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Adaptive maximum power point tracking control for wind turbines with effective wind speed estimation & prediction. (English) Zbl 1438.93112
Summary: With the rapid development of wind power generation technology, maximum power point tracking (MPPT) control of wind turbines is still a challenging problem due to the unavailable effective wind speed. In this paper, an adaptive MPPT controller for wind turbines based on effective wind speed estimation & prediction is presented, without requiring the knowledge of system parameters, rotor or wind acceleration. Firstly, support vector regression (SVR) is utilized to develop the wind speed estimation & prediction models. The wind speed information is delivered to the MPPT controller in a real-time manner. Further, an online learning approximator (OLA) is employed in the controller to cope with the unknown dynamics of the wind turbines. Thus, the proposed OLA-based adaptive controller is parameter-free and can be readily extended to other types. Moreover, decreased torque gain control (DTG) is integrated to mitigate the mechanical loads on the driven train. Meanwhile, all signals in the closed-loop system are proven to be bounded via Lyapunov theory. Finally, the effectiveness of the proposed controller is validated with WP 1.5MW wind turbines on the platform of FAST (fatigue, aerodynamics, structures, and turbulence) code and Simulink.
MSC:
93C40 Adaptive control/observation systems
93E10 Estimation and detection in stochastic control theory
93C95 Application models in control theory
Software:
FAST; Simulink
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