Wind turbine design optimization under environmental uncertainty

Marco Caboni, M. Sergio Campobasso, Edmondo Minisci

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

Wind turbine design optimization is typically performed considering a given wind distribution. However, turbines so designed often end up being used at sites characterized by different wind distributions, and this results in signi?cant performance penalties. This paper presents a probabilistic integrated multidisciplinary approach to the design optimization of multi-megawatt wind turbines accounting for the stochastic variability of the mean wind speed. The presented technology is applied to the design of a 5 MW rotor to be used at sites of wind power class from 3 to 7, where the mean wind speed at 50 m above the ground ranges from 6.4 to 11.9 m/s. Assuming the mean wind speed to vary stochastically in such range, the rotor design is optimized by minimizing mean and standard deviation of the levelized cost of energy. Airfoil shapes, spanwise distributions of blade chord and twist, internal structural layup and rotor speed are optimized concurrently, subject to structural and aeroelastic constraints. The probabilistically designed turbine achieves a more favourable probabilistic performance than the initial baseline turbine. The presented probabilistic design framework is portable and modular in that any of its analysis modules can be replaced with counterparts of user-selected fidelity.
LanguageEnglish
Article number082601
Number of pages10
JournalJournal of Engineering for Gas Turbines and Power
Volume138
Issue number8
Early online date15 Mar 2016
DOIs
Publication statusPublished - 1 Aug 2016

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Wind turbines
Turbines
Rotors
Airfoils
Wind power
Design optimization
Uncertainty
Costs

Keywords

  • wind energy
  • renewable energy
  • robust design optimisation

Cite this

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Wind turbine design optimization under environmental uncertainty. / Caboni, Marco; Campobasso, M. Sergio; Minisci, Edmondo.

In: Journal of Engineering for Gas Turbines and Power, Vol. 138, No. 8, 082601, 01.08.2016.

Research output: Contribution to journalArticle

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