Convolutional Neural Network‐Based Intelligent Protection Strategy for Microgrids-Reference-Cited by-同舟云学术

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Convolutional Neural Network‐Based Intelligent Protection Strategy for Microgrids

Published:2020-02-28 Issue:7 Volume:14 Page:1177-1185
ISSN:1751-8695
Container-title:IET Generation, Transmission & Distribution
language:en
Short-container-title:IET Generation, Transmission & Distribution

Author:

Bukhari Syed Basit Ali¹^ORCID,Kim Chul‐Hwan²,Mehmood Khawaja Khalid¹,Haider Raza³,Saeed Uz Zaman Muhammad²

Affiliation:

1. US‐Pak Center for Advance Studies in EnergyNational University of Sciences and TechnologyIslamabadPakistan

2. Department of Electrical and Computer EngineeringSungkyunkwan UniversitySuwonRepublic of Korea

3. Electrical Engineering DepartmentBalochistan University of Engineering and TechnologyKhuzdarPakistan

Publisher

Institution of Engineering and Technology (IET)

Subject

Electrical and Electronic Engineering,Energy Engineering and Power Technology,Control and Systems Engineering

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/iet-gtd.2018.7049

Reference31 articles.

1. Predictive analysis of microgrid reliability using a probabilistic model of protection system operation;Xu X.;IEEE Trans. Power Syst.,2017

2. Passive islanding detection scheme based on autocorrelation function of modal current envelope for photovoltaic units;Haider R.;IET Gener. Transm. Distrib.,2017

3. An evaluation strategy for microgrid reliability considering the effects of protection system;Xu X.;IEEE Trans. Power Deliv.,2016

4. Time‐frequency transform‐based differential scheme for microgrid protection

5. Intelligent Fault Detection Scheme for Microgrids With Wavelet-Based Deep Neural Networks

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2. Novel protection method for AC microgrids with multiple distributed generations using Unscented Kalman filter;Electric Power Systems Research;2024-05

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