Voltage ranking using artificial neural network

Voltage ranking attempts to rank busbar voltage deviations from their normally accepted security margins based on a set of performance indices (PI), without performing a full load flow. Existing methods suffer from either masking effects or long computation time. In this paper, an artificial neural...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Compel 1999-12, Vol.18 (4), p.587-599
Hauptverfasser: Lo, K.L., Luan, W.P., Given, M., Macqueen, J.F., Ekwue, A.O., Chebbo, A.M.
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Voltage ranking attempts to rank busbar voltage deviations from their normally accepted security margins based on a set of performance indices (PI), without performing a full load flow. Existing methods suffer from either masking effects or long computation time. In this paper, an artificial neural network method is proposed for voltage ranking. Counterpropagation network (CPN) has been employed to overcome the problems listed above. A variety of input features are used with the aim of lowering the dimension of the proposed ANN to make it applicable for large power systems. The method is tested on two example systems, a five-bus system and a 71-bus system with very encouraging results.
ISSN:0332-1649
2054-5606
DOI:10.1108/03321649910296618