On-line Voltage and Power Flow Contingencies Ranking Using Enhanced Radial Basis Function Neural Network and Kernel Principal Component Analysis

Timely and accurate assessment of voltage and power flow security is necessary to detect post-contingency problems in order to prevent a large-scale blackout. This article presents an enhanced radial basis function neural network based on a modified training algorithm for on-line ranking of the cont...

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Bibliographic Details
Published in:	Electric power components and systems Vol. 40; no. 5; pp. 534 - 555
Main Authors:	Javan, D. Seyed, Rajabi Mashhadi, H., Toussi, S. Ashkezari, Rouhani, M.
Format:	Journal Article
Language:	English
Published:	Philadelphia Taylor & Francis Group 01-03-2012 Taylor & Francis Ltd
Subjects:	Algorithms contingency Effectiveness Electric power feature extraction Neural networks performance index radial basis function neural network Simulation static security assessment
Online Access:	Get full text
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Summary:	Timely and accurate assessment of voltage and power flow security is necessary to detect post-contingency problems in order to prevent a large-scale blackout. This article presents an enhanced radial basis function neural network based on a modified training algorithm for on-line ranking of the contingencies expected to cause steady-state bus voltage and power flow violations. Hidden layer neurons have been selected with the proposed algorithm, which has the advantage of being able to automatically choose optimal centers and radii. The proposed radial basis function neural network based security assessment algorithm has very small training time and space in comparison with multi-layer perceptron neural networks, support vector machines, and other machine learning based algorithms. A feature extraction technique based on kernel principal component analysis has been employed to identify the relevant inputs for the neural network. Also, the proposed feature extraction algorithm has been compared with Fisher-like criterion, the class separability index, and the correlation coefficient technique. The competence of the proposed approaches has been demonstrated on IEEE 14-bus and IEEE 118-bus power systems. The simulation results show the effectiveness and the stability of the proposed scheme for on-line voltage and power flow contingencies ranking procedures of large-scale power systems.
Bibliography:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23
ISSN:	1532-5008 1532-5016
DOI:	10.1080/15325008.2011.647240