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Title:
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Wind Turbine Extreme Gust Control
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Author(s):
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Published by:
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Publication date:
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ECN
Wind Energy
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6-10-2008
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ECN report number:
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Document type:
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ECN-E--08-069
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ECN publication
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Number of pages:
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Full text:
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56
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Download PDF
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Abstract:
This report presents the research activities and achieved results on extreme event recognition(EER) and control (EEC). This work has been performed within the framework of WP3 of the SenterNovem project “Sustainable Control (SusCon). A new approach to operate wind turbines” with project number EOSLT02013.
An extreme wind gust with direction change can lead to large loads on the turbine (causing fatigue) and unnecessary turbine shut-downs by the supervisory system due to rotor overspeed. The proposed EER algorithm is based on a nonlinear observer (extended Kalman filter) that estimates
the oblique wind inflow angle and the blade effective wind speed signals, which are then used by a detection algorithm (CUSUM test) to recognize extreme events. The nonlinear observer requires that blade root bending moments measurements (in-plane and out-of-plane) are available.
Once an extreme event is detected, an EEC algorithm is activated that (i) tries to prevent the rotor speed from exceeding the overspeed limit by fast collective blade pitching, and (ii) reduces 1p blade loads by means of individual pitch control algorithm, designed in an H1 optimal control
setting. The method is demonstrated on a complex nonlinear test turbine model.
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