Robust aerodynamic design optimization of horizontal axis wind turbine rotors

Caboni, M., Minisci, E. and Campobasso, M. S. (2014) Robust aerodynamic design optimization of horizontal axis wind turbine rotors. In: Greiner, D., Galvan, B., Periaux, J., Gauger, N., Giannakoglou, K. and Winter, G. (eds.) Advances in Evolutionary and Deterministic Methods for Design, Optimization and Control in Engineering and Sciences. Series: Computational methods in applied sciences (36). Springer International Publishing, pp. 225-240. ISBN 9783319115405 (doi: 10.1007/978-3-319-11541-2_14)

Abstract

The work reported in this paper deals with the development of a design system for the robust aerodynamic design optimization of horizontal axis wind turbine rotors. The system developed is here used to design a 126-m diameter, three-bladed rotor, featuring minimal sensitivity to uncertainty associated with blade manufacturing tolerances. In particular, the uncertainty affecting the rotor geometry is associated with the radial distributions of blade chord and twist, and the airfoil thickness. In this study, both geometric and operative design variables are treated as part of the optimization. Airfoil aerodynamics and rotor aeroelasticity are predicted by means of XFOIL and FAST codes, respectively, and a novel deterministic method, the Univariate Reduced Quadrature, is used for uncertainty propagation. The optimization is performed by means of a two-stage multi-objective evolution-based algorithm, aiming to maximize the rotor expected annual energy production and minimize its standard deviation. The design optimization is subjected to a single structural constrain associated with the maximum out-of-plane blade tip deflection. The results of this research highlight that a lower sensitivity to uncertainty tied to manufacturing tolerances can be achieved by lowering the angular speed of the rotor.

• Item Type: Book Sections
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Campobasso, Dr Michele and Minisci, Dr Edmondo
• Authors: Caboni, M., Minisci, E., and Campobasso, M. S.
• College/School: College of Science and Engineering > School of Engineering > Autonomous Systems and Connectivity
• Publisher: Springer International Publishing
• ISBN: 9783319115405

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