Title :
Multimachine power system stabilizer design based on a simplified version of genetic algorithms combined with learning
Author_Institution :
Dept. of Electr. Eng., Cape Town Univ.
Abstract :
A method of designing power system stabilizer for a multimachine power system using a simplified version of genetic algorithms (GAs) called population-based incremental learning (PBIL) is proposed in this paper. The controller design problem is converted into an optimization problem that is solved via the PBIL algorithm. The resulting controllers ensure robust stability and good performance for both the nominal and off-nominal operating conditions. Simulation results are presented to show the effectiveness of PBIL-PSSs
Keywords :
control system synthesis; genetic algorithms; learning (artificial intelligence); power system control; power system stability; controller design problem; genetic algorithm; low-frequency oscillation; multimachine power system stabilizer design; population-based incremental learning; robust stability; Algorithm design and analysis; Control systems; Genetic algorithms; Power system analysis computing; Power system control; Power system simulation; Power system stability; Power systems; Robust control; Robust stability;
Conference_Titel :
Intelligent Systems Application to Power Systems, 2005. Proceedings of the 13th International Conference on
Conference_Location :
Arlington, VA
Print_ISBN :
1-59975-174-7
DOI :
10.1109/ISAP.2005.1599270
