Title :
Adaptive Frequency Control for Hybrid Wind-Diesel power system using system estimator
Author :
Supriyadi, A. N. Cuk ; Takano, Hirotaka ; Murata, Junichi ; Goda, Tadahiro ; Hashiguchi, Taiki
Author_Institution :
Grad. Sch. of Inf. Sci. & Electr. Eng., Kyushu Univ., Fukuoka, Japan
fDate :
Oct. 30 2012-Nov. 2 2012
Abstract :
This paper presents an adaptive pitch and a battery controller design based on a system estimator. The approach presented in this research uses an online identification system, which updated whenever the estimated model mismatch exceeds predetermined bounds. Based on the redesigned model, an adaptive PID and lead-lag controller will be re-tuned using genetic algorithm (GA). The optimization problems are formulated to increase the damping ratio and place the dominant mode in a D-shape region. The GA is applied to solve the optimization problem and to achieve control parameters. The performance of the proposed adaptive controller has been investigated in a hybrid wind-diesel power system in comparison with conventional controller. Simulation results confirm that damping effect of the proposed adaptive controllers are much better that of the conventional controllers against various operating.
Keywords :
adaptive control; genetic algorithms; hybrid power systems; power system simulation; three-term control; adaptive PID controller; adaptive controller; adaptive frequency control; adaptive pitch; battery controller design; genetic algorithm; hybrid wind-diesel power system; lead-lag controller; online identification system; system estimator; Adaptation models; Adaptive control; Blades; Genetic algorithms; Genetics; Indexes; Lead; Adaptive Control; Frequency Control; Hybrid Wind-Diesel Power System; System Estimator;
Conference_Titel :
Power System Technology (POWERCON), 2012 IEEE International Conference on
Conference_Location :
Auckland
Print_ISBN :
978-1-4673-2868-5
DOI :
10.1109/PowerCon.2012.6401449