Model Predictive Control for Power Optimization in a Hydrostatic Wind Turbine

Feng Wang
Center for Compact and Efficiency Fluid Power, Department of Mechanical Engineering, University of Minnesota, Minneapolis, USA

Kim A. Stelson
Center for Compact and Efficiency Fluid Power, Department of Mechanical Engineering, University of Minnesota, Minneapolis, USA

Ladda ner artikelhttp://dx.doi.org/10.3384/ecp1392a16

Ingår i: 13th Scandinavian International Conference on Fluid Power; June 3-5; 2013; Linköping; Sweden

Linköping Electronic Conference Proceedings 92:16, s. 155-160

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Publicerad: 2013-09-09

ISBN: 978-91-7519-572-8

ISSN: 1650-3686 (tryckt), 1650-3740 (online)


Model predictive control (MPC) is applied to a mid-sized hydrostatic (HST) wind turbine for maximizing power capture in this paper. This study focuses on the torque control in region 2; which tracks the desired rotor speed so that the turbine can operate at the optimum tip-speed ratio (TSR) for maximum power. Preliminary study shows that the widely used $K\omega^{2}$ control law has a good control performance in steady-state wind conditions. However due to wind turbulence; the turbine operates at tip-speed ratios far away from the optimal point. This deviation is not only due to the large rotor inertia; but also due to the characteristics of the $K\omega^{2}$ control. An MPC controller is proposed to track the desired rotor speed by using the future prediction of wind speed. To consider the potential advantage; the MPC controller is applied to a 50 kW HST wind turbine. A wind speed step change is selected as a basic test of transient response. The control performance of the MPC is evaluated and compared with the $K\omega^{2}$ control law. Results show that the MPC controller in a smaller wind speed step change shows a faster response than $K\omega^{2}$ control law; but a large overshoot is observed. In a larger wind speed change; the MPC controller loses control when the wind speed steps down. This indicates the MPC controller in this study has limited effective operation range since it uses a linearized plant model and the wind turbine is a highly nonlinear system. Future work includes the optimization of MPC controller parameters to reduce the overshoot during the wind speed change and the design of multiple MPC controllers for wide operation range


Mid-sized wind turbine; hydrostatic transmission; wind turbulence; power optimization; model predictive control


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