataltepe, Zehra; Genc, Veysel Murat Istemihan
International Journal of Intelligent Systems and Applications in Engineering Vol 6, No 1 (2018)
Publisher : Advanced Technology and Science (ATScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18201/ijisae.2018637931

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.
Co-Authors Beyranvand, Peyman Cataltepe, Zehra Genc, Veysel Murat Istemihan