Articles
<![CDATA[A Voltage Improvement of Transmission System using Static Var Compensator via Matlab/Simulink ]]>
<![CDATA[Siti Amely Jumaat]]>;
<![CDATA[Ismail Musirin]]>;
<![CDATA[Mazliya Mohd Baharun]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Computer Science Vol 6, No 2: May 2017 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.11591/ijeecs.v6.i2.pp330-337
<![CDATA[High demand in electricity consumption is rising and modern society would case to function without access to electricity. The volume of power transmitted and distributed are increasing, these need the requirements for high quality and reliable supply. At the same time, rising the costs and the growing environmental concerns make the process of develop a new power transmission line make complicated and the time consuming. One of alternatives to solve the issues is installed the Flexible AC Transmission System (FACTS). This research presents to modeling and simulation of Static Var Compensator (SVC) in the power system network using Matlab/Simulink Software. The objective function of this research is improvement the voltage of the system with four cases study for validation. From the simulation results shown that the SVC installation gives the effect to voltage of system.]]>
<![CDATA[Chaos Embedded Symbiotic Organisms Search Technique for Optimal FACTS Device Allocation for Voltage Profile and Security Improvement ]]>
<![CDATA[Mohamad Khairuzzaman Mohamad Zamani]]>;
<![CDATA[Ismail Musirin]]>;
<![CDATA[Saiful Izwan Suliman]]>;
<![CDATA[Tarek Bouktir]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Computer Science Vol 8, No 1: October 2017 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.11591/ijeecs.v8.i1.pp146-153
<![CDATA[Due to the ever-increasing energy demand, power system operators have attempted to cope with these demands while keeping the power system remain operable. Economic constraints have forced the power system operator to abandon their effort in expanding the power system. The increased load demand can cause the power system to suffer from voltage instability and voltage collapse, especially during contingency condition. Hence, a strategy is required to maintain the steady state operation of a power system. Various research has been conducted to tackle this problem. Therefore, this paper presents the implementation of Chaos Embedded Symbiotic Organisms Search technique to solve optimal FACTS device allocation problem in power transmission system. Various practical constraints are also considered in the optimisation process to emulate the real-life constraints in power system. The optimisation process is conducted on a 26-bus IEEE RTS has validated that the results obtained has not violated the power system stability. The results provided by the proposed optimisation technique has successfully improved the voltage profile and voltage security in the system. Comparative studies are also conducted involving Particle Swarm Optimization and Evolutionary Programming technique resulting good results agreement and superiority of the proposed technique. Results obtained from this study would be beneficial to the power system operators regarding optimisation in power system operation for the implementation in real power transmission network.]]>
<![CDATA[Network intrusion detection system by using genetic algorithm ]]>
<![CDATA[Hamizan Suhaimi]]>;
<![CDATA[Saiful Izwan Suliman]]>;
<![CDATA[Ismail Musirin]]>;
<![CDATA[Afdallyna Fathiyah Harun]]>;
<![CDATA[Roslina Mohamad]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Computer Science Vol 16, No 3: December 2019 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.11591/ijeecs.v16.i3.pp1593-1599
<![CDATA[Developing a better intrusion detection systems (IDS) has attracted many researchers in the area of computer network for the past decades. In this paper, Genetic Algorithm (GA) is proposed as a tool that capable to identify harmful type of connections in a computer network. Different features of connection data such as duration and types of connection in network were analyzed to generate a set of classification rule. For this project, standard benchmark dataset known as KDD Cup 99 was investigated and utilized to study the effectiveness of the proposed method on this problem domain. The rules comprise of eight variables that were simulated during the training process to detect any malicious connection that can lead to a network intrusion. With good performance in detecting bad connections, this method can be applied in intrusion detection system to identify attack thus improving the security features of a computer network.]]>
<![CDATA[Optimal sizing of distributed generation using firefly algorithm and loss sensitivity for voltage stability improvement ]]>
<![CDATA[Zulkiffli Bin Abdul Hamid]]>;
<![CDATA[Sylvester Jipinus]]>;
<![CDATA[Ismail Musirin]]>;
<![CDATA[Muhammad Murtadha Othman]]>;
<![CDATA[Rahmatul Hidayah Salimin]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Computer Science Vol 17, No 2: February 2020 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.11591/ijeecs.v17.i2.pp720-727
<![CDATA[This paper proposes an optimization technique for distributed generation (DG) sizing in power system. The DG placement was done through Loss Sensitive (LS) technique to determine the suitable locations. The LS index is calculated such that the change in power losses is divided with generation increment and a rank of buses is obtained to identify the suitable locations for DG placement. Subsequently, a meta-heuristic algorithm, known as Firefly Algorithm (FA) was run to obtain the optimal size or capacity of the DG. The installation takes into consideration the aspect of voltage stability in terms of total real power losses and voltage profiles to be improved in the distribution system. Based on the experiment, the real power losses and voltage profiles were improved significantly as a result of the DG placement. In addition, the installation could prevent the power system from collapse as the reactive loading was increased to maximum.]]>
<![CDATA[Gamma Stirling Engine for a Small Design of Renewable Resource Model ]]>
<![CDATA[Syed Mohamad Hisyam Wan Dawi]]>;
<![CDATA[Muhammad Murtadha Othman]]>;
<![CDATA[Ismail Musirin]]>;
<![CDATA[Amirul Asyraf Mohd Kamaruzaman]]>;
<![CDATA[Aainaa Mohd Arriffin]]>;
<![CDATA[Nur Ashida Salim]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Computer Science Vol 8, No 2: November 2017 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.11591/ijeecs.v8.i2.pp350-359
<![CDATA[This paper presents a research on designing a heat engine known as the Stirling engine. The first task is to study on the background of Stirling engine including its robustness, advantages and disadvantages, history and its ability to produce useful energy. Gamma type Stirling engine will be the main focus for this paper. Thus, an effort has been made in determining a suitable formulation that will be used to design a functioning Gamma Stirling engine. This formulation can be divided into several criteria, the Stirling cycle method used to find the p-V diagram of Stirling engine, the 0th order calculation method used as a preliminary system analysis on the efficiency and performance of the engine and lastly, the Schmidt Analysis whereby used in dealing with the design and development of the engine. This formulation is then arranged accordingly into Excel programming software. As for the hardware analysis, it will be on the performance of the Stirling engine model in term of its electrical power production based on different heat source. At the end of this project, it shows that the obtained formulations can be used in designing the Gamma Stirling engine and are capable to produce an output power from the Stirling engine.]]>
<![CDATA[Harmonic Load Mitigation Using the Optimal Double Tuned Passive Filter Technique ]]>
<![CDATA[Muhammad Murtadha Othman]]>;
<![CDATA[W Muhammad Faizol bin W Mustapha]]>;
<![CDATA[Amirul Asyraf Mohd Kamaruzaman]]>;
<![CDATA[Aainaa Mohd Arriffin]]>;
<![CDATA[Ismail Musirin]]>;
<![CDATA[Nur Ashida Salim]]>;
<![CDATA[Zulkiffli Abdul Hamid]]>;
<![CDATA[Nofri Yenita Dahlan]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Computer Science Vol 6, No 2: May 2017 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.11591/ijeecs.v6.i2.pp338-348
<![CDATA[Harmonic is one of the power quality disturbances customarily imminent in an unbalanced electrical system. Harmonic represents as the multiple integral of fundamental frequency of voltage and current inflicting towards the shifting in system frequency causing to a disruptive operation of electrical devices. This paper investigates on the performance of passive filter intrinsically by utilizing the inductor and capacitor electrical components to mitigate harmonic problem emanating from an unbalanced electrical system. In particular, explication in this paper will focus on the optimal parameters specification for the double tuned passive filter that used to overcome the phenomenon of harmonic issue. The two case studies constituting with different number of harmonic orders injected in a system were introduced to distinguish effectiveness of double tuned passive filter in solving the aforesaid problems. The parameters configuration of the passive filter are automatically tuned by the MATLAB® software to reduce the total harmonic distortion incurred in a system designed under the Simulink® software.]]>
<![CDATA[The Application of Modified Least Trimmed Squares with Genetic Algorithms Method in Face Recognition ]]>
<![CDATA[Nur Azimah Abdul Rahim]]>;
<![CDATA[Nor Azura Md. Ghani]]>;
<![CDATA[Norazan Mohamed]]>;
<![CDATA[Hishamuddin Hashim]]>;
<![CDATA[Ismail Musirin]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Computer Science Vol 8, No 1: October 2017 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.11591/ijeecs.v8.i1.pp154-158
<![CDATA[Severely occluded face images are the main problem in low performance of face recognition algorithms. In this paper, we apply a new algorithm, a modified version of the least trimmed squares (LTS) with a genetic algorithms introduce by [1]. We focused on the application of modified LTS with genetic algorithm method for face image recognition. This algorithm uses genetic algorithms to construct a basic subset rather than selecting the basic subset randomly. The modification in this method lessens the number of trials to obtain the minimum of the LTS objective function. This method was then applied to two benchmark datasets with clean and occluded query images. The performance of this method was measured by recognition rates. The AT&T dataset and Yale Dataset with different image pixel sizes were used to assess the method in performing face recognition. The query images were contaminated with salt and pepper noise. The modified LTS with GAs method is applied in face recognition framework by using the contaminated images as query image in the context of linear regression. By the end of this study, we can determine this either this method can perform well in dealing with occluded images or vice versa.]]>
<![CDATA[Modeling Baseline Energy Using Artificial Neural Network – A Small Dataset Approach ]]>
<![CDATA[Wan Nazirah Wan Md Adnan]]>;
<![CDATA[Nofri Yenita Dahlan]]>;
<![CDATA[Ismail Musirin]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 2: November 2018 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.11591/ijeecs.v12.i2.pp662-669
<![CDATA[In this work, baseline energy model development using Artificial Neural Network (ANN) with resampling techniques; Cross Validation (CV) and Bootstrap (BS) are presented. Resampling techniques are used to examine the ability of the ANN model to deal with a small dataset. Working days, class days and Cooling Degree Days (CDD) are used as ANN input meanwhile the ANN output is monthly electricity consumption. The coefficient of correlation (R) is used as performance function to evaluate the model accuracy. For this analysis, R is calculated for the entire data set (R_all) and separately for training set (R_train), validation set (R_valid) dan testing set (R_test). The closer R to 1, the higher similarities between targeted and predicted output. The total of two different models with several number of neurons are developed and compared. It can be concluded that all models are capable to train the network. Artificial Neural Network with Bootstrap Cross Validation technique (ANN-BSCV) outperforms Artificial Neural Network with Cross Validation technique (ANN-CV). The 3-6-1 ANN-BSCV, with R_train = 0.95668, R_valid = 0.97553, R_test = 0.85726 and R_all = 0.94079 is selected as the baseline energy model to predict energy consumption for Option C IPMVP.]]>
<![CDATA[Chaotic Local Search Based Algorithm for Optimal DGPV Allocation ]]>
<![CDATA[Sharifah Azma Syed Mustaffa]]>;
<![CDATA[Ismail Musirin]]>;
<![CDATA[Mohd. Murtadha Othman]]>;
<![CDATA[Mohamad Khairuzzaman Mohamad Zamani]]>;
<![CDATA[Akhtar Kalam]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 1: July 2018 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.11591/ijeecs.v11.i1.pp113-120
<![CDATA[The advent of advanced technology has led to the increase of electricity demand in most countries in the world. This phenomenon has made the power system network operate close to the stability limit. Therefore, the power utilities are looking forward to the solution to increase the loadability of the existing infrastructure. Integration of renewable energy into the grid such as Distributed Generation Photovoltaic (DGPV) can be one of the possible solutions. In this paper, Chaotic Mutation Immune Evolutionary Programming (CMIEP) algorithm is used as the optimization method while the chaotic mapping was employed in the local search for optimal location and sizing of DGPV. The chaotic local search has the capability of finding the best solution by increasing the possibility of exploring the global minima. The proposed technique was applied to the IEEE 30 Bus RTS with variation of load. The simulation results are compared with Evolutionary Programming (EP) and it is found that CMIEP performed better in most of the cases.]]>
<![CDATA[Active and Reactive Power Scheduling Optimization using Firefly Algorithm to Improve Voltage Stability under Load Demand Variation ]]>
<![CDATA[Mohamad Khairuzzaman Mohamad Zamani]]>;
<![CDATA[Ismail Musirin]]>;
<![CDATA[Halim Hassan]]>;
<![CDATA[Sharifah Azwa Shaaya]]>;
<![CDATA[Shahril Irwan Sulaiman]]>;
<![CDATA[Nor Azura Md. Ghani]]>;
<![CDATA[Saiful Izwan Suliman]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Computer Science Vol 9, No 2: February 2018 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.11591/ijeecs.v9.i2.pp365-372
<![CDATA[This paper presents active and reactive power scheduling using firefly algorithm (FA) to improve voltage stability under load demand variation. The study involves the development of firefly optimization engine for power scheduling process involving the active and reactive power for wind generator. The scheduling optimization of wind generator is tested by using IEEE 30-Bus Reliability Test System (RTS). Voltage stability of the system is assessed based in a pre-developed voltage stability indicator termed as fast voltage stability index (FVSI). This study also considers the effects on the loss and voltage profile of the system resulted from the optimization, where the FVSI value at the observed line, minimum voltage of the system and loss were monitored during the load increment. Results obtained from the study are convincing in addressing the scheduling of power in wind generator. Implementation of FA approach to solve power scheduling revealed its flexibility and feasible for solving larger system within different objective functions.This paper presents active and reactive power scheduling using firefly algorithm (FA) to improve voltage stability under load demand variation. The study involves the development of firefly optimization engine for power scheduling process involving the active and reactive power for wind generator. The scheduling optimization of wind generator is tested by using IEEE 30-Bus Reliability Test System (RTS). Voltage stability of the system is assessed based in a pre-developed voltage stability indicator termed as fast voltage stability index (FVSI). This study also considers the effects on the loss and voltage profile of the system resulted from the optimization, where the FVSI value at the observed line, minimum voltage of the system and loss were monitored during the load increment. Results obtained from the study are convincing in addressing the scheduling of power in wind generator. Implementation of FA approach to solve power scheduling revealed its flexibility and feasible for solving larger system within different objective functions.]]>
