Power quality event detection and analysis in power system using wavelet transformation

Guangbin Ding; Peilin Pang

doi:10.1117/12.806356

13 October 2008 Power quality event detection and analysis in power system using wavelet transformation

Guangbin Ding, Peilin Pang

Proceedings Volume 7127, Seventh International Symposium on Instrumentation and Control Technology: Sensors and Instruments, Computer Simulation, and Artificial Intelligence; 71271K (2008) https://doi.org/10.1117/12.806356
Event: Seventh International Symposium on Instrumentation and Control Technology, 2008, Beijing, China

Abstract

By means of wavelet transform and neural network, a novel approach for power quality (PQ) event classification is proposed. The feature vectors for various PQ events are extracted using wavelet transform which can accurately localizes the characteristics of signal in time-frequency domains. The feature vectors are then applied to the neural network for training and PQ pattern classification. The neural network have demonstrated promise in pattern recognition and been considered a potential alternative approach to pattern recognition It is concluded that the proposed neural network has better data driven learning and local interconnections performance by comparing with a classic neural network. The comparison between the proposed method and the other existing method is discussed. It is proved that the proposed approach can provide accurate classification results and give a new way for detection and analysis of power quality events.

Citation Download Citation

Guangbin Ding and Peilin Pang "Power quality event detection and analysis in power system using wavelet transformation", Proc. SPIE 7127, Seventh International Symposium on Instrumentation and Control Technology: Sensors and Instruments, Computer Simulation, and Artificial Intelligence, 71271K (13 October 2008); https://doi.org/10.1117/12.806356

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