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| Titel: |
Application of Artificial Intelligence Techniques for Classification and Location of Faults on Thyristor-Controlled Series-Compensated Line |
| Auteur: |
Dash, P. K. Pradhan, A. K. Panda, G. |
| Verschenen in: |
Electric power components & systems |
| Paginering: | Jaargang 31 (2003) nr. 3 pagina's 241-260 |
| Jaar: |
2003-03 |
| Inhoud: |
Radial basis function neural networks (RBFNN) and fuzzy neural networks (FNN) are finding increasing attention as AI techniques. Power systems protection is a complex task in which AI techniques are successfully employed. Minimal RBFNN (MRBFNN) is a newer version of neural network that provides a minimum number of neurons using the sequential learning and pruning strategy. On the other hand, the fuzzy neural network, using a pruning strategy, yields fewer fuzzy rules. These new techniques are employed for the protection of a power network having a thyristor-controlled series capacitor (TCSC) which introduces further complexity into the protection problem. A comparison of the two new schemes is also outlined. |
| Uitgever: |
Taylor & Francis |
| Bronbestand: |
Elektronische Wetenschappelijke Tijdschriften |
Details van artikel 2 van 6 gevonden artikelen
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