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Islanding Detection for Active Distribution Networks Using a WaveNet+UNet Classifier
Amirhosein Alizadeh
, Seyed Fariborz Zarei
,
Mohammadhadi Shateri
École de technologie supérieure
Systems Engineering Department
LIVIA - Imaging, Vision and Artificial Intelligence Laboratory
Qom University of Technology
Research output
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Contribution to journal
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Journal Article
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peer-review
Overview
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Dive into the research topics of 'Islanding Detection for Active Distribution Networks Using a WaveNet+UNet Classifier'. Together they form a unique fingerprint.
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Engineering
Active Distribution Network
100%
Active Load
50%
Applicability
50%
Artificial Intelligence
100%
Capacitor Bank
50%
Convolutional Layer
50%
Fault Condition
50%
Input Sequence
50%
Input Signal
50%
Inverter
50%
Long Short-Term Memory
50%
Lstm
50%
Network Topology
50%
Q Factor
50%
Reactive Power
50%
Signal-to-Noise Ratio
100%
Keyphrases
AI Approach
50%
Capacitor Bank Switching
50%
Inverter-based Sources
50%
Load Quality Factor
50%
Non-islanding
50%
Residual Connection
50%
U-Net Model
50%
WaveNet
100%
Earth and Planetary Sciences
Artificial Intelligence
100%
Long Short-Term Memory Network
50%
Q Factor
50%
Spatial Analysis
50%
State of the Art
50%
Computer Science
1D Convolutional Layer
50%
Noisy Condition
50%