Discrimination of Inrush Currents in Differential Relays

Discrimination of Inrush Currents in Differential Relays | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 6 May 2025 V1 Latest version Share on Discrimination of Inrush Currents in Differential Relays Authors : Robert Ofosu [email protected] and Isaac Oppong-Baah 0009-0009-4426-8600 Authors Info & Affiliations https://doi.org/10.22541/au.174655299.93970055/v1 277 views 183 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract This research addresses the critical challenge of accurately discriminating inrush currents within differential relays, a key component of power transformer protection systems. Differential relays distinguish genuine internal faults from transient events, such as inrush currents and external faults. Failure to make this distinction can lead to false tripping, which, in turn, may result in significant operational disruptions and economic losses. The study employs Discrete Wavelet Transform (DWT) and Adaptive Neuro-Fuzzy Inference System (ANFIS) techniques to develop reliable and intelligent protection systems. This intelligent system distinguishes internal faults from inrush currents and external faults. This system improves traditional remedies such as harmonic blocking and restrain and wave shape recognition techniques. The paper discusses the project’s methods, MATLAB/Simulink simulations, and implications for power transformers in electrical grid stations. The results indicated that this system accurately discriminated inrush currents with a 100% success rate and 91.5% accuracy at a speed of 3.5 ms. Supplementary Material File (fault discrimination draft 2.pdf) Download 1.92 MB Information & Authors Information Version history V1 Version 1 06 May 2025 Copyright This work is licensed under a Non Exclusive No Reuse License. Keywords artificial intelligence fault detection fault diagnosis machine learning power systems Authors Affiliations Robert Ofosu [email protected] University of Mines and Technology View all articles by this author Isaac Oppong-Baah 0009-0009-4426-8600 University of Mines and Technology Faculty of Engineering View all articles by this author Metrics & Citations Metrics Article Usage 277 views 183 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Robert Ofosu, Isaac Oppong-Baah. Discrimination of Inrush Currents in Differential Relays. Authorea . 06 May 2025. DOI: https://doi.org/10.22541/au.174655299.93970055/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu . 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