Optimization‐based study of bend–twist coupled rotor blades for passive and integrated passive/active load alleviation

C.L. Bottasso, F. Campagnolo, A. Croce, Carlo Tibaldi

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

This work is concerned with the design of wind turbine blades with bend‐twist‐to‐feather coupling that self‐react to wind fluctuations by reducing the angle of attack, thereby inducing a load mitigation effect. This behavior is obtained here by exploiting the orthotropic properties of composite materials by rotating the fibers away from the pitch axis. The first part of this study investigates the possible configurations for achieving bend‐twist coupling. At first, fully coupled blades are designed by rotating the fibers for the whole blade span, and a best compromise solution is found to limit weight increase by rotations both in the spar caps and in the skin. Next, partially coupled blades are designed where fibers are rotated only on the outboard part of the blade, this way achieving good load mitigation capabilities together with weight savings. All blades are designed with a multilevel constrained optimization procedure, on the basis of combined cross‐sectional, multibody aero‐servo‐elastic and three‐dimensional finite element models. Finally, the best configuration of the passive coupled blade is combined with an active individual pitch controller. The synergistic use of passive and active load mitigation technologies is shown to allow for significant load reductions while limiting the increase in actuator duty cycle, thanks to the opposite effects on this performance metric of the passive and active control solutions. Copyright © 2012 John Wiley & Sons, Ltd.
Original languageEnglish
JournalWind Energy
Volume16
Issue number8
Pages (from-to)1149-1166
ISSN1095-4244
DOIs
Publication statusPublished - 2013
Externally publishedYes

Keywords

  • Wind turbine
  • Blade design
  • Bend–twist coupling
  • Individual pitch control
  • Aero-servo-elasticity
  • Multidisciplinary optimization

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