DocumentCode
2241354
Title
Design and implementation of power system stabilizers based on evolutionary algorithms
Author
Sheetekela, Severus ; Folly, Komla ; Malik, Om P.
Author_Institution
Dept. of Electr. Eng., Univ. of Cape Town, Cape Town, South Africa
fYear
2009
fDate
23-25 Sept. 2009
Firstpage
1
Lastpage
6
Abstract
This paper discusses the design and implementation of power system stabilizers based on newly introduced evolutionary algorithms, namely the population- based incremental learning (PBIL) and the breeder genetic algorithm (BGA) with adaptive mutation. The designed PSSs were implemented on a power system experimental setup and the experimental results are presented in this paper. A conventional power system stabilizer (CPSS) was also designed and implemented for comparison purposes. In total three PSSs were designed and implemented, and their performance compared. It was found that CPSS gives the worst performance and BGA-PSS performs better than the PBIL-PSS for the specific case described in this paper, with the electrical power used as the input to the PSS.
Keywords
evolutionary computation; genetic algorithms; power system stability; breeder genetic algorithm; evolutionary algorithms; population-based incremental learning algorithm; power system stabilizers; Africa; Algorithm design and analysis; Cities and towns; Damping; Evolutionary computation; Frequency; Genetic algorithms; Genetic mutations; Optimal control; Power systems; BGA; PBIL; automatic voltage regulators; genetic algorithm; premature convergence; real — time; stability;
fLanguage
English
Publisher
ieee
Conference_Titel
AFRICON, 2009. AFRICON '09.
Conference_Location
Nairobi
Print_ISBN
978-1-4244-3918-8
Electronic_ISBN
978-1-4244-3919-5
Type
conf
DOI
10.1109/AFRCON.2009.5308124
Filename
5308124
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