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All Journal International Journal of Power Electronics and Drive Systems (IJPEDS) IAES International Journal of Artificial Intelligence (IJ-AI) Indonesian Journal of Electrical Engineering and Computer Science
Mohd Noor bin Abdullah
Universiti Tun Hussein Onn Malaysia
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

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Journal : IAES International Journal of Artificial Intelligence (IJ-AI)

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Optimization of detection of single line to ground fault by controlling peterson coil through ANFIS Feryal Ibrahim Jabbar; Dur Muhammad Soomro; Adnan Hasan Tawafan; Mohd Noor bin Abdullah; Nur Hanis binti Mohammad Radzi; Mazhar Hussain Baloch
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 9, No 3: September 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1199.318 KB) | DOI: 10.11591/ijai.v9.i3.pp409-416

Abstract

The most common fault in the distribution network is the single line to ground fault (SLGF). With earthling in the distribution network, it causes electrical arc as well as a high voltage in the faulted phase compared to other two healthy phases. It increases the danger of separation and isolation in the power network. One of the classical technique to control the arc is through Peterson Coil (PC), which detects and turns off/reduces the electrical arc making the network safer, increasing its reliability and device's safety. To control the PC, some of the techniques used in this research area are PID, FL, NN etc. This paper presents Adaptive Neural-Fuzzy Inference System (ANFIS) technique to controlling the PC. It gives the best results by detecting the fault, reducing the electrical arc and minimizing the fault current to the rated current in a very short time. Moreover, this research focuses on suppressing fault current by looking at its higher and lower peaks. Also, it calculates the opposing inductance to compensate the capacitance caused. It will save thousands of tons of copper costs. This research was conducted using MATLAB. For the validity of the proposed technique results, PID control technique was used.
Optimization of detection of a single line to ground fault based on ABCNN algorithm Feryal Ibrahim Jabbar; DurMuhammad Soomro; Adnan Hasan Tawafan; Mohd Noor bin Abdullah; Nur Hanis binti Mohammad Radzi; Mazhar Hussain Baloch
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 9, No 4: December 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v9.i4.pp623-629

Abstract

One of the most faults found in the electrical distribution network is a single line to ground fault (SLGF). It can be detected and rectified through many methods. The utilization of Peterson coil (PC), reduces the electrical arcs and make the distribution network safe from damage in contrast to the cost value. This paper focuses on the method for its detection on higher and lower values of the ground fault current (GFC). Moreover, it will identify the capacitance and earth leakage of earthling network lines as well as calculate the opposing inductance to compensate for the cause. It also presents the selfextinguishing of GFC by controlling PC through one of the novel optimization techniques called adaptive and artificial bee colony with network neural (ABCNN) to improve the algorithm's performance, like optimization efficiency, speed, solution, and iteration. As a result, the determination of the GFC equals the sound phase current. Also, the extinguishing of an electric arc results in a short time compared with classical methods. The significant advantage of this research is the increment in the system's reliability, protection of devices as well as saving in copper cost. MATLAB was used to carry out this research. For the validity, the proposed algorithm results were compared with the classical method by creating faults on separate phases also.
Co-Authors Adnan Hasan Tawafan Adnan Hasan Tawafan Asif Ahmed Rahmoon Dur Muhammad Soomro DurMuhammad Soomro Feryal Ibrahim Jabbar Feryal Ibrahim Jabbar Feryal Ibrahim Jabbar Hassan Falah Fakhruldeen Hassan Falah Fakhruldeen Mazhar Hussain Baloch Mazhar Hussain Baloch Mazhar Hussain Baloch Nur Hanis binti Mohammad Radzi Nur Hanis Mohammad Radzi