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AuthorGaouda A.M.
AuthorAbdrabou A.
AuthorShaban K.B.
AuthorKhairalla M.
AuthorAbdrabou A.M.
AuthorEl Shatshat R.
AuthorSalama M.M.A.
Available date2019-10-06T09:38:36Z
Publication Date2018
Publication NameIEEE Transactions on Smart Grid
ResourceScopus
ISSN1949-3053
URIhttp://dx.doi.org/10.1109/TSG.2016.2600680
URIhttp://hdl.handle.net/10576/12105
AbstractThis paper proposes and experimentally validates the functionality of a smart IEC 61850 merging unit (MU) that supports self-healing and asset management functions of future power grids. The proposed MU can operate in a standalone or as an integrated element within a primary substation. The MU communicates with a supervisory control and data acquisition (SCADA) system over Ethernet and WiFi-5 GHz links. A dynamic wavelet-based windowing technique is implemented in the proposed MU to process signals and report limited situation awareness (SA) features. The SA features serve two purposes. First, they can be used by asset management functions to monitor and diagnose the equipment heath condition. Second, they can be employed by self-healing functions in order to detect and anticipate early stages of impending faults masked by high noise. The MU capability to acquire real-time sampling or estimated-time sampling is examined and the impact of wireless sensor network data transfer latency between the proposed MU and an SCADA system is also investigated. Extensive laboratory experiments show promising results for the proposed IEC 61850 MU as a smart tool that can monitor, control, protect, and also initiate corrective actions. 2016 IEEE.
SponsorManuscript received December 14, 2015; revised March 11, 2016 and June 15, 2016; accepted August 8, 2016. Date of publication August 18, 2016; date of current version April 19, 2018. This work was supported by the Qatar National Research Fund (a member of Qatar Foundation) under Grant NPRP 6-711-2-295. Paper no. TSG-01570-2015. A. M. Gaouda is with the American University of the Middle East, Eqaila 15453, Kuwait (e-mail: ahmed.gaouda@aum.edu.kw). A. Abdrabou, M. Khairalla, and A. M. Abdrabou are with the Department of Electrical Engineering, United Arab Emirates University, Al Ain 15551, UAE. K. B. Shaban is with the Computer Science and Engineering Department, Qatar University, Doha 2713, Qatar. R. El Shatshat and M. M. A. Salama are with the University of Waterloo, Waterloo, ON N2L3G1, Canada. Color versions of one or more of the figures in this paper are available online at http://ieeexplore.ieee.org. Digital Object Identifier 10.1109/TSG.2016.2600680
Languageen
PublisherInstitute of Electrical and Electronics Engineers Inc.
Subjectasset management
impending faults
Merging unit
partial discharge
self-healing
wavelet analysis
wireless sensor network
TitleA Smart IEC 61850 Merging Unit for Impending Fault Detection in Transformers
TypeArticle
Pagination1812-1821
Issue Number3
Volume Number9


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