Articles
<![CDATA[Investigation of distributed generation units placement and sizing based on voltage stability condition indicator (VSCI) ]]>
<![CDATA[Arvind Raj]]>;
<![CDATA[Nur Fadilah Ab Aziz]]>;
<![CDATA[Zuhaila Mat Yasin]]>;
<![CDATA[Nur Ashida Salim]]>
<![CDATA[ International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 10, No 3: September 2019 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijpeds.v10.i3.pp1317-1323
<![CDATA[Voltage instability in power distribution systems can result in voltage collapse throughout the grid. Today, with the advanced of power generation technology from renewable sources, concerns of utility companies are much being focused on the stability of the grid when there is an integration of distributed generation (DG) in the system. This paper presents a study on DG units placement and sizing in a radial distribution network by using a pre-developed index called Voltage Stability Condition Index (VSCI). In this paper, VSCI is used to determine DG placement candidates, while the value of power losses is used to identify the best DG placement. The proposed method is tested on a standard 33-bus radial distribution network and compared with existing Ettehadi and Aman methods. The effectiveness of the method is presented in terms of reduction in power system losses, maximization of system loadability and voltage quality improvement. Results show that VSCI can be utilized as the voltage stability indicator for DG placement in radial distribution power system. The integration of DG is found to improve voltage stability by increasing the system loadability and reducing the power losses of the network.]]>
<![CDATA[Hybrid islanding detection method based on the rate of change of frequency and load impedance ]]>
<![CDATA[Hasmaini Mohamad]]>;
<![CDATA[Zuhaila Mat Yasin]]>;
<![CDATA[Nur Ashida Salim]]>;
<![CDATA[Bibi Norasiqin Sheikh Rahimullah]]>;
<![CDATA[Kanendra Naidu]]>
<![CDATA[ Bulletin of Electrical Engineering and Informatics Vol 10, No 6: December 2021 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/eei.v10i6.3246
<![CDATA[Interconnection of distributed generation (DG) in distribution system will result in formation of islands in the event of loss of main supply. This scenario is harmful to the power system, hence quick detection is critical to halt the formation of islands. Among the common passive and active detection methods available, the hybrid detection method is identified as the most reliable method. This paper proposes a new hybrid method using the combination of passive and active technique which is the rate of change of frequency (ROCOF) and load impedance, respectively. The passive method works when the value of ROCOF exceeds the threshold value which is set at 0.3Hz/s. The active method works when it detects low value of ROCOF and immediately inject a pre-specified load into the system to increase the ROCOF value up to its threshold value. Simulation study on different case studies is carried out on distribution test system to evaluate the performance of the proposed method. Results show that this method is effective in detecting any events that could result in islanding.]]>
<![CDATA[Implementation of artificial intelligence for prediction performance of solar thermal system ]]>
<![CDATA[Mohd Danish Irfan Mohd Sufian]]>;
<![CDATA[Nur Ashida Salim]]>;
<![CDATA[Hasmaini Mohamad]]>;
<![CDATA[Zuhaila Mat Yasin]]>
<![CDATA[ International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 13, No 3: September 2022 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijpeds.v13.i3.pp1751-1760
<![CDATA[A related input parameter is used in this case study to forecast solar thermal systems (STS) capabilities and to compare which artificial neural network (ANN) algorithms and other artificial intelligence (AI) methods have the most reliable predictor for STS performance. In order to gauge the performance of the STS, this research aims to implement AI for predicting STS performance by comparing the ANN technique with other methods. Three different training algorithms which are Levenberg-Marquardt (LM), scaled conjugate gradient (SCG) and Bayesian regularization (BR) are considered in this research. This research will identify acceptable parameters and the best AI technique to use in predicting the STS performance. Previous research on STS demonstrates that the efficiency of STS has been estimated using different input parameters. The results show that the prediction of the LM training algorithm is the best for STS performance.]]>
<![CDATA[Graphical user interface based model for transmission line performance implementation in power system ]]>
<![CDATA[Nur Ashida Salim]]>;
<![CDATA[Hasmaini Mohamad]]>;
<![CDATA[Zuhaila Mat Yasin]]>;
<![CDATA[Nur Fadilah Ab Aziz]]>;
<![CDATA[Nur Azzammudin Rahmat]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Computer Science Vol 16, No 1: October 2019 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijeecs.v16.i1.pp92-100
<![CDATA[Transmission line is one of the important elements in the process of power transfer from the source of generation to the consumer. In order to analyze the performance of a transmission line, it has to be represented by an equivalent model with suitable circuit parameters at a per phase basis. The line models are used to measure voltages, currents and the amount of power flow depending on the line length. Transmission line performance is determined by the voltage regulation and its efficiency under their normal operating conditions. In this study, a systematic approach was developed in order to assists the lecturers in teaching this important topic to the students despite so many complicated mathematical equations involved in the calculation. With the aid of Graphical User Interface (GUI), the performance of transmission line can be determined and monitored due to the change of line parameters. The results obtained could assist the lecturers in delivering the concept of engineering in a more systematic approach. On top of that, it could also assist the power system utility in planning the transmission line that needed to be installed in the system.]]>
<![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 ]]>
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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 ]]>
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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[Optimal Charging Schedule Coordination of Electric Vehicles in Smart Grid ]]>
<![CDATA[Wan Iqmal Faezy Wan Zalnidzam]]>;
<![CDATA[Hasmaini Mohamad]]>;
<![CDATA[Nur Ashida Salim]]>;
<![CDATA[Hazlie Mokhlis]]>;
<![CDATA[Zuhaila Mat Yasin]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 1: July 2018 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijeecs.v11.i1.pp82-89
<![CDATA[The increasing penetration of electric vehicle (EV) at distribution system is expected in the near future leading to rising demand for power consumption. Large scale uncoordinated charging demand of EVs will eventually threatens the safety operation of the distribution network. Therefore, a charging strategy is needed to reduce the impact of charging. This paper proposes an optimal centralized charging schedule coordination of EV to minimize active power losses while maintaining the voltage profile at the demand side. The performance of the schedule algorithm developed using particle swarm optimization (PSO) technique is evaluated at the IEEE-33 Bus radial distribution system in a set time frame of charging period. Coordinated and uncoordinated charging schedule is then compared in terms of active power losses and voltage profile at different level of EV penetration considering 24 hours of load demand profile. Results show that the proposed coordinated charging schedule is able to achieve minimum total active power losses compared to the uncoordinated charging.]]>
<![CDATA[Impact of Distributed Generation on the Fault Current in Power Distribution System ]]>
<![CDATA[Zuhaila Mat Yasin]]>;
<![CDATA[Izni Nadhirah Sam’ón]]>;
<![CDATA[Norziana Aminudin]]>;
<![CDATA[Nur Ashida Salim]]>;
<![CDATA[Hasmaini Mohamad]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Computer Science Vol 6, No 2: May 2017 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijeecs.v6.i2.pp357-367
<![CDATA[Monitoring fault current is very important in power system protection. Therefore, the impact of installing Distributed Generation (DG) on the fault current is investigated in this paper. Three types of fault currents which are single line-to-ground, double line-to-ground and three phase fault are analyzed at various fault locations. The optimal location of DG was identified heuristically using power system simulation program for planning, design and analysis of distribution system (PSS/Adept). The simulation was conducted by observing the power losses of the test system by installing DG at each load buses. Bus with minimum power loss was chosen as the optimal location of DG. In order to study the impact of DG to the fault current, various locations and sizes of DG were also selected. The simulations were conducted on IEEE 33-bus distribution test system and IEEE 69-bus distribution test system. The results showed that the impact of DG to the fault current is significant especially when fault occurs at busses near to DG location.]]>
<![CDATA[Power system restoration in distribution network using minimum spanning tree - Kruskal’s algorithm ]]>
<![CDATA[Hasmaini Mohamad]]>;
<![CDATA[Wan Iqmal Faezy Wan Zalnidzham]]>;
<![CDATA[Nur Ashida Salim]]>;
<![CDATA[Shahrani Shahbudin]]>;
<![CDATA[Zuhaila Mat Yasin]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Computer Science Vol 16, No 1: October 2019 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijeecs.v16.i1.pp1-8
<![CDATA[Events such as natural and manmade interference, line, transformer and feeder outages that occur in electric power distribution system negatively impact the continuity of power supply, thus affecting the power demand supply as well as customer’s satisfaction. In that cases, the restoration of power needs to be carried out immediately in order to guarantee the system’s reliability. The power flow path identification is considered as a difficult task especially in a huge system due to large number of switches. Kruskal’s algorithm is presented in this paper to find the minimum power flow path in a power distribution network. The comparison of performance between presented Kruskal’s algorithm and Binary Particle Swarm Optimization (BPSO) was made in solving a problem regarding network reconfiguration. The proposed load restoration approach is tested on IEEE 33-bus single feeder radial distribution system using MATLAB software. From the results, it is found that the presented Kruskal’s algorithm was able to search for the minimal power flow path that contribute to loss reduction for power restoration after the occurrence of fault.]]>
<![CDATA[Prediction of solar irradiance using grey wolf Optimizer-Least-Square support vector machine ]]>
<![CDATA[Zuhaila Mat Yasin]]>;
<![CDATA[Nur Ashida Salim]]>;
<![CDATA[Nur Fadilah Ab Aziz]]>;
<![CDATA[Hasmaini Mohamad]]>;
<![CDATA[Norfishah Ab Wahab]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Computer Science Vol 17, No 1: January 2020 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijeecs.v17.i1.pp10-17
<![CDATA[Prediction of solar irradiance is important for minimizing energy costs and providing high power quality in a photovoltaic (PV) system. This paper proposes a new technique for prediction of hourly-ahead solar irradiance namely Grey Wolf Optimizer- Least-Square Support Vector Machine (GWO-LSSVM). Least Squares Support Vector Machine (LSSVM) has strong ability to learn a complex nonlinear problems. In GWO-LSSVM, the parameters of LSSVM are optimized using Grey Wolf Optimizer (GWO). GWO algorithm is derived based on the hierarchy of leadership and the grey wolf hunting mechanism in nature. The main step of the grey wolf hunting mechanism are hunting, searching, encircling, and attacking the prey. The model has four input vectors: time, relative humidity, wind speed and ambient temperature. Mean Absolute Performance Error (MAPE) is used to measure the prediction performance. Comparative study also carried out using LSSVM and Particle Swarm Optimizer-Least Square Support Vector Machine (PSO-LSSVM). The results showed that GWO-LSSVM predicts more accurate than other techniques. ]]>
