
Design load definition by LEXPOL
Author(s) -
von Collani Elart,
Binder A.,
Sans W.,
Heitmann A.,
AlGhazali K.
Publication year - 2008
Publication title -
wind energy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.743
H-Index - 92
eISSN - 1099-1824
pISSN - 1095-4244
DOI - 10.1002/we.290
Subject(s) - turbine , reliability (semiconductor) , wind power , probability distribution , bin , computer science , wind engineering , uncertainty quantification , wind speed , reliability engineering , engineering , mathematics , statistics , meteorology , power (physics) , algorithm , structural engineering , mechanical engineering , physics , electrical engineering , quantum mechanics
The predicted long‐term loads for wind turbines determine turbine cost and reliability; and therefore, the definition of the maximum loads, which might realistically occur during the turbine's lifetime, are of considerable importance. The difficulty with predicting the extreme loads derives from the involved uncertainties. Uncertainty refers to the wind and materializes in variability in the sense that the wind speed and the load magnitude varying in time, even if the meteorologic conditions do not change. Therefore, the problem is to describe the variability of the loads in a way that allows reliable, and at the same time accurate, predictions of the maximum loads that the turbines have to withstand. The predictions must have a specified reliability, as otherwise the inherent risks would be unknown, and they should be accurate, as otherwise the cost of manufacturing the turbines would become excessive. LEXPOL ® is based on recent results concerning the stochastic handling of uncertainty, resulting in sets of probability distributions for each considered wind bin. These sets of probability distributions cover the unknown true distribution rather than approximate it by a fitted distribution as it is the case in conventional approaches. The coverage refers to uncertainty measured by entropy and some characteristic distributional properties. Thus, the stochastic models allow reliable and – with respect to the available knowledge – most accurate predictions. Based on the models for specified values of the mean wind speed and the turbulence, prediction procedures for the extreme loads are developed in the unconditional case as well as for long periods. Copyright © 2008 John Wiley & Sons, Ltd.