Abstract
The objective of this paper is to present a new method for automatically detecting, localizing and classifying various types of power quality disturbances. The new method is based on wavelet transform analysis, artificial neural networks, and the mathematical theory of evidence. The proposed detection and localization algorithm is carried out in the wavelet transform domain using multiresolution signal decomposition techniques and the proposed classification method is carried out in the sets of multiple neural networks using a learning vector quantization network. The outcomes of the networks are then integrated using a voting decision making scheme. The performance of the automatic detection and localization have 90.14% accuracy and the error is less than 5%.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
