Abstract
Power System Stabilizers (PSSs) are used in interconnected power systems in order to mitigate low frequency oscillations. the comparison of the performances of four advanced population-based techniques in tuning the parameters of PSS in a three-machine-nine-bus test system is presented in this paper. the algorithms considered in this paper are A) Differential Evolution based Particle Swarm Optimization (DEPSO), b) Modified Clonal Selection Algorithm (MCSA), c) Small Population based Particle Swarm Optimization (SPPSO) and d) Population based Incremental Learning (PBIL). the comparative study is focused on the frequency domain performances. It is observed that MCSA is performing better than the other three algorithms. the performances of DEPSO and PBIL are quite similar whereas the SPPSO algorithm is not showing very good results compared to the other three. © 2009 IEEE.
Recommended Citation
P. Mitra et al., "Comparative Study of Population based Techniques for Power System Stabilizer Design," 2009 15th International Conference on Intelligent System Applications to Power Systems, ISAP '09, article no. 5352927, Institute of Electrical and Electronics Engineers, Dec 2009.
The definitive version is available at https://doi.org/10.1109/ISAP.2009.5352927
Department(s)
Electrical and Computer Engineering
Keywords and Phrases
Differential evolution based particle swarm optimization; Modified clonal selection algorithm; Population based incremental learning; Small population based particle swarm optimization; Small signal stability
International Standard Book Number (ISBN)
978-142445098-5
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2024 Institute of Electrical and Electronics Engineers, All rights reserved.
Publication Date
09 Dec 2009
