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All Journal Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Indonesian Journal of Electrical Engineering and Computer Science
Shen Yuong Wong
Xiamen University Malaysia
Computer Science & IT Electrical & Electronics Engineering

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Harmonic current classification using hybrid FAM-RBF neural network Shoun Ying Leow; Keem Siah Yap; Shen Yuong Wong
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i3.pp1551-1558

Abstract

In this paper, the type of customers of electricity in Malaysia is classified into the type of electricity consumers based on the harmonic current data. A hybrid of Fuzzy Adaptive Resonance Theory with Mapping Algorithm (Fuzzy ARTMAP) and Radial Basis Function (RBF) neural network is developed (namely FAM-RBF), and it is used to classify the harmonic current into types of consumers. The result of the proposed neural network is discussed, and compared with other neural networks in this paper. The comparison result shows that the proposed FAM-RBF obtained the best performance result and is a truthful neural network to be used in this application.
Predictive-TOPSIS-based MPPT for PEMFC Featuring Switching Frequency Reduction Jye Yun Fam; Shen Yuong Wong; Mohammad Omar Abdullah; Kasumawati Lias; Saad Mekhilef; Hazrul Mohamed Basri
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 11, No 3: September 2023
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v11i3.4350

Abstract

A maximum power point tracking (MPPT) for a proton exchange membrane fuel cell (PEMFC) using a combination of conventional finite control set model predictive control (FCS-MPC) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is proposed in this paper. The key idea is to maximize the power generation from a PEMFC while minimizing the switching frequency of the power converter. The FCS-MPC technique is formulated to track the maximum power of PEMFC highly affected by ever-changing internal parameters. Meanwhile, the TOPSIS algorithm is applied to overcome the potential weaknesses of insulated-gate bipolar transistor (IGBT), which can only withstand a lower switching frequency. In this project, all simulations were run using MATLAB software to display the output power of the PEMFC system. As a result, the proposed predictive-TOPSIS-based MPPT algorithm can track the MPP for various PEMFC parameters within 0.019 s with an excellent accuracy up to 99.11%. The proposed MPPT technique has fast-tracking of the MPP locus, excellent accuracy, and robustness to environmental changes.
Co-Authors Hazrul Mohamed Basri Jye Yun Fam Kasumawati Lias Keem Siah Yap Mohammad Omar Abdullah Saad Mekhilef Shoun Ying Leow