DocumentCode
622227
Title
PSS-LL based power system stability enhancement using IPSO approach
Author
Kamari, N. A. Mohamed ; Musirin, I. ; Othman, M.M. ; Hamid, Z. Abdul
Author_Institution
Univ. Teknol. Mara, Shah Alam, Malaysia
fYear
2013
fDate
3-4 June 2013
Firstpage
658
Lastpage
663
Abstract
This paper introduced a new swarm based optimization technique for tuning Power System Stabilizer (PSS) that attached to a synchronous generator in a single machine infinite bus (SMIB) system. PSS which is installed with Lead-Lag (LL) controller is introduced to elevate the damping capability of the generator in the low frequency mode. For tuning three PSS-LL parameters, a new Particle Swarm Optimization (PSO) technique called Iteration PSO (IPSO) is proposed. In this method, a new iteration best index is implemented into conventional PSO in order to enhance the quality of the solution. Based on eigenvalues and damping ratio results, it is confirmed that the proposed technique is more efficient than conventional PSO in improving the angle stability of the system. Comparison between IPSO, PSO and Evolutionary Programming (EP) optimization techniques showed that the proposed computation approach give better solution and faster computation time.
Keywords
damping; electric current control; iterative methods; machine control; particle swarm optimisation; power system stability; synchronous generators; IPSO Approach; PSS-LL; angle stability; eigenvalues; generator damping capability; iteration PSO; lead-lag controller; low frequency mode; particle swarm optimization technique; power system stability enhancement; power system stabilizer tuning; single machine infinite bus system; swarm based optimization technique; synchronous generator; Damping; Eigenvalues and eigenfunctions; Generators; Linear programming; Optimization; Oscillators; Power system stability; Damping Factor; Damping Ratio; Evolutionary Programming; Iteration Particle Swarm Optimization; Transient Stability;
fLanguage
English
Publisher
ieee
Conference_Titel
Power Engineering and Optimization Conference (PEOCO), 2013 IEEE 7th International
Conference_Location
Langkawi
Print_ISBN
978-1-4673-5072-3
Type
conf
DOI
10.1109/PEOCO.2013.6564629
Filename
6564629
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