Design and implementation of partial offline fuzzy model-predictive pitch controller for large-scale wind-turbines. (January 2020)

• Record Type: Journal Article
• Authors: Abdelbaky, Mohamed Abdelkarim; Liu, Xiangjie; Jiang, Di
• Is Part Of: Renewable energy. Volume 145(2020)
• Page Start: 981
• Page End: 996
• Publication Date: 2020-01
• Subjects: Variable speed/pitch wind-turbine -- Pitch control -- Fuzzy model-predictive control -- Linear matrix inequalities -- Partial offline quasi-min-max; Renewable energy sources -- Periodicals; Power resources -- Periodicals; Énergies renouvelables -- Périodiques; Ressources énergétiques -- Périodiques; 333.794
• DOI: 10.1016/j.renene.2019.05.074
• Languages: English
• ISSNs: 0960-1481

Abstract

Abstract: In the variable rotor speed and variable blade pitch wind-turbines system, the pitch controller is crucial in the high wind speed range to adjust the generator speed so as to produce the rated power. The main challenges in designing the pitch controller are the wind turbine's nonlinearities, constraints on pitch-angle, the variations in wind-speed, and the unstructured model dynamics. From this perspective, a new pitch controller is proposed by employing partial offline quasi-min-max fuzzy model-predictive control to investigate the variable-speed wind turbine performance. Based on the fuzzy modeling, the online optimization problem is simplified as a partial offline optimization problem (offline design and online synthesis). The key advantage of this controller is the guaranteed stability with actuator constraints using LMI constraints and less computational burden. Also, this controller is compared with standard gain scheduled-PI (proportional integral) controller, which has been utilized profusely in the wind-turbine industry. Furthermore, a typical 5 MW benchmark wind-turbine is employed to validate the results from the nonlinear mathematical model. Several case studies are made to prove the proposed controller effectiveness. The results show the superiority of the proposed controller over the gain scheduled-PI controller and two other advanced control techniques. Highlights: The quasi-min-max fuzzy model predictive control (FMPC) strategy has been improved. Fuzzy modeling is involved with MPC design to cope with wind-turbine nonlinearity. The wind-turbine system stability has been guaranteed using the quasi-min-max FMPC. The partial offline strategy has been utilized to alleviate the computation burden. A typical 5 MW wind turbine is used to test the partial offline quasi-min-max FMPC.