NDLI: A radial basis function neural network controller for UPFC

Content Provider	IEEE Xplore Digital Library
Author	Dash, P.K. Mishra, S. Panda, G.
Copyright Year	2000
Description	Author affiliation: Regional Eng. Coll., Rourkela, India (Dash, P.K.)
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 exhibits a superior damping performance in comparison to the existing PI controllers. Its simple architecture reduces the computational burden thereby making it attractive for real-time implementation.
File Size	53595
File Format	PDF
ISBN	0780364201
DOI	10.1109/PESS.2000.868836
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2000-07-16
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Radial basis function networks Power system transients Control systems Neurons Power system dynamics Power system stability Damping Reactive power Voltage Backpropagation
Content Type	Text
Resource Type	Article

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