Regulated Two-Dimensional Deep Convolutional Neural Network-Based Power Quality Classifier for Microgrid

Regulated Two-Dimensional Deep Convolutional Neural Network-Based Power Quality Classifier for Microgrid

Show other versions (1)

Due to the penetration of renewable energy and load variation in the microgrid, the diagnosis of power quality disturbances (PQD) is important to the operation stability and safety of the microgrid system. Once the power imbalance is present between the generation and the load demand, the fundamenta...

Full description

Bibliographic Details
Main Authors: Berutu, S.S (Author), Chen, C.-H (Author), Chen, C.-I (Author), Chen, Y.-C (Author), Yang, H.-C (Author)
Format: Article
Language:English
Published: MDPI 2022
Subjects:
Convolution
Convolutional neural networks
Deep neural networks
Disturbances classification
Fundamental frequencies
IEEE Standards
IEEE Std 1159
IEEE Std. 1159
microgrid
Microgrid
Microgrids
Natural frequencies
Network-based
Power quality
power quality classifier
Power quality classifier
power quality disturbances
Power quality disturbances
regulated two-dimensional deep convolutional neural network
Regulated two-dimensional deep convolutional neural network
signal synchronization
Signal synchronization
Two-dimensional
Online Access:View Fulltext in Publisher

Similar Items

Similar Items