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Bulletin of Electrical Engineering and Informatics

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Published by Universitas Ahmad Dahlan

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Core Subject : Engineering,

Electrical & Electronics Engineering

Bulletin of Electrical Engineering and Informatics (Buletin Teknik Elektro dan Informatika) ISSN: 2089-3191, e-ISSN: 2302-9285 is open to submission from scholars and experts in the wide areas of electrical, electronics, instrumentation, control, telecommunication and computer engineering from the global world. The journal publishes original papers in the field of electrical, computer and informatics engineering.

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Articles 2,901 Documents

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0.18µm-CMOS Rectifier with Boost-converter and Duty-cycle-control for Energy Harvesting Roskhatijah Radzuan; Mohd Khairul Mohd Salleh; Nuha A. Rhaffor; Shukri Korakkottil Kunhi Mohd
Bulletin of Electrical Engineering and Informatics Vol 7, No 2: June 2018
Publisher : Institute of Advanced Engineering and Science

Existing works on battery-less of energy harvesting systems often assume as a high efficiency of rectifier circuit for power management system. In practice, rectifier circuit often varies with output power and circuit complexity. In this paper, based on a review of existing rectifier circuits for the energy harvesters in the literature, an integrated rectifier with boost converter for output power enhancement and complexity reduction of power management system is implemented through 0.18-micron CMOS process. Based on this topology and technology, low threshold-voltage of MOSFETs is used instead of diodes in order to reduce the power losses of the integrated rectifier circuit. Besides, a single switch with the duty-cycle control is introduced to reduce the complexities of the integrated boost converter. Measurement results show that the realistic performances of the rectifier circuit could be considerably improved based on the performances showed by the existing study.

Results of Fitted Neural Network Models on Malaysian Aggregate Dataset Nor Azura Md Ghani; Saadi Bin Ahmad Kamaruddin; Ismail Musirin; Hishamuddin Hashim
Bulletin of Electrical Engineering and Informatics Vol 7, No 2: June 2018
Publisher : Institute of Advanced Engineering and Science

This result-based paper presents the best results of both fitted BPNN-NAR and BPNN-NARMA on MCCI Aggregate dataset with respect to different error measures. This section discusses on the results in terms of the performance of the fitted forecasting models by each set of input lags and error lags used, the performance of the fitted forecasting models by the different hidden nodes used, the performance of the fitted forecasting models when combining both inputs and hidden nodes, the consistency of error measures used for the fitted forecasting models, as well as the overall best fitted forecasting models for Malaysian aggregate cost indices dataset.

Comparison of Solar Radiation Intensity Forecasting Using ANFIS and Multiple Linear Regression Methods Hadi Suyono; Rini Nur Hasanah; R. A. Setyawan; Panca Mudjirahardjo; Anthony Wijoyo; Ismail Musirin
Bulletin of Electrical Engineering and Informatics Vol 7, No 2: June 2018
Publisher : Institute of Advanced Engineering and Science

Solar radiation forecasting is important in solar energy power plants (SEPPs) development. The electrical energy generated from the sunlight depends on the weather and climate conditions in the area where the SEPPs are installed. The condition of solar irradiation will indirectly affect the electrical grid system into which the SEPPs are injected, i.e. the amount and direction of the power flow, voltage, frequency, and also the dynamic state of the system. Therefore, the prediction of solar radiation condition is very crucial to identify its impact into the system. There are many methods in determining the prediction of solar radiation, either by mathematical approach or by heuristic approach such as artificial intelligent method. This paper analyzes the comparison of two methods, Adaptive Neuro Fuzzy Inference (ANFIS) method, which belongs into the heuristic methods, and Multiple Linear Regression (MLP) method, which uses a mathematical approach. The performance of both methods is measured using the root mean square error (RMSE) and the mean absolute error (MAE) values. The data of the Swiss Basel city from Meteoblue are used to test the performance of the two methods being compared. The data are divided into four cases, being classified as the training data and the data used as predictions. The solar radiation prediction using the ANFIS method indicates the results which are closer to the real measurement results, being compared to the the use MLP method. The average values of RMSE and MAE achieved are 123.27 W/m2 and 90.91 W/m2 using the ANFIS method, being compared to 138.70 W/m2 and 101.56 W/m2 respectively using the MLP method. The ANFIS method gives better prediction performance of 12.51% for RMSE and 11.71% for MAE with respect to the use of the MLP method.

Harmonic Contribution Analysis of Electric Arc Furnace by Using Spectrogram M. H. Jopri; A. R. Abdullah; M. Manap; T. Sutikno; M. R. Ab Ghani
Bulletin of Electrical Engineering and Informatics Vol 7, No 2: June 2018
Publisher : Institute of Advanced Engineering and Science

In this paper, spectrogram, a fast and accurate technique is introduced for the analysis of the contribution. Based on a rule-based classifier and the threshold settings that referred to the IEEE Standard 1159 2009, the analysis of the harmonic and interharmonic contribution of EAF are carried out successfully. Moreover, the impact of contribution is measured using total harmonic distortion (THD) and total non-harmonic distortion (TnHD). In addition, spectrogram also gives 100 percent correct detection and able to analyze the contribution impact. It is proven that the proposed method is accurate, fast and cost efficient for analyzing the impact of harmonic and interharmonic of EAF.

An Identification of Multiple Harmonic Sources in a Distribution System by Using Spectrogram M. H. Jopri; A. R. Abdullah; M. Manap; T. Sutikno; M. R. Ab Ghani
Bulletin of Electrical Engineering and Informatics Vol 7, No 2: June 2018
Publisher : Institute of Advanced Engineering and Science

The identification of multiple harmonic sources (MHS) is vital to identify the root causes and the mitigation technique for a harmonic disturbance. This paper introduces an identification technique of MHS in a power distribution system by using a time-frequency distribution (TFD) analysis known as a spectrogram. The spectrogram has advantages in term of its accuracy, a less complex algorithm, and use of low memory size compared to previous methods such as probabilistic and harmonic power flow direction. The identification of MHS is based on the significant relationship of spectral impedances, which are the fundamental impedance (Z1) and harmonic impedance (Zh) that estimate the time-frequency representation (TFR). To verify the performance of the proposed method, an IEEE test feeder with several different harmonic producing loads is simulated. It is shown that the suggested method is excellent with 100% correct identification of MHS. The method is accurate, fast and cost-efficient in the identification of MHS in power distribution arrangement.

Performance Comparison of Artificial Intelligence Techniques for Non-intrusive Electrical Load Monitoring Khairuddin Khalid; Azah Mohamed; Ramizi Mohamed; Hussain Shareef
Bulletin of Electrical Engineering and Informatics Vol 7, No 2: June 2018
Publisher : Institute of Advanced Engineering and Science

The increased awareness in reducing energy consumption and encouraging response from the use of smart meters have triggered the idea of non-intrusive load monitoring (NILM). The purpose of NILM is to obtain useful information about the usage of electrical appliances usually measured at the main entrance of electricity to obtain aggregate power signal by using a smart meter. The load operating states based on the on/off loads can be detected by analysing the aggregate power signals. This paper presents a comparative study for evaluating the performance of artificial intelligence techniques in classifying the type and operating states of three load types that are usually available in commercial buildings, such as fluorescent light, air-conditioner and personal computer. In this NILM study, experiments were carried out to collect information of the load usage pattern by using a commercial smart meter. From the power parameters captured by the smart meter, effective signal analysis has been done using the time time (TT)-transform to achieve accurate load disaggregation. Load feature selection is also considered by using three power parameters which are real power, reactive power and the TT-transform parameters. These three parameters are used as inputs for training the artificial intelligence techniques in classifying the type and operating states of the loads. The load classification results showed that the proposed extreme learning machine (ELM) technique has successfully achieved high accuracy and fast learning compared with artificial neural network and support vector machine. Based on validation results, ELM achieved the highest load classification with 100% accuracy for data sampled at 1 minute time interval.

Noise and Bandwidth Consideration in Designing Op-Amp Based Transimpedance Amplifier for VLC Trio Adiono; Rachmad Vidya Wicaksana Putra; Syifaul Fuada
Bulletin of Electrical Engineering and Informatics Vol 7, No 2: June 2018
Publisher : Institute of Advanced Engineering and Science

In a visible light communication (VLC) system, there are many modules involved. One of the important modules is Transimpedance Amplifier (TIA) that resides in the analog front-end receiver (Rx-AFE). TIA is responsible for performing signal conversion from current signal, which is provided from the photodiode (PD) to voltage signal. It is the reason why the TIA should be operating in low noise condition and wide bandwidth of frequency. These will enable a flexible coverage of the VLC system in performing its signal processing. Hence, in this research, we provide considerations of the noise and frequency bandwidth analysis in designing TIA to cope with the required design specification of a VLC system.

Sabah Traditional Chinese Medicine Database Aslina Baharum; Neoh Yee Jin; Shaliza Hayati A. Wahab; Mohd Helmy Abd Wahab; Radzi Ambar; Nurul Hidayah Mat Zain
Bulletin of Electrical Engineering and Informatics Vol 7, No 3: September 2018
Publisher : Institute of Advanced Engineering and Science

As technology grows, people tend to use or apply anything digitalized instead of printed, especially for references. This is because the printed form references are not easy to find. Even if the references are found successfully, it has already cost a lot of time, money, energy, etc. At the same time, people also put more emphasize on health issues. They are beginning to be more alert in fields that they have ignored before, such as traditional medicine and Chinese medicine. Based on these two points, it can be said that the effort of transforming Traditional Chinese Medicine (TCM) from printed based reference into online reference as a database is a public beneficial effort. There are a lot of online TCM database outside of Malaysia, especially from the People’s Republic of China, Hong Kong, and Taiwan. Those herbal remedies from overseas are somewhat different from the herbal remedies in Malaysia due to the habits and occurrences of the herbs. Through this project, it is hoped that this database will help the local people to discover and identify the herbs that they could find in the surrounding area. The objectives of this project are to identify the validity of the information of the Sabah TCM using mixed method, to develop the Sabah TCM database, and finally to evaluate the usability of the database designed using meCUE. The methodology used was 4D Appreciative Inquiry Model, which included discovery, dream, design, and destiny phases. The advantage of this model was to take a positive core to make any changes instead of finding the weaknesses of the project. Hopefully through the developed database, local Sabahan can take the advantage in identifying the proper usage of existing herbs in their surroundings.

Estimation of Photovoltaic Module Parameters based on Total Error Minimization of I-V Characteristic M. N. Abdullah; M. Z. Hussin; S. A. Jumaat; N. H. Radzi; Lilik J. Awalin
Bulletin of Electrical Engineering and Informatics Vol 7, No 3: September 2018
Publisher : Institute of Advanced Engineering and Science

Mathematical Modelling of photovoltaic (PV) modules is important for simulation and performance analysis of PV system. Therefore, an accurate parameters estimation is necessary. Single-diode and two-diode model are widely used to model the PV system. However, it required to determine several parameters such as series and shunt resistances that not provided in datasheet. The main goal of PV modelling technique is to obtain the accurate parameters to ensure the I-V characteristic is closed to the manufacturer datasheet. Previously, the maximum power error of calculated and datasheet value are considered as objective to be minimized for both models. This paper proposes the PV parameter estimation model based minimizing the total error of open circuit voltage (VOC), short circuit current (ISC) and maximum power (PMAX) where all these parameters are provided by the manufacturer. The performance of single-diode and two-diode models are tested on different type of PV modules using MATLAB. It found that the two-diode model obtained accurate parameters with smaller error compared to single-diode model. However, the simulation time is slightly higher than single-diode model due extra calculation required.

GA-based Optimisation of a LiDAR Feedback Autonomous Mobile Robot Navigation System Siti Nurhafizah Anual; Mohd Faisal Ibrahim; Nurhana Ibrahim; Aini Hussain; Mohd Marzuki Mustafa; Aqilah Baseri Huddin; Fazida Hanim Hashim
Bulletin of Electrical Engineering and Informatics Vol 7, No 3: September 2018
Publisher : Institute of Advanced Engineering and Science

Autonomous mobile robots require an efficient navigation system in order to navigate from one location to another location fast and safe without hitting static or dynamic obstacles. A light-detection-and-ranging (LiDAR) based autonomous robot navigation is a multi-component navigation system consists of various parameters to be configured. With such structure and sometimes involving conflicting parameters, the process of determining the best configuration for the system is a non-trivial task. This work presents an optimisation method using Genetic algorithm (GA) to configure such navigation system with tuned parameters automatically. The proposed method can optimise parameters of a few components in a navigation system concurrently. The representation of chromosome and fitness function of GA for this specific robotic problem are discussed. The experimental results from simulation and real hardware show that the optimised navigation system outperforms a manually-tuned navigation system of an indoor mobile robot in terms of navigation time.

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