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DC Field | Value | Language |
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dc.contributor.author | Dash, P K | - |
dc.contributor.author | Mishra, S | - |
dc.contributor.author | Panda, G | - |
dc.date.accessioned | 2005-07-04T08:10:56Z | - |
dc.date.available | 2005-07-04T08:10:56Z | - |
dc.date.issued | 2000 | - |
dc.identifier.citation | IEEE Power Engineering Society Summer Meeting, 16-20 July 2000, P 1959 vol. 3 | en |
dc.identifier.uri | http://hdl.handle.net/2080/99 | - |
dc.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. | en |
dc.description.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 | en |
dc.format.extent | 53595 bytes | - |
dc.format.mimetype | application/pdf | - |
dc.language.iso | en | - |
dc.publisher | IEEE | en |
dc.subject | damping | en |
dc.subject | load flow control | en |
dc.subject | neurocontrollers | en |
dc.subject | power system control | en |
dc.subject | power system transient | en |
dc.title | A radial basis function neural network controller for UPFC | en |
dc.type | Article | en |
Appears in Collections: | Conference Papers |
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pkd2000co3.pdf | 52.34 kB | Adobe PDF | View/Open |
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