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IDM based on image classification with CNN

Content Provider	IET Digital Library
Author	Manikonda, Santhosh K. G. Gaonkar, Dattatraya N.
Abstract	Distributed generation (DG) has seen tremendous growth to meet the needs of ever-increasing energy demand. Most of these distributed sources are renewable in nature and connected at the consumer end. The increasing penetration of DG sources has made their control and operation complex. One of the issues that are responsible for this increased complexity is islanding. This study presents a new islanding detection method (IDM) that is based on deep learning approach, using a convolution neural network (CNN). The proposed method first converts time-series data to images and then uses them to train and test the designed CNN. A CNN is specifically designed to perform islanding detection. The results using the designed CNN are compared with IDMs based on artificial NN and support vector machine. These comparisons show that islanding detection performed using deep learning technique has better detection accuracy. Also, the proposed method performs well even for noisy data.
Starting Page	7256
Ending Page	7262
Page Count	7
Volume Number	2019
e-ISSN	20513305
Issue Number	Issue 10, Oct (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/joe/2019/10
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/joe.2019.0025
Journal	The Journal of Engineering
Publisher	The Institution of Engineering and Technology
Publisher Date	2019-05-13
Access Restriction	Open
Rights License	Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/)
Subject Keyword	CNN Computer Vision And Image Processing Technique Convolution Neural Network Convolutional Neural Nets Deep Learning Approach Deep Learning Technique Detection Accuracy DG Sources Distributed Generation Distributed Power Generation Distributed Sources Distribution Network Energy Demand IDM Image Classification Image Recognition Islanding Detection Method Knowledge Engineering Technique Learning in AI Neural Computing Technique Operation Complex Power Distribution Fault Power Engineering Computing Support Vector Machine Time Series Time-series Data
Content Type	Text
Resource Type	Article

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