Wind direction error in the Lillgrund offshore wind farm

Xi Yu, David Infield, Eoghan Maguire

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

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Abstract

The reduction of wake effects and maximisation of wind farm power output are always of interest to wind researchers [2][3]. However, one of the research challenges is to distinguish sensor errors from wake losses and losses due to poor yaw alignment. SCADA data from Lillgrund, the Swedish offshore wind farm, shows significant differences between the wind direction as measured at the met mast and as indicated by the nacelle directions measured at the individual wind turbines. Various possibilities might explain this data, the most likely being poor yaw control at particular wind turbines and/or sensor error. Both of these make power performance assessment and wake analysis problematic. In this paper, animations presented have been proved useful in the initial identification of turbines with potential problems. These anomalous turbines are then subject to a range of analyses designed to distinguish the different potential issues
Original languageEnglish
Title of host publication2nd IET Renewable Power Generation Conference (RPG 2013)
Place of PublicationStevenage
Number of pages6
DOIs
Publication statusPublished - 9 Sep 2013
Event2nd IET Renewable Power Generation Conference, IET 2013 - Beijing, China
Duration: 9 Sep 201311 Sep 2013

Conference

Conference2nd IET Renewable Power Generation Conference, IET 2013
CountryChina
CityBeijing
Period9/09/1311/09/13

Keywords

  • SCADA systems
  • offshore installations
  • optimisation
  • wind power plants
  • Lillgrund offshore wind farm
  • SCADA data
  • anomalous turbines
  • maximisation
  • performance assessment
  • sensor errors
  • wake effects
  • wake losses
  • wind direction error
  • direction sensor error
  • offshore
  • yawing problem

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  • Cite this

    Yu, X., Infield, D., & Maguire, E. (2013). Wind direction error in the Lillgrund offshore wind farm. In 2nd IET Renewable Power Generation Conference (RPG 2013) [3.32]. https://doi.org/10.1049/cp.2013.1839