Electric power systems transient stability analysis by neural networks

Minussi, Carlos R.; Silveira, Maria do Carmo G

Please use this identifier to cite or link to this item: http://acervodigital.unesp.br/handle/11449/64681

Title:

Electric power systems transient stability analysis by neural networks

Author(s):

Institution:

Universidade Estadual Paulista (UNESP)

Sponsorship:

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Sponsorship Process Number:

CPNq: 521870/94-1

Abstract:

This work aims to investigate the use of artificial neural networks in the analysis of the transient stability of Electric Power Systems (determination of critical clearing time for short-circuit faults type with electric power transmission line outage), using a supervised feedforward neural network. To illustrate the proposed methodology, it is presented an application considering a system having by 08 synchronous machines, 23 transmission lines, and 17 buses.

Issue Date:

1-Dec-1995

Citation:

Midwest Symposium on Circuits and Systems, v. 2, p. 1305-1308.

Time Duration:

1305-1308

Keywords:

Adaptive algorithms
Backpropagation
Computational methods
Computer simulation
Electric power transmission
Feedforward neural networks
Functions
Iterative methods
Short circuit currents
Synchronous machinery
Transients
Transmission line theory
Critical clearing time
Neuron weight
Quadratic error gradient
Short circuit faults
Transient stability analysis
Electric power systems

Source:

http://dx.doi.org/10.1109/MWSCAS.1995.510337

URI:

Access Rights:

Acesso restrito

Type:

outro

Source:

http://repositorio.unesp.br/handle/11449/64681

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