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All Journal International Journal of Power Electronics and Drive Systems (IJPEDS) Perfecting a Video Game with Game Metrics Bulletin of Electrical Engineering and Informatics
Mohd Ruddin Ab Ghani
Universiti Teknikal Malaysia Melaka
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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Sensitivity Analysis and Comparison between 25 kW Parabolic Dish System Mohd Ruddin Ab Ghani; Liaw Geok Pheng; Chin Kim Gan; Tole Sutikno
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 14, No 3: September 2016
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v14i3.4056

Abstract

Dish-Stirling concentrating solar power systems is an efficient and reliable source of renewable energy. In this paper, the proposed model showed the idea of Parabolic Dish (PD) systems with control system model which vary the amount of working gas in the Stirling engine. The control systems were designed using Matlab /Simulink 2012a. Based on the developed linearized model, an improved temperature controller with transient droop characteristic and Mean Pressure Control (MPC) has been proposed. This temperature controller was effective in reducing the temperature and improving performance of the PD system. The overall performance of the system improved more than 78% in output power and energy. Besides, the system improved in term of sensitivity compared with the PD system without compensated. In addition, thermal losses decreased to 97.6% which is directly have significant improvement for the output efficiency to the system. The analysis shows that the PD system is feasible in term of technical but not economically feasible in the Malaysia environment.
K-nearest neighbor and naïve Bayes based diagnostic analytic of harmonic source identification Mohd Hatta Jopri; Mohd Ruddin Ab Ghani; Abdul Rahim Abdullah; Mustafa Manap; Tole Sutikno; Jingwei Too
Bulletin of Electrical Engineering and Informatics Vol 9, No 6: December 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v9i6.2685

Abstract

This paper proposes a comparison of machine learning (ML) algorithm known as the k-nearest neighbor (KNN) and naïve Bayes (NB) in identifying and diagnosing the harmonic sources in the power system. A single-point measurement is applied in this proposed method, and using the S-transform the measurement signals are analyzed and extracted into voltage and current parameters. The voltage and current features that estimated from time-frequency representation (TFR) of S-transform analysis are used as the input for MLs. Four significant cases of harmonic source location are considered, whereas harmonic voltage (HV) and harmonic current (HC) source type-load are used in the diagnosing process. To identify the best ML, the performance measurement of the proposed method including the accuracy, precision, specificity, sensitivity, and F-measure are calculated. The sufficiency of the proposed methodology is tested and verified on IEEE 4-bust test feeder and each ML algorithm is executed for 10 times due to prevent any overfitting result.
Co-Authors Abdelhak Lekbir Abdul Rahim Abdullah Auzani Jidin Chin Kim Gan Jingwei Too Jurifa Lazi Liaw Geok Pheng M.R. Tamjis Md Nazri Othman Mohamad Aqil Mohd Fuad Mohamad Fani Sulaima Mohd Hafiz Jali Mohd Hatta Jopri Muhammad Faez Ali Mustafa Manap Nabil Farah Nur Huda Mohd Amin Rosnani Affandi Rozaimi Ghazali Saif Tahseen Hussein Saif Tahseen Hussein Syariffah Othman Tarmizi Ahmad Izzuddin Tole Sutikno Zanariah Jano