Automatic Power Quality Disturbance Diagnosis Based on Residual Denoising Convolutional Auto-Encoder

Automatic Power Quality Disturbance Diagnosis Based on Residual Denoising Convolutional Auto-Encoder

With the increasing integration of non-linear electronic loads, the diagnosis and classification of power quality are becoming crucial for power grid signal management. This paper presents a novel diagnosis strategy based on unsupervised learning, namely residual denoising convolutional auto-encoder...

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Bibliographic Details
Main Authors: Jie Liu, Qiu Tang, Wei Qiu, Jun Ma, Yuhong Qin, Biao Sun
Format: Article
Language:English
Published: MDPI AG 2021-08-01
Series:Applied Sciences
Subjects:
automatic extracted features
power quality disturbances
residual denoising convolutional auto-encoder
single-layer convolutional neural network
Online Access:https://www.mdpi.com/2076-3417/11/16/7637

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https://www.mdpi.com/2076-3417/11/16/7637

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