Electric power systems transient stability analysis by neural networks
| Contribuinte(s) |
Universidade Estadual Paulista (UNESP) |
|---|---|
| Data(s) |
27/05/2014
27/05/2014
01/12/1995
|
| Resumo |
Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) 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. |
| Formato |
1305-1308 |
| Identificador |
http://dx.doi.org/10.1109/MWSCAS.1995.510337 Midwest Symposium on Circuits and Systems, v. 2, p. 1305-1308. http://hdl.handle.net/11449/64681 10.1109/MWSCAS.1995.510337 WOS:A1996BF75Z00323 2-s2.0-0029463113 |
| Idioma(s) |
eng |
| Relação |
Midwest Symposium on Circuits and Systems |
| Direitos |
closedAccess |
| Palavras-Chave | #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 |
| Tipo |
info:eu-repo/semantics/conferencePaper |
