Artículos de revistas
Power quality analysis applying a hybrid methodology with wavelet transforms and neural networks
Fecha
2009Registro en:
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, v.31, n.5, p.206-212, 2009
0142-0615
10.1016/j.ijepes.2009.01.012
Autor
OLESKOVICZ, Mario
Coury, Denis Vinicius
FELHO, Odilon Delmont
USIDA, Wesley F.
CARNEIRO, Adriano A. F. M.
PIRES, Leandro R. S.
Institución
Resumen
A hybrid system to automatically detect, locate and classify disturbances affecting power quality in an electrical power system is presented in this paper. The disturbances characterized are events from an actual power distribution system simulated by the ATP (Alternative Transients Program) software. The hybrid approach introduced consists of two stages. In the first stage, the wavelet transform (WT) is used to detect disturbances in the system and to locate the time of their occurrence. When such an event is flagged, the second stage is triggered and various artificial neural networks (ANNs) are applied to classify the data measured during the disturbance(s). A computational logic using WTs and ANNs together with a graphical user interface (GU) between the algorithm and its end user is then implemented. The results obtained so far are promising and suggest that this approach could lead to a useful application in an actual distribution system. (C) 2009 Elsevier Ltd. All rights reserved.