Abstract
Bend-twist coupling of wind turbine blades reduces the structural loads of the turbine but it also results in a decrease of the annual energy production. The main part of the power loss can be mitigated by pretwisting the blade, but some power loss remains and previous studies indicate that it might be related to the dynamic response of bend-twist coupled blades in turbulent flow. This paper contains estimations of the power curve from nonlinear time simulations, a linear frequency domain based method and a normal distribution weighted average method. It is shown that the frequency domain based estimation is highly dependant on the validity of the linearized model, thus estimations are poor for operational points close to rated wind speed. The weighted average method gives good results if an appropriate standard
deviation is known a priori. The nonlinear time simulations show that changes in power due to turbulence are similar for coupled and uncoupled blades. Power gains at low wind speeds are related to the curvature of the steady state power curve. Losses around rated wind speed are caused by the effects of controller switching between partial and full power operation.
deviation is known a priori. The nonlinear time simulations show that changes in power due to turbulence are similar for coupled and uncoupled blades. Power gains at low wind speeds are related to the curvature of the steady state power curve. Losses around rated wind speed are caused by the effects of controller switching between partial and full power operation.
Original language | English |
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Article number | 042018 |
Book series | Journal of Physics: Conference Series (Online) |
Volume | 753 |
Number of pages | 10 |
ISSN | 1742-6596 |
DOIs | |
Publication status | Published - 2016 |
Event | The Science of Making Torque from Wind 2016 - Technische Universität München (TUM), Munich, Germany Duration: 5 Oct 2016 → 7 Oct 2016 Conference number: 6 https://www.events.tum.de/?sub=29 |
Conference
Conference | The Science of Making Torque from Wind 2016 |
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Number | 6 |
Location | Technische Universität München (TUM) |
Country/Territory | Germany |
City | Munich |
Period | 05/10/2016 → 07/10/2016 |
Internet address |