Title :
Design of power system stabilizer: a comparison between genetic algorithms (GAs) and population-based incremental learning (PBIL)
Author_Institution :
Dept. of Electr. Eng., Cape Town Univ., Rondebosch
Abstract :
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
Keywords :
control system synthesis; genetic algorithms; power system control; power system stability; controller design; evolutionary algorithm; genetic algorithms; multimachine power system; population-based incremental learning; power system stabilizer design; Algorithm design and analysis; Cities and towns; Genetic algorithms; Genetic mutations; Power system analysis computing; Power system interconnection; Power system modeling; Power system simulation; Power system stability; Power systems; Genetic algorithms; low-frequency oscillations; population-based incremental learning; power system stabilizer;
Conference_Titel :
Power Engineering Society General Meeting, 2006. IEEE
Conference_Location :
Montreal, Que.
Print_ISBN :
1-4244-0493-2
DOI :
10.1109/PES.2006.1709635
