Artificial intelligence‐based short‐circuit fault identifier for MT‐HVDC systems-Reference-Cited by-同舟云学术

Artificial intelligence‐based short‐circuit fault identifier for MT‐HVDC systems

Published:2018-04-13 Issue:10 Volume:12 Page:2436-2443
ISSN:1751-8695
Container-title:IET Generation, Transmission & Distribution
language:en
Short-container-title:IET Generation, Transmission & Distribution

Author:

Hossam‐Eldin Ahmed¹,Lotfy Ahmed²,Elgamal Mohammed³,Ebeed Mohammed⁴

Affiliation:

1. Electrical Engineering DepartmentAlexandria UniversityAlexandriaEgypt

2. Electrical and Control Engineering DepartmentArab Academy for Science, Technology and Maritime TransportAlexandriaEgypt

3. Operation Services DepartmentArab Petroleum Pipelines Co. SUMEDAlexandriaEgypt

4. Electromechanical Maintenance DepartmentAlexandria Port AuthorityAlexandriaEgypt

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.2017.1345

Reference50 articles.

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2. Livermor L. Liang J. Ekanayake J.: ‘MTDC VSC technology and its applications for wind power’.2010 45th Int. Universities Power Engineering Conf. (UPEC) Cardiff Wales UK September2010

3. Rui Q. Ohlen C. Solvik J.et al.: ‘Design operation and availability analysis of a multi‐terminal HVDC grid – a case study of a possible offshore grid in the Norwegian sea’.IEEE Trondheim Power Tech Bucharest 2011 pp.1–7

4. Wang S. Li G. Zhou M.et al.: ‘Research on interconnecting offshore wind farms based on multi‐terminal VSC‐HVDC’.Int. Conf. Power System Technology Zhejiang Province China 2010 pp.1–7

5. Multiterminal LVDC system for optimal acquisition of power in wind-farm using induction generators

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