Fatigue Load Estimation through a Simple Stochastic Model

Pedro G. Lind, Iván Herráez, Matthias Wächter and Joachim Peinke
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Pedro G. Lind: ForWind—Center for Wind Energy Research, Institute of Physics, Carl von Ossietzky University of Oldenburg, 26111 Oldenburg, Germany
Iván Herráez: ForWind—Center for Wind Energy Research, Institute of Physics, Carl von Ossietzky University of Oldenburg, 26111 Oldenburg, Germany
Matthias Wächter: ForWind—Center for Wind Energy Research, Institute of Physics, Carl von Ossietzky University of Oldenburg, 26111 Oldenburg, Germany
Joachim Peinke: ForWind—Center for Wind Energy Research, Institute of Physics, Carl von Ossietzky University of Oldenburg, 26111 Oldenburg, Germany

Energies, 2014, vol. 7, issue 12, 1-15

Abstract: We propose a procedure to estimate the fatigue loads on wind turbines, based on a recent framework used for reconstructing data series of stochastic properties measured at wind turbines. Through a standard fatigue analysis, we show that it is possible to accurately estimate fatigue loads in any wind turbine within one wind park, using only the load measurements at one single turbine and the set of wind speed measurements. Our framework consists of deriving a stochastic differential equation that describes the evolution of the torque at one wind turbine driven by the wind speed. The stochastic equation is derived directly from the measurements and is afterwards used for predicting the fatigue loads for neighboring turbines. Such a framework could be used to mitigate the financial efforts usually necessary for placing measurement devices in all wind turbines within one wind farm. Finally, we also discuss the limitations and possible improvements of the proposed procedure.

Keywords: fatigue loads; stochastic modeling; Langevin equation (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2014
References: View complete reference list from CitEc
Citations: View citations in EconPapers (9)

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