Article | 13th Scandinavian International Conference on Fluid Power; June 3-5; 2013; Linköping; Sweden | Model Predictive Control for Power Optimization in a Hydrostatic Wind Turbine Link�ping University Electronic Press Conference Proceedings
Göm menyn

Title:
Model Predictive Control for Power Optimization in a Hydrostatic Wind Turbine
Author:
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
DOI:
10.3384/ecp1392a16
Year:
2013
Conference:
13th Scandinavian International Conference on Fluid Power; June 3-5; 2013; Linköping; Sweden
Issue:
092
Article no.:
016
Pages:
155-160
No. of pages:
6
Publication type:
Abstract and Fulltext
Published:
2013-09-09
ISBN:
978-91-7519-572-8
Series:
ISSN (print):
1650-3686
ISSN (online):
1650-3740
Publisher:

Export in BibTex, RIS or text

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

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

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

Author:
Feng Wang, Kim A. Stelson
Title:
Model Predictive Control for Power Optimization in a Hydrostatic Wind Turbine
References:

[1] Thul; B.; Dutta; R.; Stelson; K. A.; Hydrostatic transmission for mid-sized wind turbines. 52nd National Conference on Fluid Power; Las Vegas; USA; 2011.

[2] Johnson; K. E. ; Pao; L. Y. ; Balas; M. J.; Fingersh; L. J.; Control of variable-speed wind turbines: standard and adaptive techniques for maximizing energy capture. IEEE Control Systems Magazine; vol.26; no.3; pp.70–81; 2006.

[3] Pao; L. Y.; Johnson; K. E.; A tutorial on the dynamics and control of wind turbines and wind farms. Amer ican Cont rol Conference ; pp. 2076-2089; St. Louis; Missouri; USA; 2009.

[4] Wang; F.; Trietch; B.; Stelson; K. A.; Mid-sized wind turbine with hydro-mechanical transmission demonstrates improved energy production. The 8th Internat ional Conference on Fluid Power Transmission and Control (ICFP 2013); Hangzhou; China; 2013.

[5] Henriksen; L. C.; Model predict ive control of a wind turbine; master thesis; Technical University of Denmark; 2007.

[6] Soltani; M.; Wisniewski; R.; Brath; P. and Boyd; S.; Load reduction of wind turbines using receding hor izon cont rol ; Proceedings IEEE Multi - Conference Systems and Control; pp. 852–857; 2011.

[7] Zhongzhou; Y.; Yaoyu; L.; and Seem; J. E.; Model predictive control for wind turbine load reduction under wake meandering of upstream wind turbines; American Control Conference; 2012.

[8] Mostafa; S.; Malik; O. P.; and Westwick; D. T.; Multiple model predictive control for wind turbines with doubly fed induction generators. IEEE Transactions on Sustainable Energy; vol.2; no.3; 2011.

[9] Khalid; M.; Savkin; A.V.; A model predictive control approach to the problem of wind power smoothing with controlled battery storage; Renewable Energy; vol.35; pp.1520-1526; 2010.

[10] Dutta; R.; Wang; F.; Bohlmann; B.; Stelson; K. A.; Analysis of short-term energy storage for mid-size hydrostatic wind turbine. ASME Dynamic Systems and Control Conference; Fort Lauderdale; FL; USA; 2012.

[11] NWTC design codes (FAST by Jason Jonkman). http://wind.nrel.gov/designcodes/simulators/fast/

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

Author:
Feng Wang, Kim A. Stelson
Title:
Model Predictive Control for Power Optimization in a Hydrostatic Wind Turbine
Note: the following are taken directly from CrossRef
Citations:
No citations available at the moment