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INDONESIA
Indonesian Journal of Electrical Engineering and Informatics (IJEEI)
Published by IAES Indonesia Section and Partners
ISSN : 20893272     EISSN : -     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) is a peer reviewed International Journal in English published four issues per year (March, June, September and December). The aim of Indonesian Journal of Electrical Engineering and Informatics (IJEEI) is to publish high-quality articles dedicated to all aspects of the latest outstanding developments in the field of electrical engineering. Its scope encompasses the engineering of Telecommunication and Information Technology, Applied Computing & Computer, Instrumentation & Control, Electrical (Power), Electronics, and Informatics.
Arjuna Subject : -
Articles 783 Documents
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Fuzzy Logic Based DTC Control of Synchronous Reluctance Motor Madbouly, Sayed O.
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 12, No 1: March 2024
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v12i1.5372

Abstract

This paper presents the utilization of a fuzzy logic controller (FLC) within the speed control loop of the direct torque control (DTC) algorithm. The aim is to enhance the dynamic performance of a 3-phase synchronous reluctance motor (SynRM) in variable speed applications. The proposed FLC employs the speed error and change of speed error to generate the torque command signal needed for the torque hysteresis comparator within the DTC scheme. The system being analyzed comprises of a synchronous reluctance motor, voltage source converter and the proposed fuzzy logic-based DTC. In order to evaluate the performance of the proposed controller, a comprehensive system model is developed and simulated using MATLAB Simulink. The dynamic response of the entire system is investigated when subjected to various command speeds and loading conditions. It is found that the proposed controller achieves fast and precise dynamic response under all operating conditions. Furthermore, a comparative analysis is conducted between utilizing the FLC and the traditional proportional integral differential (PID) controller in the speed control loop of the DTC, the results demonstrate a significant improvement in the dynamic response when employing FLC compared to the traditional PID controller.
Smart Security Solution for Market Shop Using IoT and Deep Learning Bin Abdul Hai, Talha; Rahman, Wahidur; Hosen, Md Solaiman; Islam, Md. Tarequl; Sadi, A H M Saifullah; Faruque, Gazi Golam; Azad, Mir Mohammad
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 12, No 1: March 2024
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v12i1.4780

Abstract

Nowadays, security system in the market shop is an immense concern everywhere. The modern world is leaning towards intelligent, automated security systems instead of the traditional human-based security or CCTV surveillance system because of their limitations. A typical CCTV surveillance system is not intelligent enough to detect intruders or fire. The proposed security system in this paper is an IoT, deep learning, and GSM based innovative security solution specially designed for shops and offices. The objectives of this system are to prevent burglary and fire. For this, the proposed model focuses on fire and intruder detection through both IoT and deep learning approaches. Several IoT sensors have been utilized with a deep learning model to detect fires in shops or offices at an initial stage. The model also utilizes a current sensor for identifying electrical short-circuit to prevent unexpected damages. This system further utilizes GSM technology to send the corresponding notifications to the authorized user and play alarm sounds at the shop as well as the owner's house while detecting suspicious occurrences. The proposed solution has used two pre-trained Convolutional Neural Network (CNN) architecture, namely ResNet50 and Inception V3. This research found an accuracy of 99.49% with ResNet50 architecture in fire detection.
Ant-Lion Optimization Algorithm Based Optimal Performance of Micro Grids Nagaraju, Samala; Chandramouli, Bethi
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 12, No 1: March 2024
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v12i1.5119

Abstract

In the operational state of an electrical power system, ensuring efficient utilization and high-quality power usage is essential. Various quality enhancement measures, such as linear and adaptive filters, are implemented to improve the current's quality. Additionally, power flow controllers are employed to mitigate losses and enhance fault tolerance. However, the escalating demand for power supply, driven by rapid industrial and urban growth, often exceeds the capacity of existing generation systems. To address this challenge, supplementary subunits are integrated into the power system. This proposal's main objective is to introduce a weight-defined parameter monitoring system for power scheduling within a multi-parameter monitoring framework. The aim is to enhance the conventional preference-based scheduler by incorporating intelligent control techniques, including Unified Power Quality Conditioner (UPQC) with the ANT-LION Optimization (ALO) algorithm, which will be compared to a Fuzzy Logic controller. UPQC plays a pivotal role in addressing power quality issues within the system, combining a shunt active power filter with an Artificial Neural Network (ANN) controlled by the ALO algorithm. Our research demonstrates the effectiveness of this proposed system, particularly in microgrid applications, with validation conducted using MATLAB/Simulink. 
Partition-Based Technique to Enhance Missing Data Prediction Barati Jozan, Mohammad Mahdi; Tabesh, Hamed
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 12, No 1: March 2024
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v12i1.4440

Abstract

Managing missing data is a critical aspect of preprocessing in data mining endeavors, significantly influencing output accuracy during both model development and utilization phases. This study introduces a novel approach to predicting missing values by partitioning data into disjoint subsets based on partitioning measures. The rationale behind this approach is the elimination of unrelated data through partitioning, thereby improving the accuracy of missing value prediction within each subset. Through a combination of expert panel insights and statistical tests (including the Chi-square test and Cramer's V coefficient), the database partitioning measure was determined using operational data from the Mashhad Fire and Safe Services Organization. Models were constructed for each partition, and missing data were segmented accordingly, with the corresponding models employed for prediction. The results revealed that in 44% of cases, models built on partitioned data outperformed those constructed on the entire dataset. The evaluation of this method underscores its capability to predict missing values with heightened accuracy. Notably, this approach is independent of the method employed for missing value prediction, enabling seamless integration into existing methods as an additional step to bolster prediction accuracy.  
Intelligent Bankruptcy Prediction Models Involving Corporate Governance Indicators, Financial Ratios and SMOTE Idhmad, Azzeddine; Kaicer, Mohammed; Nejjar, Chaymae; Benjouad, Abdelghani
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 12, No 1: March 2024
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v12i1.5241

Abstract

This study enhances bankruptcy prediction models by investigating synergies between predictors, utilizing a diverse dataset of financial statements and corporate governance data. Rigorous feature selection identifies key financial ratios (FRs) and corporate governance indicators (CGIs) to enhance model interpretability. Multiple machine learning algorithms construct and assess the models, including Logistic Regression, Decision Trees, Random Forests, Support Vector Machines, and Neural Networks. Integration of CGIs with FRs aims to identify effective combinations that improve model performance with an accuracy respectively 90%, 95%, 97%, and 98%. Researchers explore feature weighting techniques and ensemble methods, examining their impact on accuracy, sensitivity, and specificity. The study also explores how regulatory frameworks and governance practices affect bankruptcy prediction, analyzing data across periods to uncover changes in predictive power under varying conditions. The findings have implications for investors, institutions, and policymakers, offering more accurate risk assessments and emphasizing the interplay between financial performance and governance quality for corporate well-being.
Summary on RoF Technologies, Modulations, and Optical Filters: Review Obied, Manea Naif; Askar, Mishari A.
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 12, No 1: March 2024
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v12i1.5354

Abstract

In order to meet the growing need for bandwidth, this article offers a thorough examination of Radio over Fibre (RoF) technology and its integration with wireless communication networks. It starts out by going over the development of wireless networks and the difficulties they encounter, like spectral congestion and RF spectrum operational constraints. An effective way to handle data traffic is to include optical fibre into wireless networks. A detailed analysis is conducted of the technical features of RoF systems, including modulation approaches such as external and direct modulation. While external modulation provides better performance by getting around constraints, direct modulation uses the RF signal to directly modify the brightness of the light source. It is detailed how optical filters, including Fabry-Perot, Fiber-Bragg Grating, and Tunable filters, are used in a variety of applications. They provide an explanation of their functions and importance in optical communication. In addition, a thorough review of relevant literature is included in the study, along with a summary of the main conclusions, approaches, goals, drawbacks, and achievements of academic studies on optical communication and RoF systems. This analysis focuses on the field's problems and achievements. In summary, RoF technology integration of optical and wireless networks holds enormous potential to satisfy the changing needs of high-capacity, high-speed wireless communication. In order to effectively utilise the potential of RoF systems and progress contemporary wireless networks, additional study and development work is yet required.
Performance Enhancement of Decode and Forward Relaying Network in a Log- normal Fading Channel using Diversity Technique I, Ojo Samson; O, Abolade Robert; L, Alagbe Oluwaseun; A, Ojerinde Idowu; O, Tooki Oluwaseun
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 12, No 2: June 2024
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v12i2.3846

Abstract

The demand for wireless communication services is increasing daily due to several emerging applications of wireless communication system. However, the services provided by wireless communication is affected by obstruction along the path of propagation resulting in scattering of signal at the receiver. Decode and Forward (DF) relaying network used in addressing the problem also suffer from signal outage at the destination due to inability of relay to decode the transmitted signal at the relay node. Hence, in this paper, performance enhancement of DF relaying network is proposed using Time Diversity (TD) at the source with hybrid Threshold Combiner and Equal Gain Combiner (TC-EGC) at the destination. The various copies of the transmitted signal are received at the DF relay node to carry out relay selection by selecting relay with signal strength greater than the set threshold of 3 dB. The selected relays decode and re-encode the received signal before been propagated to the destination. The various copies of the signal received at the destination with varying paths ‘L’ (2, 3 and 4) are combined using TC-EGC. Mathematical expressions of Outage Probability (OP) and Bit Error Rate (BER) for the proposed technique are derived using Probability Density Function (PDF) of the signal received. The proposed DF technique is simulated using MATLAB R2018a and validated using OP and BER by comparing with the conventional DF cooperative relaying network. The proposed technique improved the performance of conventional DF cooperative relaying network with reduced BER and OP.
A Simple Lyapunov Function Based Control Strategy for Coordinated Transient Stability Enhancement of Power Systems Muluh, Fombu Andrew; Sanjong Dagang, Clotaire Thierry; Jean Pierre, Pesdjock Mathieu; Lionel Leroy, Sonfack; Godpromesse, Kenne
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 12, No 2: June 2024
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v12i2.5489

Abstract

Transient stability is still a serious impediment in power system operation due to their highly nonlinear nature. Over the last decades, a vast number of diverse nonlinear control algorithms for sub-controllers located at the generator subsystem and transmission lines have been developed to boost power system stability. However, for an effective and feasible operation of these power systems, coordination of these sub-controllers is very essential. In this paper, a simple direct Lyapunov based approach for coordinated control is proposed for global enhancement of power system stability. The proposed control scheme is achieved through the coordination of Lyapunov based decentralized steam valve, excitation and SSSC adaptive controllers. To test the efficacy of the proposed scheme, several comparisons in multi-machine fault scenarios with other design coordinated approaches are presented. Numerical simulations demonstrate the swiftness and efficacy of the proposed control scheme in boosting global stability.
Optimal Power Flow with Integrated Large Scale PV Systems: Case of the Algerian solar field Mallem, Aicha; Boudebbouz, Omar
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 12, No 2: June 2024
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v12i2.5465

Abstract

The integration of large-scale solar-photovoltaic generation in the traditional power system complicates the optimal power flow (OPF) problem formulation. In the present paper, the OPF based on the quadratic and cubic fuel cost functions integrating solar energy potential of the south of Algeria is presented. Solar energy has a stochastic behavior described in the proposed methodology by the Beta probability distribution function (βPDF). The corresponding objective functions consider the penalty and reserve costs of large-scale solar-photovoltaic generations. The proposed OPF is solved by particle swarm optimization (PSO) algorithm. Computer simulations have been performed on an Algerian 59 bus test system considering some candidates solar energy source emplacements. The comparison between OPF solutions based on the two aforementioned cost functions has been established. The cubic fuel cost function case shows more environmental pollution reduction as well as satisfying interconnected power demands. Thanks to the PSO algorithm properties used for the OPF resolution, the Algerian solar field seems to be a good opportunity for large-scale solarphotovoltaic generation installations in an oligopolistic and eco-friendly sense.
Examining the ability of Advanced Systems of Wireless Communication Enhanced by IRS Technology Razzaque, Md. Abdur; Mahmud, Ashek Raihan; Islam, Md. Shariful
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 12, No 2: June 2024
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v12i2.5496

Abstract

Intelligent Reflecting Surfaces (IRSs) represents a pivotal component of technology, facilitating the enhancement of wireless communication performance and the manipulation of electromagnetic propagation environment. IRS technology has the remarkable capability to transform wireless channels from highly probabilistic to notably deterministic, effectively mitigating the substantial losses encountered in the millimeterwave (mmWave) band. Our analysis emphasizes how this innovative technology has ushered in a new era in wireless communications. Within the scope of this study, we delved into investigating the effectiveness of IRSassisted wireless transmissions across various scenarios, encompassing both line-of-sight (LOS) and non-line-of-sight (NLOS) conditions. Our investigation involved the simulation of a 32×32 IRS array with a wavelength of 1 meter and an incident angle of 45 degrees. By manipulating the phase shifts of individual IRS elements, we examined their impact on achievable data rates concerning the number of elements. We also explored the relationship between throughput and separation distances, highlighting the significance of IRS placement in achieving optimal data rates. Channel capacity analysis was conducted for single IRS configurations with 50 and 100 elements, as well as dual IRS setups, shedding light on the capacity improvements achievable in different arrangements. Additionally, our study delved into Bit Error Rate (BER) performance in cooperative doubled IRS-aided wireless communication, employing a range of digital modulation techniques across various Signal-to-Noise Ratio (SNR) levels. This insight offers a valuable perspective on the reliability of IRS-aided systems across diverse modulation schemes. We also undertook a comprehensive Spectral Efficiency (SE) analysis, investigating IRS-assisted Multiple-Input, Single-Output (MISO) and Multiple-Input, Multiple-Output (MIMO) communications using various modulation schemes. Finally, we examined path loss characteristics across indoor encompassing different environments, especially at 20 GHz and 28 GHz using vertical to vertical (V-V) polarization. The culmination of this thorough simulation study underscores the tremendous potential of IRS technology in revolutionizing wireless communication across diverse scenarios, offering invaluable insights for future design and development endeavors.

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