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Articles by Aini Hussain
Total Records ( 5 ) for Aini Hussain
  Muhammad Nizam , Azah Mohamed and Aini Hussain
  The research presents a study in evaluating the performance of several voltage stability indices used for dynamic voltage collapse prediction in power systems. A new voltage stability index has been proposed and it is named as the power transfer stability index. The proposed index is then compared with other known voltage stability indices such as the voltage collapse prediction index, the line index and the power margin. To evaluate and compare the effectiveness of these indices in predicting proximity to voltage collapse, simulations are carried out using the WSCC 9 bus test system. Simulation test results show that the proposed power transfer stability index and the voltage collapse prediction index give a better prediction of dynamic voltage collapse compared to the power margin and the line index.
  Kamarul Hawari Ghazali , Mohd. Marzuki Mustafa , Aini Hussain and Saifudin Razali
  This study presents a new and robust technique using Scale Invariant Feature Transform (SIFT) for weed classification in oil palm plantation. The proposed SIFT classification technique was developed to overcome problem in real application of image processing such as varies of lighting densities, resolution and target range which contributed to classification accuracy. In this study, SIFT classification algorithm is used to extract a set of feature vectors to represent the input image. The set of feature vectors then can be used to classify weed. In general, the weeds can be classified as either broad or narrow. Based on this classification, a decision will be made to control the strategy of weed infestation in oil palm plantations. The effectiveness of the robust SIFT technique has been tested offline where the input images were captured under varies conditions such as different lighting effects, ambiguity resolution values, variable range of object and many sizes of weed which simulate the actual field conditions. The proposed SIFT resulted in over 95.7% accuracy of classification of weed in palm oil plantation.
  Ahmed M.A. Haidar , Azah Mohamed and Aini Hussain
  Vulnerability assessment in power systems is to determine a power system`s ability to continue to provide service in case of an unforeseen catastrophic contingency. It combines information on the level of system security as well as information on a wide range of scenarios, events and contingencies. To assess the level of system strength or weakness relative to the occurrence of an undesired event, a quantitative measure based on vulnerability index is often considered. In this study, a new vulnerability assessment method is proposed based on total power system loss which considers power generation loss due to generation outage, power line loss due to line outage, increase in total load and amount of load disconnected. The objective of this study is to investigate the effectiveness of the new proposed method in assessing the vulnerability of power system when subject to various contingencies. The performance of the proposed vulnerability assessment method is compared with other known vulnerability assessment methods based on anticipated loss of load as well as comprehensive system information of individual system components. In this study, vulnerability analysis was carried out on the IEEE 24 bus test system using the Power System Analysis and Toolbox (PSAT) and the vulnerability indices were calculated using the Matlab program. Obtained results, indicate the efficiency of proposed method.
  Nooritawati Md Tahir , Aini Hussain , Salina Abdul Samad , Hafizah Husain and Mohd Marzuki Mustafa
  This study outlines a mechanism for human body posture classification based on various combination of eigenspace transform which we named as `eigenposture` using three different classifiers; the Multilayer Perceptron (MLP), Nearest Neighbour (NN) and Probabilistic Neural Network (PNN). We apply principal component transformation to extract the features from human shape silhouettes. A combination of them was used to classify the posture of standing and non standing based on the human shape obtained from segmentation process. Different classifiers are compared to each other with respect to classification performance. Results show that combination of second and fourth eigenpostures outperformed the other eigenpostures combination.
  M.A. Hannan , Azah Mohamed and Aini Hussain
  This study deals with the application of a Solid-state Transfer Switch (SSTS) for protection in the distribution system that has been evaluated through modeling and simulation. The modeling of this SSTS is based on graphic models using the electromagnetic transient simulation program PSCAD/EMTDC. The SSTS for protection in distribution systems has been modeled with the objective of achieving faster interruptions. In the SSTS model, a new control scheme based on Park`s transformation theory and three-phase proportional integral controlled phase locked loop has been proposed. Extensive simulations were carried out to validate the performance of the SSTS to transfer power to the load from a faulted feeder to a healthy one in a short period of time. Simulation results obtained also prove that the SSTS can mitigate voltage sag and protect bus bar voltage from various types of faults. It is observed that the impact of the induction motor load on the performance of the SSTS in which it has a higher time delay to complete the transfer process as compared to the system with static loads. The effectiveness of SSTS was also evaluated under various faults and load conditions and compared with the IEEE benchmark system STS-1 in terms of transfer time.
 
 
 
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