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dc.contributor.authorAgbenyo Folly, Komla
dc.contributor.authorFa Mulumba, Tshina
dc.date.accessioned2022-07-07T09:44:41Z
dc.date.available2022-07-07T09:44:41Z
dc.date.issued2022-06-06
dc.identifier.citationADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal, 11 (2022)
dc.identifier.issn2255-2863
dc.identifier.urihttp://hdl.handle.net/10366/150217
dc.description.abstractThe population size of DE plays a significant role in the way the algorithm performs as it influences whether good solutions can be found. Generally, the population size of DE algorithm is a user-defined input that remains fixed during the optimization process. Therefore, inadequate selection of DE population size may seriously hinder the performance of the algorithm. This paper investigates the impact of DE population size on (i) the performance of DE when applied to the optimal tuning of power system stabilizers (PSSs); and (ii) the ability of the tuned PSSs to perform efficiently to damp low-frequency oscillations. The effectiveness of these controllers is evaluated based on frequency domain analysis and validated using time-domain simulations. Simulation results show that a small population size may lead the algorithm to converge prematurely, and thus resulting in a poor controller performance. On the other hand, a large population size requires more computational effort, whilst no noticeable improvement in the performance of the controller is observed.
dc.format.mimetypeapplication/pdf
dc.publisherEdiciones Universidad de Salamanca (España)
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectdamping ratio
dc.subjectdifferential evolution
dc.subjectlow-frequency oscillations
dc.subjectpopulation size
dc.subjectpower system stabilizer
dc.titleA Study on the Impact of DE Population Size on the Performance Power System Stabilizers
dc.typeinfo:eu-repo/semantics/article


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