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All Journal International Journal of Electrical and Computer Engineering International Journal of Power Electronics and Drive Systems (IJPEDS) IAES International Journal of Artificial Intelligence (IJ-AI) TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics Bulletin of Electrical Engineering and Informatics Bulletin of Electrical Engineering and Informatics Indonesian Journal of Electrical Engineering and Computer Science

Ismail Musirin

Universiti Teknologi MARA

Author-ID : 2397306

Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

Published : 54 Documents Claim Missing Document

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Articles

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Development of PV array configuration under different partial shading condition Mohammad Syahir Bin Ishak; Rahmatul Hidayah Salimin; Ismail Musirin; Zulkiffli Abdul Hamid
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 10, No 3: September 2019
Publisher : Institute of Advanced Engineering and Science

This paper investigates the performances of different photovoltaic (PV) array under several shading condition. Four types of photovoltaic array configuration scheme which are ‘Series’ (S), Series-Parallel’ (SP), Total-Cross-Tied’ (TCT), and ‘Bridge-Link’ (BL) array topologies were tested by applying a 6x6 PV array under 6 different shading scenarios. The modeling is developed using Matlab/Simulink. The performances and output characteristics of photovoltaic array are compared and analyzed. System engineer can use the detailed characteristics of different array configuration to approximate the outcome power and pick the best configuration of the system by concerning the current natural condition to enhance the overall efficiency.

Energy efficiency enhancement using dynamic voltage restorer (DVR) Muhammad Murtadha Othman; Nik Muhamad Lokman Fahmi Nek Rakami; Zulkiffli Abdul Hamid; Ismail Musirin; Mohammad Lutfi Othman
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 10, No 3: September 2019
Publisher : Institute of Advanced Engineering and Science

Dynamic voltage restorer (DVR) is a device that can compensate harmonic, voltage sag and voltage swell condition that exists in a three-phase system. Other than that, DVR can also be used to enhance the energy efficiency or energy saving by reducing excessive amount of incoming power via the reduction incoming voltage at allowable limit. The DVR can inject the required voltage in the system so that the interruption of supply voltage can be compensated. The compensation of voltage supply interruption is improved based on the hysteresis voltage output of controller used in the DVR to detect the difference between reference voltage and disrupted voltage. The hysteresis voltage control mainly controlled by relays switching so that the signal can be sent to IGBT switches controller. The hysteresis voltage control and unipolar SPWM is supplied to control the IGBT switches by the DC supply for voltage interruption compensation. The unipolar SPWM technique converts the DC supply voltage into AC supplied voltage, thus making the DVR injection become easier to inject the AC voltage into the system to compensate voltage sag and voltage swell.

Improved reliability assessment of backup battery storage integrated with power supply system in a building Muhammad Murtadha Othman; Muhamad Amirul Naim Mohd Jamaluddin; Faisal Fauzi; Ismail Musirin; Mohammad Lutfi Othman
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 10, No 3: September 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v10.i3.pp1538-1546

This paper presents the improved analysis of reliability for battery storage used in power system. The reliability assessment of this paper includes the evaluation of reliability of the system components, battery module and power electronic components. Battery storage is considered as one of energy storage and energy source that commonly used in power system. The evaluation of the reliability of power systems utilising with the storage batteries is performed by using the Markov chain process. The computation of the reliability is conducted by referring to the generated reliability block begins from power supply system. Every part of the system is evaluated regarding two specific states that are in normal or failure mode. By using the Markov method, the system unavailability and failure frequency can be computed.This paper presents the improved analysis of reliability for battery storage used in power system. The reliability assessment of this paper includes the evaluation of reliability of the system components, battery module and power electronic components. Battery storage is considered as one of energy storage and energy source that commonly used in power system. The evaluation of the reliability of power systems utilising with the storage batteries is performed by using the Markov chain process. The computation of the reliability is conducted by referring to the generated reliability block begins from power supply system. Every part of the system is evaluated regarding two specific states that are in normal or failure mode. By using the Markov method, the system unavailability and failure frequency can be computed.

Supervised evolutionary programming based technique for multi-DG installation in distribution system Muhammad Firdaus Shaari; Ismail Musirin; Muhamad Faliq Mohamad Nazer; Shahrizal Jelani; Farah Adilah Jamaludin; Mohd Helmi Mansor; A.V.Senthil Kumar
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 9, No 1: March 2020
Publisher : Institute of Advanced Engineering and Science

Installing DG in network system, has supported the distribution system to provide the increasing number of consumer demand and load, in order to achieve that this paper presents an efficient and fast converging optimization technique based on a modification of traditional evolutionary programming method for obtain the finest optimal location and power loss in distribution systems. The proposed algorithm that is supervised evolutionary programming is implemented in MATLAB and apply on the 69-bus feeder system in order to minimize the system power loss and obtaining the best optimal location of the distributed generators.

Development of option c measurement and verification model using hybrid artificial neural network-cross validation technique to quantify saving Wan Nazirah Wan Md Adnan; Nofri Yenita Dahlan; Ismail Musirin
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 9, No 1: March 2020
Publisher : Institute of Advanced Engineering and Science

This paper aims to develop a hybrid artificial neural network for Option C Measurement and Verification model to predict monthly building energy consumption. In this work, baseline energy model development using artificial neural networks embedded with artificial bee colony optimization and cross validation technique for a small dataset were considered. Artificial bee colony optimization with coefficient of correlation fitness function was used in optimizing the neural network training process and selecting the optimal values of initial weights and biases. Working days, class days and cooling degree days were used as input meanwhile monthly electricity consumption as an output of artificial neural network. The results indicated that this hybrid artificial neural network model provided better prediction results compared to the other model. The best model with the highest value of coefficient of correlation was selected as the baseline model hence is used to determine the saving.

Continuous domain ant colony optimization for distributed generation placement and losses minimization Zulkiffli Abdul Hamid; Ismail Musirin; Ammar Yasier Azman; Muhammad Murtadha Othman
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 9, No 2: June 2020
Publisher : Institute of Advanced Engineering and Science

This paper proposes a method for distributed generation (DG) placement in distribution system for losses minimization and voltage profile improvement. An IEEE 33-bus radial distribution system is used as the test system for the placement of DG. To facilitate the sizing of DG capacity, a meta-heuristic algorithm known as Continuous Domain Ant Colony Optimization (ACOR) is implemented. The ACOR is a modified version of the traditional ACO which was developed specially for solving continuous domain optimization problem like sizing a set of variables. The objective of this paper is to determine the optimal size and location of DG for power loss minimization and voltage profile mitigation. Three case studies were conducted for the purpose of verification. It was observed that the proposed technique is able to give satisfactory results of real power loss and voltage profile at post-optimization condition. Experiment under various loadings of the test system further justifies the objective of the study.

Killer whale-backpropagation (KW-BP) algorithm for accuracy improvement of neural network forecasting models on energyefficient data Saadi Bin Ahmad Kamaruddin; Nor Azura Md Ghani; Hazrita Ab Rahim; Ismail Musirin
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 8, No 3: September 2019
Publisher : Institute of Advanced Engineering and Science

Green technology building is not newly introduced to the world nor Malaysia, but it is rarely practiced globally and now it has promoted noteworthy due to destructions caused by human hands towards the nature. Now people started to realize that the world is polluted by many hazardous substances. Therefore, Help University came up with the effort of preserving the nature through a new Green Technology campus, which has been fully operated since year 2017. In this research, neural network forecasting models on energy-efficient data of Help University, Subang 2 green technology campus at Subang Bistari, Selangor has been done with respect to value-formoney (VFM) attribute. Previously there were no similar research done on energy-efficient data of Help University, Subang 2 campus. The significant factors with respect to energy or electricity saved (MW/hr) in the year 2017 variable were studied as recorded by Building Automation and Control System (BAS) of Help University Subang 2 campus. Using multiple linear regression (stepwise method), the significant predictor towards energy saved (MW/hr) was Building Energy Index (BEI) (kWh/m2/year) based p-value<α=0.05. A mathematical model was developed. Moreover, the proposed neural network forecasting model using Killer WhaleBackpropagation Algorithm (KWBP) were found to better than existing conventional techniques to forecast BEI data. This research is expected to specifically assist maintenance department of Help University, Subang 2 campus towards load forecasting for power saving planning in years to come.

Exploration on digital marketing as business strategy model among Malaysian entrepreneurs via neurocomputing Hazrita Ab Rahim; Shafaf Ibrahim; Saadi Bin Ahmad Kamaruddin; Nor Azura Md. Ghani; Ismail Musirin
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 9, No 1: March 2020
Publisher : Institute of Advanced Engineering and Science

Artificial Intelligence is great when it comes to routine activities and vast amounts of data are analyzed. This can be done more quickly and efficiently than men. In the world of digital marketing, Artificial Intelligence is quickly coming into play. With Artificial Intelligence joining the digital marketing environment, predicting user behavior, search cycles, and much more will be easier. This can support websites that are highly user-friendly for organizations. Moreover, with the aid of Artificial Intelligence, content creation has become a faster and easier task for brands. Practically, a company's degree of enterprise marketing can have an effect on its overall business efficiency. Entrepreneurial marketing is driven by entrepreneurial opportunities which involves the proactive identification and exploitation of opportunities for acquiring and retaining profitable customers through Digital approaches to risk management, resource leveraging and value creation. This research was done by collecting data using semi structure questionnaire distributed to 169 start up owners in Klang Valley area. Using two-layer 6-3-1 with hyperbolic tangent-purelin configurations neural network model, it was found that proactiveness, risk taking, resource leveraging, opportunity focus, intensity and value add are the significant factors towards digital marketing respectively. It is expected that the findings would give some inputs to the Malaysian entrepreneurs on innovative digital marketing in their businesses, regardless the sizes.

Optimal SVC allocation via symbiotic organisms search for voltage security improvement Mohamad Khairuzzaman Mohamad Zamani; Ismail Musirin; Sharifah Azma Syed Mustaffa; Saiful Izwan Suliman
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 17, No 3: June 2019
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v17i3.9905

It is desirable that a power system operation is in a normal operating condition. However, the increase of load demand in a power system has forced the system to operate near to its stability limit whereby an increase in load poses a threat to the power system security. In solving this issue, optimal reactive power support via SVC allocation in a power system has been proposed. In this paper, Symbiotic Organisms Search (SOS) algorithm is implemented to solve for optimal allocation of SVC in the power system. IEEE 26 Bus Reliability Test System is used as the test system. Comparative studies are also conducted concerning Particle Swarm Optimization (PSO) and Evolutionary Programming (EP) techniques based on several case studies. Based on the result, SOS has proven its superiority by producing higher quality solutions compared to PSO and EP. The results of this study can benefit the power system operators in planning for optimal power system operations.

Load Management for Voltage Control Study Using Parallel Immunized-computational Intelligence Technique Amirul Izzat Abu Bakar; Mohamad Khairuzzaman Mohamad Zamani; Ismail Musirin; Nor Azura Md Ghani
Bulletin of Electrical Engineering and Informatics Vol 7, No 2: June 2018
Publisher : Institute of Advanced Engineering and Science

The increase of power demand is a crucial issue in the power system community in many parts of the world. Malaysia has also witnessed the familiar scenario due to the current development throughout the country has invited the urgency of increase in the power supply. Since Malaysia practices vertical system; where the electricity is supplied by only one utility, load management is an important issue so that the delivery of electricity is implemented without discrimination. Parallel Computational Intelligence will be developed which can alleviate and avoid all the unsolved issues, highlighting the weakness of current schemes. Parallel Computational Intelligence is developed to manage the optimal load in making sure the system maintains the stability condition, within the voltage limits. This paper presents evolutionary programming (EP) technique for optimizing the voltage profile. In this study, 3 algorithms which are Gaussian, Cauchy and Parallel EP were developed to solve optimal load management problem on IEEE 26-bus Reliability Test System (RTS). Results obtained from the study revealed that the application of Parallel EP has significantly reduced the time for the optimization process to complete.

Co-Authors A. V. Senthil Kumar A.V.Senthil Kumar Aainaa Mohd Arriffin Abdul Kadir Ismail Afdallyna Fathiyah Harun Afdallyna Harun Ahmad Farid Abidin Ahmad Faris Akhtar Kalam Amirul Asyraf Mohd Kamaruzaman Amirul Izzat Abu Bakar Ammar Yasier Azman Anthony Wijoyo Azhan Ab. Rahman Bibi Norasiqin Sheikh Rahimullah Dalina Johari Faisal Fauzi Faisal Zahari Farah Adilah Jamaludin Hadi Suyono Halim Hassan Hamizan Suhaimi Hari Santoso Hasmaini Mohamad Hazrita Ab Rahim Hishamuddin Hashim Hishamuddin Hashim Kamrul Hasan Mazliya Mohd Baharun Mohamad Khairuzzaman Mohamad Zamani Mohamad Sabri Omar Mohammad Lutfi Othman Mohammad Syahir Bin Ishak Mohd Affendi Ismail Salim Mohd Helmi Mansor Mohd. Helmi Mansor Mohd. Murtadha Othman Mohd. Murthada Othman Mudjirahardjo, Panca Muhamad Amirul Naim Mohd Jamaluddin Muhamad Faliq Mohamad Nazer Muhamad Firdaus Zambri Muhamad Nabil Hidayat Muhammad Amirul Adli Nan Muhammad Firdaus Shaari Muhammad Haziq Suhaimi Muhammad Murtadha Othman Muhammad Murtadha Othman Muhd Azri Abdul Razak Murizah Kassim Muzaiyanah Hidayab Naeem M. S. Honnoon Nik Fasdi Nik Ismail Nik Muhamad Lokman Fahmi Nek Rakami Nofri Yenita Dahlan Nor Azura Md Ghani Nor Azura Md. Ghani Nor Zulaily Mohamad Norazan Mohamed Norazan Mohamed Ramli Norazan Mohammed Ramli Norazlan Hashim Nur Ainna Shakinah Abas Nur Ashida Salim Nur Ashida Salim Nur Azimah Abdul Rahim Nur Azwan Mohamed Kamari Nur Zahirah Mohd Ali R. A. Setyawan Rahmatul Hidayah Salimin Rini Hasanah Rini Nur Hasanah Roslina Mohamad Saadi Ahmad Kamaruddin Saadi Bin Ahmad Kamaruddin Saadi bin Ahmad Kamaruddin Saadi Bin Ahmad Kamaruddin Saiful Amri Ismail Saiful Izwan Suliman Shafaf Ibrahim Shahrani Shahbudin Shahril Irwan Sulaiman Shahrizal Jelani Sharifah Azma Syed Mustaffa Sharifah Azwa Shaaya Siti Amely Jumaat Suyono, Hadi Syed Mohamad Hisyam Wan Dawi Sylvester Jipinus Tarek Bouktir Unggul Wibawa W Muhammad Faizol bin W Mustapha Wan n Nazirah Wan Md Adna Wan Nazirah Wan Md Adnan Wan Nazirah Wan Md Adnan Zilaila Zakaria Zulkiffli Abdul Hamid Zulkiffli Bin Abdul Hamid Zulkifli Othman

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