DSpace@nitr >
National Institue of Technology- Rourkela >
Conference Papers >

Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/99

Title: A radial basis function neural network controller for UPFC
Authors: Dash, P K
Mishra, S
Panda, G
Keywords: damping
load flow control
neurocontrollers
power system control
power system transient
Issue Date: 2000
Publisher: IEEE
Citation: IEEE Power Engineering Society Summer Meeting, 16-20 July 2000, P 1959 vol. 3
Abstract: Summary form only given as follows. This paper presents the design of radial basis function neural network controllers (RBFNN) for UPFC to improve the transient stability performance of a power system. The RBFNN uses either single neuron or multi-neuron architecture and the parameters are dynamically adjusted using an error surface derived from active or reactive power/voltage deviations at the UPFC injection bus. The performance of the new single neuron controller is evaluated using both single-machine infinite-bus and three-machine power systems subjected to various transient disturbances. In the case of a three-machine 8-bus power system, the performance of the single neuron RBF controller is compared with BP (backpropagation) algorithm based multi-layered ANN controller. Further it is seen that by using a multi-input multi-neuron RBF controller, instead of a single neuron one, the critical clearing time and damping performance are improved. The new RBFNN controller for UPFC exhibit...
Description: or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
URI: http://hdl.handle.net/2080/99
Appears in Collections:Conference Papers

Files in This Item:

File Description SizeFormat
pkd2000co3.pdf52KbAdobe PDFView/Open

Show full item record

All items in DSpace are protected by copyright, with all rights reserved.

 

Powered by DSpace Feedback