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Novel algorithm for online voltage stability assessment based on feed forward neural network

Kamalasadan, S and Srivastava, AK and Thukaram, D (2006) Novel algorithm for online voltage stability assessment based on feed forward neural network. In: 2006. IEEE Power Engineering Society General Meeting, 18-22 June 2006, Montreal, Que.

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Abstract

This paper presents an artificial feed forward neural network (FFNN) approach for the assessment of power system voltage stability. A novel approach based on the input-output relation between real and reactive power, as well as voltage vectors for generators and load buses is used to train the neural net (NN). The input properties of the feed forward network are generated from offline training data with various simulated loading conditions using a conventional voltage stability algorithm based on the L-index. The neural network is trained for the L-index output as the target vector for each of the system loads. Two separate trained NN, corresponding to normal loading and contingency, are investigated on the 367 node practical power system network. The performance of the trained artificial neural network (ANN) is also investigated on the system under various voltage stability assessment conditions. As compared to the computationally intensive benchmark conventional software, near accurate results in the value of L-index and thus the voltage profile were obtained. Proposed algorithm is fast, robust and accurate and can be used online for predicting the L-indices of all the power system buses. The proposed ANN approach is also shown to be effective and computationally feasible in voltage stability assessment as well as potential enhancements within an overall energy management system in order to determining local and global stability indices

Item Type: Conference Paper
Additional Information: Copyright 2006 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Keywords: Artificial Neural Network;Voltage Stability;Quasi Newton and Levenberg Marquardt Algorithms;Back Propagation method.
Department/Centre: Division of Electrical Sciences > Electrical Engineering
Date Deposited: 13 Apr 2012 10:49
Last Modified: 13 Apr 2012 10:49
URI: http://eprints.iisc.ernet.in/id/eprint/44294

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