On-line Transient Stability Assessment Using Hybrid Artificial Neural Network

On-line transient stability assessment of a power system is not yet feasible due to the intensive computation involved. Artificial neural network has been proposed as one of the approaches to this problem because of its ability to quickly map nonlinear relationships between the input data and the ou...

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Main Authors: Li Chunyan, Tang Biqiang, Chen Xiangyi
Format: Conference Proceeding
Language:English
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Artificial neural network
Artificial neural networks
Industrial electronics
On-line
Power system
Stability
Transient stability assessment
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Tang Biqiang
Chen Xiangyi
description On-line transient stability assessment of a power system is not yet feasible due to the intensive computation involved. Artificial neural network has been proposed as one of the approaches to this problem because of its ability to quickly map nonlinear relationships between the input data and the output. In this paper a hybrid neural network for TSA is proposed. The proposed hybrid neural network is composed of a Kohonen network and several radial-basis function (RBF) networks. It possesses properties of both kinds of networks. So, its ability of TSA is improved. The proposed hybrid neural network is applied for an actual power grid, the obtain results confirm the validity of the developed method. Also, a comparison between the proposed neural network and other ones is present, which indicates the efficiency of the proposed neural network.
doi_str_mv 10.1109/ICIEA.2007.4318427
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subjects Artificial neural network
Artificial neural networks
Industrial electronics
On-line
Power system
Stability
Transient stability assessment
title On-line Transient Stability Assessment Using Hybrid Artificial Neural Network
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