Design of power system stabilizer: a comparison between genetic algorithms (GAs) and population-based incremental learning (PBIL)

This paper compares a method of designing power system stabilizer for a multimachine power system using a simple evolutionary algorithm called population-based incremental learning (PBIL) and genetic algorithms (GAs). The controller design issue is formulated as an optimization problem that is solve...

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Bibliographische Detailangaben
1. Verfasser:	Folly, K.A.
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Algorithm design and analysis Cities and towns Genetic algorithms Genetic mutations low-frequency oscillations population-based incremental learning Power system analysis computing Power system interconnection Power system modeling Power system simulation Power system stability power system stabilizer Power systems
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Beschreibung
Zusammenfassung:	This paper compares a method of designing power system stabilizer for a multimachine power system using a simple evolutionary algorithm called population-based incremental learning (PBIL) and genetic algorithms (GAs). The controller design issue is formulated as an optimization problem that is solved via PBIL algorithm and GAs. The resulting controllers are tested on both the nominal and off-nominal operating conditions. Simulation results show that PBIL-PSSs perform comparably to GA-PSSs
ISSN:	1932-5517
DOI:	10.1109/PES.2006.1709635