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A novel out of step relaying algorithm based on wavelet transform and a deep learning machine model
by
Desai, Jigneshkumar Pramodbhai
, Makwana, Vijay Hiralal
in
Algorithms
/ Deep learning
/ Electrical Machines and Networks
/ Electrical networks
/ Energy
/ Energy Systems
/ Generators
/ Hardware
/ Machine learning
/ Original Research
/ Pattern recognition
/ Penetration
/ Power Electronics
/ Power System Protection and Control
/ Renewable and Green Energy
/ Renewable energy
/ Transmission lines
/ Wavelet transforms
2021
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A novel out of step relaying algorithm based on wavelet transform and a deep learning machine model
by
Desai, Jigneshkumar Pramodbhai
, Makwana, Vijay Hiralal
in
Algorithms
/ Deep learning
/ Electrical Machines and Networks
/ Electrical networks
/ Energy
/ Energy Systems
/ Generators
/ Hardware
/ Machine learning
/ Original Research
/ Pattern recognition
/ Penetration
/ Power Electronics
/ Power System Protection and Control
/ Renewable and Green Energy
/ Renewable energy
/ Transmission lines
/ Wavelet transforms
2021
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Do you wish to request the book?
A novel out of step relaying algorithm based on wavelet transform and a deep learning machine model
by
Desai, Jigneshkumar Pramodbhai
, Makwana, Vijay Hiralal
in
Algorithms
/ Deep learning
/ Electrical Machines and Networks
/ Electrical networks
/ Energy
/ Energy Systems
/ Generators
/ Hardware
/ Machine learning
/ Original Research
/ Pattern recognition
/ Penetration
/ Power Electronics
/ Power System Protection and Control
/ Renewable and Green Energy
/ Renewable energy
/ Transmission lines
/ Wavelet transforms
2021
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A novel out of step relaying algorithm based on wavelet transform and a deep learning machine model
Journal Article
A novel out of step relaying algorithm based on wavelet transform and a deep learning machine model
2021
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Overview
Out-of-step protection of one or a group of synchronous generators is unreliable in a power system which has significant renewable power penetration. In this work, an innovative out-of-step protection algorithm using wavelet transform and deep learning is presented to protect synchronous generators and transmission lines. The specific patterns are generated from both stable and unstable power swing, and three-phase fault using the wavelet transform technique. Data containing 27,008 continuous samples of 48 different features is used to train a two-layer feed-forward network. The proposed algorithm gives an automatic, setting free and highly accurate classification for the three-phase fault, stable power swing, and unstable power swing through pattern recognition within a half cycle. The proposed algorithm uses the Kundur 2-area system and a 29-bus electric network for testing under different swing center locations and levels of renewable power penetration. Hardware-in-the-loop (HIL) tests show the hardware compatibility of the developed out-of-step algorithm. The proposed algorithm is also compared with recently reported algorithms. The comparison and test results on different large-scale systems show that the proposed algorithm is simple, fast, accurate, and HIL tested, and not affected by changes in power system parameters.
Publisher
Springer Singapore,Power System Protection and Control Press
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