Modelling turbulence intensity within a large offshore wind farm

Peter Argyle, Simon Watson, Christiane Montavon, Ian Jones, Megan Smith

Research output: Contribution to journalArticleScientificpeer-review

14 Citations (Scopus)
128 Downloads (Pure)

Abstract

The IEC standard 61400-1 edition 3 uses the so-called Frandsen model to assess levels of turbulence intensity (TI) within wind farms, specifically to determine turbine suitability associated with stress and fatigue. Since the Frandsen model was developed, turbines have significantly grown in size and the number of turbines in an individual wind farm has grown in number. It is of interest to test the accuracy of such models, especially when applied to large wind farms offshore. This work presents results from comparing the Frandsen model with measured data from the Greater Gabbard offshore wind farm. Comparisons are also made with a simplified version of the Frandsen model. In general, both models were shown to perform well when predicting values of TI. However, the ambient wind farm turbulence model utilised by the Frandsen model was shown to be less reliable than the use of an individual turbine wake-generated turbulence model, regardless of distance, as demonstrated using a simplified model. The difference between observed mean and 90th percentile (also known as representative TI) values was in general larger than that predicted. It is proposed that this is primarily due to model reliance on variance in the turbulence of the freestream flow rather than actually modelling the variance of the turbulence generated by individual turbines, although this would require further work to confirm this.
Original languageEnglish
Pages (from-to)1329-1343
Number of pages15
JournalWind Energy
Volume21
Issue number12
DOIs
Publication statusPublished - 2018

Keywords

  • Frandsen model
  • Offshore wind farm
  • Turbulence intensity

Fingerprint Dive into the research topics of 'Modelling turbulence intensity within a large offshore wind farm'. Together they form a unique fingerprint.

Cite this