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Wind Energy Science The interactive open-access journal of the European Academy of Wind Energy
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https://doi.org/10.5194/wes-2019-87
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wes-2019-87
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 04 Dec 2019

Submitted as: research article | 04 Dec 2019

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Wind Energy Science (WES).

Development of a Second Order Dynamic Stall Model

Niels Adema1, Menno Kloosterman2, and Gerard Schepers1 Niels Adema et al.
  • 1EUREC European Master in Renewable Energy, Hanze University of Applied Sciences, Groningen, 9747 AS, the Netherlands
  • 2DNV GL, Groningen, 9743 AN, the Netherlands

Abstract. Dynamic stall phenomena bring risk for negative damping and instability in wind turbine blades. It is crucial to model these phenomena accurately to reduce inaccuracies in predicting design driving (fatigue) loads. Inaccuracies in current dynamic stall models may be due to the facts that they are not properly designed for high angles of attack, and that they do not specifically describe vortex shedding behaviour. The Snel second order dynamic stall model attempts to explicitly model unsteady vortex shedding. This model could therefore be a valuable addition to DNV GL's turbine design software Bladed. In this thesis the model has been validated with oscillating airfoil experiments and improvements have been proposed for reducing inaccuracies. The proposed changes led to an overall reduction in error between the model and experimental data. Furthermore the vibration frequency prediction improved significantly. The improved model has been implemented in Bladed and tested against small scale turbine experiments at parked conditions. At high angles of attack the model looks promising for reducing mismatches between predicated and measured (fatigue) loading. Leading to possible lower safety factors for design and more cost efficient designs for future wind turbines.

Niels Adema et al.
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Status: open (until 23 Feb 2020)
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