Electric power systems transient stability analysis by neural networks
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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.
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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
Language
English
Citation
Midwest Symposium on Circuits and Systems, v. 2, p. 1305-1308.
