The assessment and improvement of angle stability condition of the power system using particle swarm optimization (PSO) technique / Nor Azwan Mohamed Kamari

Mohamed Kamari, Nor Azwan (2017) The assessment and improvement of angle stability condition of the power system using particle swarm optimization (PSO) technique / Nor Azwan Mohamed Kamari. In: The Doctoral Research Abstracts. Professorial Lecture, 11 (11). Institute of Graduate Studies, UiTM, Shah Alam.

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Abstract

This thesis presents the assessment and improvement of stability domains for the angle stability condition of the power system using particle swarm optimization (PSO) technique. An efficient optimization method using PSO for synchronizing torque coefficients Ks and damping torque coefficients Kd to solve angle stability problems was developed and used to identify the angle stability condition on single and multi machine system. In order to accelerate the determination of angle stability, particle swarm optimization (PSO) is proposed to be implemented in this study. The application of the proposed algorithm has been justified as the most accurate with lower computation time as compared to other optimization techniques such as evolutionary programming (EP) and artificial immune system (AIS). Subsequently, a newly control technique named as proportional-integral-derivative (PID) incorporated with flexible AC transmission (FACTS) device is proposed in this study to improve the damping capability of the system. The minimum damping ratio ξmin was applied as an indicator to precisely determine the angle stability condition based on PSO technique. The proposed optimization technique was compared with respect to EP and AIS…

Item Type: Book Section
Creators:
CreatorsEmail
Mohamed Kamari, Nor AzwanUNSPECIFIED
Subjects: L Education > LB Theory and practice of education > Higher Education > Dissertations, Academic. Preparation of theses > Malaysia
Divisions: Institut Pengajian Siswazah (IPSis) : Institute of Graduate Studies (IGS)
Series Name: Professorial Lecture
Volume: 11
Number: 11
Item ID: 19791
Uncontrolled Keywords: Abstract; Abstract of thesis; Newsletter; Research information; Doctoral graduates; IPSis; IGS; UiTM;
Last Modified: 08 Jun 2018 00:51
Depositing User: Staf Pendigitalan 5
URI: http://ir.uitm.edu.my/id/eprint/19791

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