Please use this identifier to cite or link to this item: http://elar.urfu.ru/handle/10995/90439
Title: Asset management in grid companies using integrated diagnostic devices
Authors: Gitelman, L. D.
Kozhevnikov, M. V.
Kaplin, D. D.
Issue Date: 2019
Publisher: WITPress
Citation: Gitelman, L. D. Asset management in grid companies using integrated diagnostic devices / L. D. Gitelman, M. V. Kozhevnikov, D. D. Kaplin. — DOI 10.2495/EQ-V4-N3-230-243 // International Journal of Energy Production and Management. — 2019. — Vol. 3. — Iss. 4. — P. 230-243.
Abstract: The digitization of power grids envisages a transition to new models of fault diagnosis, repair and maintenance of electric power grid equipment. The most promising tools for implementing advanced production asset management strategies are integrated technologies that are based on robotic diagnostic platforms, various hardware-software instruments and smart data analysis systems. The article analyzes other countries' experience of developing robotic methods of fault diagnosis and maintenance of overhead power transmission lines, which present a major challenge in terms of monitoring, failure prediction and localized repairs. The Cablewalker robotic system was used as an example for identifying the advantages of integrated diagnostic hardware systems as opposed to traditional methods of power grid equipment maintenance and overhaul. Recommendations are given for adopting the technology in grid companies. During trials of the technology on a 2.34-km section of a power transmission line 112 defects were detected versus three that were identified by means of 'manual' inspection. A digital twin of the transmission line was created to manage its technical condition with regard to various risks. © 2019 WIT Press
Keywords: ASSET MANAGEMENT
DIGITAL TWIN
GRIDS
MAINTENANCE STRATEGIES
OVERHEAD TRANSMISSION LINES
ROBOTIC DIAGNOSIS
URI: http://elar.urfu.ru/handle/10995/90439
Access: info:eu-repo/semantics/openAccess
SCOPUS ID: 85072665322
PURE ID: 10770346
ISSN: 2056-3272
DOI: 10.2495/EQ-V4-N3-230-243
metadata.dc.description.sponsorship: Government Council on Grants, Russian Federation
The work was supported by Act 211 of the Government of the Russian Federation, contract № 02.A03.21.0006.
Appears in Collections:Научные публикации ученых УрФУ, проиндексированные в SCOPUS и WoS CC

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