Optimize single line to ground fault detection in distribution grid power system using artificial bee colony

Feryal Ibrahim Jabbar, Feryal Ibrahim Jabbar and Dur Muhammad Soomro, Dur Muhammad Soomro and Mohd Noor Abdullah, Mohd Noor Abdullah and Nur Hanis Mohammad Radzi, Nur Hanis Mohammad Radzi and Mazhar Hussain Baloch, Mazhar Hussain Baloch and Asif Ahmed Rahmoon, Asif Ahmed Rahmoon and Hassan Falah Fakhruldeen, Hassan Falah Fakhruldeen (2023) Optimize single line to ground fault detection in distribution grid power system using artificial bee colony. Indonesian Journal of Electrical Engineering and Computer Science, 31 (3). pp. 1286-1294. ISSN 2502-4752

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Abstract

The most common power system (PS) distribution network fault, single lineto-ground fault (SLGF), causes residual current (I res) to start an electrical arc and high voltage (HV) three times the rated voltage in other healthy phases. HV from capacitive currents (IC) damages cable insulation and PS appliances. Peterson The neutral point coil (PC) reduces (I res) and extinguishes the electric arc, but the fault current (I fault) remains below the protection devices' threshold. Operations and equipment are riskier. PC adaptive eliminates electrical arcs, making the network safer. This paper detects I faults online using Texas instrument validation in MATLAB and adaptive by artificial bee colony (ABC). This paper discusses Texas instrument fault current detection and MATLAB validation. It improves system reliability, device protection, and copper savings by thousands of tons. ABC intelligently optimizes many mathematical problems. ABC with network neural artificial intelligence (AI) improves algorithm performance (artificial bee colony network neural (ABCNN)). This new method may improve distribution network SLGF detection. This first work can work online in electrical power stations by building the (eZdsp F28335-RS232) into the program to send fault signals to the control when SLGF occurs without damaging devices, equipment, cables, or power outages.

Item Type:	Article
Uncontrolled Keywords:	Artificial bee colony Chip of (eZdsp F28335-RS232) Distribution networ Neural network Petersen coil Texas instrument in MATLAB
Subjects:	T Technology > T Technology (General)
Divisions:	Faculty of Electrical and Electronic Engineering > Department of Electronic Enngineering
Depositing User:	Mr. Mohamad Zulkhibri Rahmad
Date Deposited:	15 Jan 2024 07:30
Last Modified:	15 Jan 2024 07:30
URI:	http://eprints.uthm.edu.my/id/eprint/10604

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