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Zali, Samila Mat
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Computer Science & IT Electrical & Electronics Engineering

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Multiple faults detection in doubly-fed induction generator wind turbine using artificial neural network Fadzail, Noor Fazliana; Zali, Samila Mat; Mid, Ernie Che
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 3: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i3.pp3342-3349

Abstract

The development of fault detection methods in wind turbine (WT), especially for single fault detection, is continuously increasing. However, the rapid growth of fault detection in WT leads to another challenge where multiple faults can occur. The single fault detection method in WT is no longer reliable, especially when multiple faults occur simultaneously. Therefore, multiple faults detection in doubly-fed induction generators (DFIG) WT was proposed using an artificial neural networks (ANN) model. These multiple faults include internal and external stator faults happening simultaneously. Internal stator faults cover inter-turn short circuit faults and open circuit faults, while external stator faults cover loss of excitation and external short circuit faults. The performance of the developed multiple faults detection model was measured using accuracy and the root mean square error (RMSE) value. The results show that the developed model performs well with high accuracy and a low RMSE value. Thus, the developed model can accurately detect the coexistence of multiple faults in DFIG WT.
Varying the energisation condition to mitigate sympathetic inrush current Nadhirah, Nurul Fatin; Halim, Hana Abdull; Mukhtar, Nurhakimah Mohd; Zali, Samila Mat
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 6: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i6.pp5975-5985

Abstract

Transformers are generally easy to access and can contribute significantly to entire power system. When a transformer is turned on for the first time, it produces a magnetising inrush current which acts as a starting current. Energisation of transformer has a substantial impact on inrush current and transformer that are connected in parallel. Sympathetic inrush current is a phenomenon that appears when a transformer is switched-on in network whereas the other transformers that was earlier energised. Besides, when sympathetic inrush phenomena occur, the peak and period fluctuate significantly. In this paper, the transformers will be energised in three different ways and each condition will be explored in depth. The operation time of the transformer’s energisation whether it is energised simultaneously or at different times are tested and analysed in terms of their characteristics. It is performed using power system computer aided design (PSCAD) software, starting with a develop model of the energisation and then generate the outcomes. The results of the simulation demonstrate that energising the transformer in different ways can give different effect on the sympathetic inrush current, as well as the variables that affect it and methods for reducing it.
Co-Authors Fadzail, Noor Fazliana Halim, Hana Abdull Mid, Ernie Che Mukhtar, Nurhakimah Mohd Nadhirah, Nurul Fatin