Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
399071 | International Journal of Electrical Power & Energy Systems | 2009 | 11 Pages |
Abstract
This paper explores a comparative performance study of two new classes of particle swarm optimization techniques, one with velocity update relaxation (VURPSO) and the other based on novel position, velocity updating strategy and craziness (CRPSO). Both VURPSO and CRPSO highly enhance searching ability. Genetic algorithm (GA) is considered for the sake of comparison. Finally, it is revealed that while applying in two power systems applications (PID controlled AVR system, PSS controlled AVR system), VURPSO exhibits better transient performance than CRPSO/GA. For on-line, off-nominal conditions, Takagi Sugeno fuzzy logic is applied to obtain on-line responses for both the system models.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
A. Chatterjee, V. Mukherjee, S.P. Ghoshal,