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

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Symbiotic Organisms Search Technique for SVC Installation in Voltage Control Mohamad Khairuzzaman Mohamad Zamani; Ismail Musirin; Saiful Izwan Suliman
Indonesian Journal of Electrical Engineering and Computer Science Vol 6, No 2: May 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v6.i2.pp318-329

Abstract

Increasing demand experienced by electric utilities in many parts of the world involving developing country is a normal phenomenon. This can be due to the urbanization process of a system network, which may lead to possible voltage decay at the receiving buses if no proper offline study is conducted. Unplanned load increment can push the system to operate closes to its instability point. Various compensation schemes have been popularly invented and proposed in power system operation and planning. This would require offline studies, prior to real system implementation. This paper presents the implementation of Symbiotic Organisms Search (SOS) algorithm for solving optimal static VAr compensator (SVC) installation problem in power transmission systems. In this study, SOS was employed to perform voltage control study in a transmission system under several scenarios via the SVC installation scheme. This realizes the feasibility of SOS applications in addressing the compensating scheme for the voltage control study. Minimum and maximum bound of the voltage at all buses have been considered as the inequality constraints as one of the aspects. A validation process conducted on IEEE 26-Bus RTS realizes the feasibility of SOS in performing compensation scheme without violating system stability. Results obtained from the optimization process demonstrated that the proposed SOS optimization algorithm has successfully reduced the total voltage deviation index and improve the voltage profile in the test system. Comparative studies have been performed with respect to the established evolutionary programming (EP) and artificial immune system (AIS) algorithms, resulting in good agreement and has demonstrated its superiority. Results from this study could be beneficial to the power system community in the planning and operation departments in terms of giving offline information prior to real system implementation of the corresponding power system utility.
Development of Hybrid Artificial Neural Network for Quantifying Energy Saving using Measurement and Verification Wan n Nazirah Wan Md Adna; Nofri Yenita Dahlan; Ismail Musirin
Indonesian Journal of Electrical Engineering and Computer Science Vol 8, No 1: October 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v8.i1.pp137-145

Abstract

This paper presents a Hybrid Artificial Neural Network (HANN) for chiller system Measurement and Verification (M&V) model development. In this work, hybridization of Evolutionary Programming (EP) and Artificial Neural Network (ANN) are considered in modeling the baseline electrical energy consumption for a chiller system hence quantifying saving. EP with coefficient of correlation (R) objective function is used in optimizing the neural network training process and selecting the optimal values of ANN initial weights and biases. Three inputs that are affecting energy use of the chiller system are selected; 1) operating time, 2) refrigerant tonnage and 3) differential temperature. The output is hourly energy use of building air-conditioning system. The HANN model is simulated with 16 different structures and the results reveal that all HANN structures produce higher prediction performance with R is above 0.977. The best structure with the highest value of R is selected as the baseline model hence is used to determine the saving. The avoided energy calculated from this model is 132944.59 kWh that contributes to 1.38% of saving percentage.
Chaotic immune symbiotic organisms search for SVC installation in voltage security control Mohamad Khairuzzaman Mohamad Zamani; Ismail Musirin; Saiful Izwan Suliman; Muhammad Murtadha Othman
Indonesian Journal of Electrical Engineering and Computer Science Vol 16, No 2: November 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v16.i2.pp623-630

Abstract

Parallel with the urbanization of the world, energy demand in the world also increased. The increase in energy demand will require a power system to be operated near its stability limit. To mitigate the problem, Flexible Alternating Current Transmission System (FACTS) devices can be installed as a compensation scheme to improve voltage security in a power system. For an effective compensation, FACTS devices should be optimally allocated in a power system. Although optimization techniques can be implemented to optimally allocate these devices, problems have been reported which would affect the performance of the optimization techniques in terms of producing high quality solutions. This paper presents the implementation of Chaotic Immune Symbiotic Organisms Search for solving optimal Static VAr Compensator (SVC) allocation problem for voltage security control. The optimization is validated in IEEE 26-Bus Reliability Test System (RTS) realizes the capability of CISOS in solving the optimization problem. Comparative studies with respect to Particle Swarm Optimization (PSO) and Evolutionary Programming (EP) resulting in good agreement on the results and demonstrated superior performance of CISOS. Results of the study can be beneficial to power system community in terms of compensation planning prior to real world implementation.
IMLANNs for Congestion Management in Power System Nur Zahirah Mohd Ali; Ismail Musirin; Hasmaini Mohamad; Saiful Izwan Suliman; Hadi Suyono
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 2: August 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v11.i2.pp630-636

Abstract

In this paper, Integrated Multi-Layer Artificial Neural Networks (IMLANNs) model has been developed for congested line prediction in a power system. The master characteristic of an ANN is the superiority to achieve complicated input-output mappings through a learning procedure, without exhaustive programming efforts. The IMLANNs model was developed to predict the congested lines in a power system. Before the IMLANNs model is developed, a case study was selected to receive an early result in power system load current during normal condition and contingency based on heavily loaded term. In order to optimize the architecture of the neural network and minimize the computational effort, but those state variables with major impact on the power system are selected as inputs. A pre-developed index, namely Fast Voltage Stability Index (FVSI) is employed as a benchmark to identify the locations declared as congested lines. This indicator was produced which aims for an analytic thinking, sustainable power system when an excessive load was imposed on the power system network. In addition, voltage collapse can be identified when the index is approaching 1.000 or unity. The value of FVSI is chosen as the targeted output in the IMLANNs model. The strength of the proposed IMLANNs model has been validated on the IEEE 30- Bus RTS. Results obtained from the study demonstrated that the proposed IMLANNs is feasible for congested line prediction, which in turns beneficial to power system operators in the planning unit of a utility.
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