Advances in Signal Processing and Artificial Intelligence Technologies in the Classification of Power Quality Events: A Survey.
Author(s)
Choong, F
Reaz, MBI
Mohd-Yasin, F
Griffith University Author(s)
Year published
2005
Metadata
Show full item recordAbstract
Power quality monitoring has advanced from strictly problem solving to ongoing monitoring of system performance. The increased amount of data being collected requires more advanced analysis tools. New intelligent system technologies using expert systems and artificial neural networks provide some unique advantages regarding fault analysis. The purpose of this article is to review and discuss various tools and methodologies aimed at providing more flexible and efficient ways of assessing power quality. Advances in signal processing and artificial intelligence tools will be examined for their role in the detection and ...
View more >Power quality monitoring has advanced from strictly problem solving to ongoing monitoring of system performance. The increased amount of data being collected requires more advanced analysis tools. New intelligent system technologies using expert systems and artificial neural networks provide some unique advantages regarding fault analysis. The purpose of this article is to review and discuss various tools and methodologies aimed at providing more flexible and efficient ways of assessing power quality. Advances in signal processing and artificial intelligence tools will be examined for their role in the detection and classification of events, the application of various mathematical transforms and the implementation of rules-based expert systems. We focus further on the review on several implementation methodologies, and a performance comparison of existing implementations are presented. Recommendations for future study are also outlined. This review opens the path for researchers to future comparative studies between different architectures, and as a reference point for developing more powerful and flexible structures.
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View more >Power quality monitoring has advanced from strictly problem solving to ongoing monitoring of system performance. The increased amount of data being collected requires more advanced analysis tools. New intelligent system technologies using expert systems and artificial neural networks provide some unique advantages regarding fault analysis. The purpose of this article is to review and discuss various tools and methodologies aimed at providing more flexible and efficient ways of assessing power quality. Advances in signal processing and artificial intelligence tools will be examined for their role in the detection and classification of events, the application of various mathematical transforms and the implementation of rules-based expert systems. We focus further on the review on several implementation methodologies, and a performance comparison of existing implementations are presented. Recommendations for future study are also outlined. This review opens the path for researchers to future comparative studies between different architectures, and as a reference point for developing more powerful and flexible structures.
View less >
Journal Title
Electric Power Components and Systems
Volume
33
Subject
Electrical and Electronic Engineering not elsewhere classified
Electrical and Electronic Engineering