Title :
On-line Transient Stability Assessment Using Hybrid Artificial Neural Network
Author :
Chunyan, Li ; Biqiang, Tang ; Xiangyi, Chen
Author_Institution :
Wuhan Univ., Wuhan
Abstract :
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.
Keywords :
power engineering computing; power grids; power system transient stability; radial basis function networks; self-organising feature maps; Kohonen network; RBF networks; hybrid artificial neural network; online transient stability assessment; power engineering computing; power grid; power system transient stability; radial-basis function networks; Artificial neural networks; Industrial electronics; Stability; Artificial neural network; On-line; Power system; Transient stability assessment;
Conference_Titel :
Industrial Electronics and Applications, 2007. ICIEA 2007. 2nd IEEE Conference on
Conference_Location :
Harbin
Print_ISBN :
978-1-4244-0737-8
Electronic_ISBN :
978-1-4244-0737-8
DOI :
10.1109/ICIEA.2007.4318427