Nur Fadilah Ab Aziz
Universiti Tenaga Nasional

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Investigation of distributed generation units placement and sizing based on voltage stability condition indicator (VSCI) Arvind Raj; Nur Fadilah Ab Aziz; Zuhaila Mat Yasin; Nur Ashida Salim
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 | Full PDF (329.747 KB) | DOI: 10.11591/ijpeds.v10.i3.pp1317-1323

Abstract

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.
Multi-machine transient stability by using static synchronous series compensator Nur Ashida Salim; Nur Diyana Shahirah Mohd Zain; Hasmaini Mohamad; Zuhaila Mat Yasin; Nur Fadilah Ab Aziz
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 11, No 3: September 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (908.605 KB) | DOI: 10.11591/ijpeds.v11.i3.pp1249-1258

Abstract

Transient stability in power system is vital to be addressed due to large disturbances that could damage the system such as load changes and voltage increases. This paper presents a multi-machine transient stability using the Static Synchronous Series Compensator (SSSC). SSSC is a device that is connected in series with the power transmission line and produces controllable voltage which contribute to a better performance in the power system stability. As a result, this research has observed a comparison of the synchronization of a three-phase system during single-phase faults before and after installing the SSSC device. In addition, this research investigates the ability of three different types of controllers i.e. Proportional Integral (PI), Proportional Integral Derivation (PID), and Generic controllers to be added to the SSSC improve the transient stability as it cannot operate by itself. This is because the improvement is too small and not able to achieve the desired output. The task presented is to improve the synchronization of the system and time taken for the voltage to stabilize due to the fault. The simulation result shows that the SSSC with an additional controller can improve the stability of a multi-machine power system in a single phase fault.
Graphical user interface based model for transmission line performance implementation in power system Nur Ashida Salim; Hasmaini Mohamad; Zuhaila Mat Yasin; Nur Fadilah Ab Aziz; Nur Azzammudin Rahmat
Indonesian Journal of Electrical Engineering and Computer Science Vol 16, No 1: October 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v16.i1.pp92-100

Abstract

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.
Prediction of solar irradiance using grey wolf Optimizer-Least-Square support vector machine Zuhaila Mat Yasin; Nur Ashida Salim; Nur Fadilah Ab Aziz; Hasmaini Mohamad; Norfishah Ab Wahab
Indonesian Journal of Electrical Engineering and Computer Science Vol 17, No 1: January 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v17.i1.pp10-17

Abstract

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. 
Implementation of graphical user interface to observe and examine the frequency and rotor angle stability of a power system due to small disturbances Nur Ashida Salim; Mohamad Salehan Ab. Samah; Hasmaini Mohamad; Zuhaila Mat Yasin; Nur Fadilah Ab Aziz
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.pp606-614

Abstract

The aim of this research is to anticipate the stability status of a power system when the system is exposed to a change in frequency and rotor angle due to small disturbances. The proposed study was implemented on the IEEE Reliability Test System 1979 (IEEE RTS-79) which contains 24 buses, 38 transmission lines and 32 generators. Steady state stability limit of a system refers to the maximum amount of power that is permissible through the system without loss of its steady state stability. This research proposes the development of a Graphical User Interface (GUI) to observe the frequency and rotor angle stability due to the effect of small disturbances using the One Machine Infinite Bus (OMIB) technique. This proposed technique could ease the power system utility especially the power system operation to observe and examine the system frequency and rotor angle stability due to small disturbances. The findings from this research has proven that the proposed technique to observe the frequency and rotor angle stability due to small disturbances has successfully been developed using a GUI.
Fault classification in smart distribution network using support vector machine Ong Wei Chuan; Nur Fadilah Ab Aziz; Zuhaila Mat Yasin; Nur Ashida Salim; Norfishah A. Wahab
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i3.pp1148-1155

Abstract

Machine learning application have been widely used in various sector as part of reducing work load and creating an automated decision making tool. This has gain the interest of power industries and utilities to apply machine learning as part of the operation. Fault identification and classification based machine learning application in power industries have gain significant accreditation due to its great capability and performance. In this paper, a machine-learning algorithm known as Support Vector Machine (SVM) for fault type classification in distribution system has been developed. Eleven different types of faults are generated with respect to actual network. A wide range of simulation condition in terms of different fault impedance value as well as fault types are considered in training and testing data. Right setting parameters are important to learning results and generalization ability of SVM. Gaussian radial basis function (RBF) kernel function has been used for training of SVM to accomplish the most optimized classifier. Initial finding from simulation result indicates that the proposed method is quick in learning and shows good accuracy values on faults type classification in distribution system. The developed algorithm is tested on IEEE 34 bus and IEEE 123 bus test distribution system.