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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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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.

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.

Dynamic Economic Dispatch Assessment Using Particle Swarm Optimization Technique Muhammad Murtadha Othman; Mohd Affendi Ismail Salim; Ismail Musirin; Nur Ashida Salim; Mohammad Lutfi Othman
Bulletin of Electrical Engineering and Informatics Vol 7, No 3: September 2018
Publisher : Institute of Advanced Engineering and Science

This paper presents the application of particle swarm optimization (PSO) technique for solving the dynamic economic dispatch (DED) problem. The DED is one of the main functions in power system planning in order to obtain optimum power system operation and control. It determines the optimal operation of generating units at every predicted load demands over a certain period of time. The optimum operation of generating units is obtained by referring to the minimum total generation cost while the system is operating within its limits. The DED based PSO technique is tested on a 9-bus system containing of three generator bus, six load bus and twelve transmission lines.

Integrated monte carlo-evolutionary programming technique for distributed generation studies in distribution system Nur Ainna Shakinah Abas; Ismail Musirin; Shahrizal Jelani; Mohd Helmi Mansor; Naeem M. S. Honnoon; Muhammad Murtadha Othman
Bulletin of Electrical Engineering and Informatics Vol 8, No 3: September 2019
Publisher : Institute of Advanced Engineering and Science

This paper presents the optimal multiple distributed generations (MDGs) installation for improving the voltage profile and minimizing power losses of distribution system using the integrated monte-carlo evolutionary programming (EP). EP was used as the optimization technique while monte carlo simulation is used to find the random number of locations of MDGs. This involved the testing of the proposed technique on IEEE 69-bus distribution test system. It is found that the proposed approach successfully solved the MDGs installation problem by reducing the power losses and improving the minimum voltage of the distribution system.

Optimal population size of particle swarm optimization for photovoltaic systems under partial shading condition Norazlan Hashim; Nik Fasdi Nik Ismail; Dalina Johari; Ismail Musirin; Azhan Ab. Rahman
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i5.pp4599-4613

Particle swarm optimization (PSO) is the most widely used soft computing algorithm in photovoltaic systems to address partial shading conditions (PSC). The success of the PSO run heavily depends on the initial population size (NP). A higher NP increases the probability of a global peak (GP) solution, but at the expense of a longer convergence time. To find the optimal value of NP, a trade-off is typically made between a high success rate and a reasonable convergence time. The most used trade-off method is a trial-and-error approach that lacks explicit guidelines and empirical evidence from detailed analysis, which can affect data reproducibility when different systems are used. Hence, this study proposes an empirical trade-off method based on the performance index (PI) indicator, which takes into account the weighted importance of success rate and convergence time. Furthermore, the impact of NP on achieving a successful PSO was empirically investigated, with the PSO tested with 16 different NPs ranging from 3 to 50, and 10,000 independent runs on various PSC problems. Overall, this study found that the best NP to use was 25, which had the best average PI value of 0.9373 for solving all PSC problems under consideration.

Comparative study of net energy metering and feed-in tariff for the 496kWp UiTM segamat solar photovoltaic system Muhamad Firdaus Zambri; Muhammad Murtadha Othman; Kamrul Hasan; Muhamad Nabil Hidayat; Abdul Kadir Ismail; Ismail Musirin
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 2: August 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i2.pp601-610

The Energy and natural resources ministry (KeTSA) of Malaysia has introduced the net energy metering (NEM) 3.0, which provides an opportunity for consumers to install solar photovoltaic (PV) systems to reduce electricity bills. The NEM 3.0 introduces three new initiatives that offer 500 MW quota from 2021 till 2023. NEM has been implemented since 2016, replacing the feed-in tariff (FiT) strategy by promoting the users to utilize the generated energy in the first place before selling any surplus to the utility. As in the FiT strategy, users can only sell the generated energy at a fixed rate without utilizing it. This paper presents the comparative study between NEM and FiT for 496 kWp solar photovoltaic system in UiTM Segamat, Johor in the perspective of economy and energy practice based on the simulation result of MATLAB/Simulink software.

Energy Efficiency of a Building Using Capacitors Optimization Amirul Asyraf Mohd Kamaruzaman; Muhammad Murtadha Othman; Aainaa Mohd Arriffin; Ismail Musirin; Muhd Azri Abdul Razak; Zilaila Zakaria
Indonesian Journal of Electrical Engineering and Computer Science Vol 8, No 2: November 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v8.i2.pp343-349

This paper presents the optimal location and sizing of capacitors to reduce the total power losses as well as its investment cost for a distribution system in a building. The capacitors location and sizing will be randomly chosen repetitively, via Stochasitic optimization method using MATLAB® and SIMULINK® software. The optimal capacitors location and sizing will be picked via analysis and comparisons between the results. The result shows improvement in power losses with minimal investment cost whilst providing optimal sizing and location of capacitors to be installed in a building.

Multi cases optimal reactive power dispatch using evolutionary programming Rahmatul Hidayah Salimin; Ismail Musirin; Zulkiffli Abdul Hamid; Afdallyna Fathiyah Harun; Saiful Izwan Suliman; Hadi Suyono; Rini Hasanah
Indonesian Journal of Electrical Engineering and Computer Science Vol 17, No 2: February 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v17.i2.pp662-670

Evolutionary Programming (EP) is one of many types in Evolutionary Computation (EC) that used for optimization process. EP technique is used to find the optimal reactive power dispatch (ORPD) since it is one of the accessible options schemes that can be used on the system as a reactive power support. Sometimes, it is not necessary to operate all generators in order to perform ORPD to in achieve the objectives. Also, increment of reactive power load to the system will cause voltage decomposes with the increase in transmission loss in the system. Therefore, the proposed method decides the best grouping of generators that should be operated in system by bearing in mind the transmission loss reduction. ORPD will be used to minimize the transmission loss as well the increasing reactive power loading. This method conducted on IEEE 30-bus Test System with multi cases scenario. The best combination of operating generators determined and the transmission loss after optimization is smaller compared to the transmission loss before optimization resulted.

Prediction of Solar Radiation Intensity using Extreme Learning Machine Hadi Suyono; Hari Santoso; Rini Nur Hasanah; Unggul Wibawa; Ismail Musirin
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 2: November 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i2.pp691-698

The generated energy capacity at a solar power plant depends on the availability of solar radiation. In some regions, solar radiation is not always available throughout the day, or even week, depending on the weather and climate in the area. To be able to produce energy optimally throughout the year, the availability of solar radiation needs to be predicted based on the weather and climate behavior data. Many methods have been so far used to predict the availability of solar radiation, either by mathematical approach, statistical probability, or even artificial intelligence-based methods. This paper describes a method of predicting the availability of solar radiation using the Extreme Learning Machine (ELM) method. It is based on the artificial intelligence methods and known to have a good prediction accuracy. To measure the performance of the ELM method, a conventional forecasting method using the Multiple Linear Regression (MLR) method has been used as a comparison. The implementation of both the ELM and MLR methods has been tested using the solar radiation data of the Basel City, Switzerland, which are available to public. Five years of data have been divided into training data and testing data for 6 case-studies considered. Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) have been used as the parameters to measure the prediction results based on the actual data analysis. The results show that the obtained average values of RMSE and MAE by using the ELM method respectively are 122.45 W/m2 and 84.04 W/m2, while using the MLR method they are 141.18 W/m2 and 104.87 W/m2 respectively. It means that the ELM method proved to perform better than the MLR method, giving 15.29% better value of RMSE parameter and 24.79% better value of MAE parameter.

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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