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contributor authorPuneet Agarwal
contributor authorLance Manuel
date accessioned2017-05-09T00:30:09Z
date available2017-05-09T00:30:09Z
date copyrightFebruary, 2008
date issued2008
identifier issn0892-7219
identifier otherJMOEEX-28325#011006_1.pdf
identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/139146
description abstractIn the design of land-based or offshore wind turbines for ultimate limit states, long-term loads associated with return periods on the order of the service life (20years, usually) must be estimated. This requires statistical extrapolation from turbine load data that may be obtained by simulation or by field tests. The present study illustrates such extrapolation that uses field data from the Blyth offshore wind farm in the United Kingdom, where a 2MW wind turbine was instrumented, and environment and load data were recorded. From this measurement campaign, the load data available are in two different formats: as 10min statistics (referred to as “summary” data) or as full time series (referred to as “campaign” data). The characteristics of the site and environment and, hence, that of the turbine response are strikingly different for winds from the sea and winds from the shore. The load data (here, only the mudline bending moment is studied) at the Blyth site are hence separated depending on wind regime. By integrating load distributions conditional on the environment with the relative likelihood of the different environmental conditions, long-term loads associated with specified return periods can be derived. This is achieved here using the peak-over-threshold method based on campaign data but long-term loads are compared with similar estimates based on the summary data. Winds from the shore are seen to govern the long-term loads at the site. Though the influence of wave heights on turbine long-term loads is smaller than that of wind speed, there is possible resonance of tower dynamics induced by the waves; still, to first order, it is largely the wind speed and turbulence intensity that control design loads. Predicted design loads based on the campaign data are close to those based on the summary data discussed in a separate study.
publisherThe American Society of Mechanical Engineers (ASME)
titleEmpirical Wind Turbine Load Distributions Using Field Data
typeJournal Paper
journal volume130
journal issue1
journal titleJournal of Offshore Mechanics and Arctic Engineering
identifier doi10.1115/1.2827937
journal fristpage11006
identifier eissn1528-896X
keywordsWind velocity
keywordsStress
keywordsWaves
keywordsTurbines
keywordsTime series
keywordsWind turbines
keywordsSeas
keywordsDesign
keywordsTurbulence AND Wind
treeJournal of Offshore Mechanics and Arctic Engineering:;2008:;volume( 130 ):;issue: 001
contenttypeFulltext


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