Earth-Fault Detection Using Fuzzy Logic in Electrical Distribution Networks

Abstract: The optimal functioning of electrical distribution networks is to maintain the voltage to acceptable limits in order not to affect the insulation of the electric lines. During a nominal regime the voltage variation is not so big due to the several voltage regulation methods, but during a fault regime, usually during earth-faults can occur overvoltages that affect the line insu­lation. That is why earth-fault must identified and eliminated as quickly as possible.

In the present medium voltage networks, the earth-fault detection is made using the admittance and current injection method. That means that in the normal regime, the system measures the reference homopolar admittances of every electric line that is supplied from the substation busbar after each tun­ning cycle for the Petersen Coil. By injecting a current in the coil it can discov­er the line with the biggest asymmetry in a 20-30ms time interval, which is the earth-faulted line. This method is perfectly functional when is precisely known the homopolar current and the capacitive current of the grid. There are pro­jects where the Holmgreen filter is chosen with a big nominal current and the measuring of the homopolar current is done with errors because of the small earth-fault current in the medium voltage networks with Petersen coil and this way the earth-fault detection can function with errors. The classic meth­od needs precise data in order to have good results.

The article is researching the possibility of detecting the earth-faults with fuzzy logic. The fuzzy logic uses artificial intelligence and allows earth-fault detection even if the input data is not so accurate because of the errors giv­en by the instrument transformers. So using several logic rules, the phase and the circuit with earth fault can be successfully identified even if the input data is not so precise.

The expert fuzzy systems can be successfully used in earth-fault detection and also in detecting any kind of fault with superior results to the classical meth­od because using the data with errors can obtain good results using the logic small, normal, and big for currents and voltages in the system can take deci­sions similar to the human operator.

9th International Scientific ERAZ Conference – ERAZ 2023 – Conference Proceedings: KNOWLEDGE BASED SUSTAINABLE DEVELOPMENT, hybrid – online, virtually and in person, Prague, Czech Republic, June 1, 2023

ERAZ Conference Proceedings published by: Association of Economists and Managers of the Balkans – Belgrade, Serbia

ERAZ conference partners: Faculty of Logistics, University of Maribor, Maribor (Slovenia); University of National and World Economy – UNWE, Sofia (Bulgaria); Center for Political Research and Documentation (KEPET), Research Laboratory of the Department of Political Science of University of Crete (Greece); Institute of Public Finance – Zagreb (Croatia); Faculty of Tourism and Hospitality Ohrid, University of St. Kliment Ohridski from Bitola (North Macedonia)

ERAZ Conference 2023 Conference Proceedings: ISBN 978-86-80194-72-1, ISSN 2683-5568, DOI: https://doi.org/10.31410/ERAZ.2023

Creative Commons Non Commercial CC BY-NC: This article is distributed under the terms of the Creative Commons Attribution-Non-Commercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission. 

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Additional reading

Keshtkar, A., & Arzanpour, S. (2016). An Adaptive Fuzzy Logic for Residential Energy Man­agement in Smart Grid Environments. Simon Fraser University.

Srivani, S. G., Kumar, A., Patil, A. U., & Praveen, G. (Year). Fuzzy Logic Technique for Smart Grid Fault Detection