DocumentCode :
2790569
Title :
Multi-objective power control of a variable speed wind turbine based H on theory
Author :
Liu, Ji-hong ; Xu, Da-ping ; Yang, Xi-yun
Author_Institution :
Dept. of Autom., North China Electr. Power Univ., Beijing
Volume :
4
fYear :
2008
fDate :
12-15 July 2008
Firstpage :
2036
Lastpage :
2041
Abstract :
A power control strategy for a real variable speed wind turbine system is presented in this paper. The Hinfin-based mixed sensitivity method is applied to realize multi-objective control such as the tracking characteristics for the rated power, poles placement and robustness to disturbances. LMI Toolbox in MATLAB is used to optimize the parameters of Hinfincontroller. First in this paper, a physical model of the fundamental drive-system dynamics of a 300 kW horizontal axis variable speed wind turbine (VWT) is derived. By linearizing this physical model, we can get its linearized state-space form. Second, Hinfin-based S/T/R algorithm is introduced in brief. Finally, the Hinfin controller of mixed sensitivity is designed on the basis of VWT model and simulation is made. The Simulation results show the better performance of the proposed control strategy compared with the conventional PI control.
Keywords :
Hinfin control; linear matrix inequalities; linearisation techniques; multivariable control systems; pole assignment; power control; robust control; state-space methods; variable speed gear; wind turbines; Hinfin control; LMI Toolbox; MATLAB; disturbance robustness; fundamental drive-system; horizontal axis variable speed wind turbine; linearized state-space form; mixed sensitivity method; multiobjective power control; parameter optimization; physical model linearization; pole placement; power 300 kW; tracking characteristics; Aerodynamics; Blades; Control systems; Power control; Power system modeling; Robust control; Rotors; Wind energy generation; Wind speed; Wind turbines; H∞-based robust control; LMI; Mixed Sensitivity (S/T/R); Multi-objective control; Power control; Wind turbine; pole placement;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics, 2008 International Conference on
Conference_Location :
Kunming
Print_ISBN :
978-1-4244-2095-7
Electronic_ISBN :
978-1-4244-2096-4
Type :
conf
DOI :
10.1109/ICMLC.2008.4620741
Filename :
4620741
Link To Document :
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