Electric power systems transient stability analysis by neural networks

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Data

1995-12-01

Autores

Minussi, Carlos R. [UNESP]
Silveira, Maria do Carmo G [UNESP]

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Resumo

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.

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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

Como citar

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