This paper presents a novel wind turbine blade with an actively adaptable twist angle. A weighted-least square technique is proposed to design and control the blade in its application. Controlling the twist distribution provides new capabilities that may not be achievable with blade pitch or rotor torque control. An adaptive twist angle can reduce fatigue loads and improve the efficiency of wind energy conversion. Our previous work established the theoretical blade twist distribution that maximizes wind capture during partial load operation. The twist distribution changes continuously as a function of wind speed. In practice, it is a challenge to design and control the blade to adapt to this range of transformation. Accordingly, a blade concept and engineering design method are proposed to achieve this task. The blade is constructed from additively manufactured sections that are assumed to have tunable stiffness. The sections are mounted on a centralized spar that provides stiffness. The sections are actuated at each end and have two zones of stiffness. A mathematical framework prescribes (1) length of each blade section and (2) the relative stiffness between a pair of compliant shells. Establishing the section length effectively sets the points of actuation, while the relative stiffness establishes a nonlinear twist. These design selections determine the twist distribution. The method employing weighted-least squares is employed to optimize these selections. The approach biases the shape design and control towards the theoretical twist distribution at a range of designated wind speed. This enables a customized solution that maximizes the wind capture based on the wind conditions at a given installation site.
- Dynamic Systems and Control Division
Weighted-Least Squares Optimization Method for Control and Shape Design of an Adaptive Blade Twist Distribution to Increase Wind Capture
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Mou, F, Nejadkhaki, HK, Estes, A, & Hall, J. "Weighted-Least Squares Optimization Method for Control and Shape Design of an Adaptive Blade Twist Distribution to Increase Wind Capture." Proceedings of the ASME 2018 Dynamic Systems and Control Conference. Volume 2: Control and Optimization of Connected and Automated Ground Vehicles; Dynamic Systems and Control Education; Dynamics and Control of Renewable Energy Systems; Energy Harvesting; Energy Systems; Estimation and Identification; Intelligent Transportation and Vehicles; Manufacturing; Mechatronics; Modeling and Control of IC Engines and Aftertreatment Systems; Modeling and Control of IC Engines and Powertrain Systems; Modeling and Management of Power Systems. Atlanta, Georgia, USA. September 30–October 3, 2018. V002T17A005. ASME. https://doi.org/10.1115/DSCC2018-9233
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