Classification of multiple power quality events via compressed deep learning-Reference-Cited by-同舟云学术

Classification of multiple power quality events via compressed deep learning

Published:2019-03-27 Issue:6 Volume:29 Page:
ISSN:2050-7038
Container-title:International Transactions on Electrical Energy Systems
language:en
Short-container-title:Int Trans Electr Energ Syst

Author:

Liu Hui¹,Hussain Fida¹²^ORCID,Yue Shen¹,Yildirim Ozal³,Yawar Sheikh Junaid⁴

Affiliation:

1. School of Electrical and Information EngineeringJiangsu University Zhenjiang China

2. Faculty of Engineering Science & TechnologyHamdard University Karachi Pakistan

3. Department of Computer EngineeringMunzur University Tunceli Turkey

4. Department of Electrical EngineeringSir Syed University of Engineering & Technology Karachi Pakistan

Funder

Natural Science Foundation of Jiangsu Province

National Natural Science Foundation of China

Publisher

Hindawi Limited

Subject

Electrical and Electronic Engineering,Energy Engineering and Power Technology,Modeling and Simulation

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/2050-7038.12010

Reference76 articles.

1. Committee EM.IEEE Recommended Practice for Monitoring Electric Power Quality. Paper presented at: IEEE Std2009.

2. Power Quality Issues Concerning Photovoltaic Generation in Distribution Grids

3. JanjiA StajiZP RadoviI.Power quality issues in smart grid environment: Serbian case studies. Paper presented at: Wseas International Conference on Systems2011.

4. AlmeidaAD MoreiraL DelgadoJ.Power quality problems and new solutions.1992.

5. WanY CaoJ ZhangH ZhuZ YaoS.Optimization of the power quality monitor number in smart grid. Paper presented at: IEEE International Conference on Smart Grid Communications2015.

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