Wind energy is the most abundant resource in the renewable energy portfolio. Increasing the wind capture capability improves the economic viability of this technology, making it more competitive with traditional fossil-fuel based approaches. Therefore, it is beneficial to explore optimal control strategies that maximize aerodynamic efficiency, thus, the wind energy capture. Accordingly, this paper presents a dynamic programming approach to find the control inputs for the blade pitch angle and speed ratio, that maximizes the power coefficient. The process uses historical wind data to evaluate the performance of various inputs over a simulated time horizon. A dynamic wind turbine model facilitates this process by characterizing the performance of the various possible input scenarios. Each scenario is scored through the programming technique, and the optimal control inputs are identified following simulation. The results are presented to compare the wind energy capture under the proposed algorithm with the traditional feedback control design.
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ASME 2012 5th Annual Dynamic Systems and Control Conference joint with the JSME 2012 11th Motion and Vibration Conference
October 17–19, 2012
Fort Lauderdale, Florida, USA
Conference Sponsors:
- Dynamic Systems and Control Division
ISBN:
978-0-7918-4531-8
PROCEEDINGS PAPER
A Dynamic Optimization Approach for Maximum Aerodynamic Coefficient of a Wind Turbine
Zeyu Yan,
Zeyu Yan
University of Texas at Austin, Austin, TX
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John Hall,
John Hall
University of Texas at Austin, Austin, TX
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Dongmei Chen
Dongmei Chen
University of Texas at Austin, Austin, TX
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Zeyu Yan
University of Texas at Austin, Austin, TX
John Hall
University of Texas at Austin, Austin, TX
Dongmei Chen
University of Texas at Austin, Austin, TX
Paper No:
DSCC2012-MOVIC2012-8565, pp. 9-16; 8 pages
Published Online:
September 17, 2013
Citation
Yan, Z, Hall, J, & Chen, D. "A Dynamic Optimization Approach for Maximum Aerodynamic Coefficient of a Wind Turbine." Proceedings of the ASME 2012 5th Annual Dynamic Systems and Control Conference joint with the JSME 2012 11th Motion and Vibration Conference. Volume 3: Renewable Energy Systems; Robotics; Robust Control; Single Track Vehicle Dynamics and Control; Stochastic Models, Control and Algorithms in Robotics; Structure Dynamics and Smart Structures; Surgical Robotics; Tire and Suspension Systems Modeling; Vehicle Dynamics and Control; Vibration and Energy; Vibration Control. Fort Lauderdale, Florida, USA. October 17–19, 2012. pp. 9-16. ASME. https://doi.org/10.1115/DSCC2012-MOVIC2012-8565
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