4.7 Article

In situ estimation of effective liquid water content on a wind turbine using a thermal based sensor

Journal

COLD REGIONS SCIENCE AND TECHNOLOGY
Volume 184, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.coldregions.2021.103235

Keywords

Wind energy; Icing; Liquid water content; Wind turbine; Cold climate

Funding

  1. Engineering Research Council of Canada (NSERC) [RGPIN-2015-04564]
  2. Fonds de recherche du Qu 'ebec -Nature et technologies (FRQNT) [259164]

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This study proposes a method for estimating the effective LWC in wind farms using a thermal-based ice sensor, which was calibrated with data from 8 icing events and showed better sensitivity and accuracy.
To correctly assess the performance of wind turbine ice protection systems (IPS), a complete overview of the meteorological conditions is needed. The same would prove helpful in the usage of the alternative operational control strategies during icing events. A crucial factor to consider is the estimation of the liquid water content (LWC). This parameter has a significant impact on the thermal behavior of IPS and therefore their efficiency. Finding a reliable, robust and accessible method for estimating the LWC on wind farms is a challenge that has yet to be solved. Wind farm operators frequently have to rely on visual observations to guide their decisions. This paper proposes a method for estimating the effective LWC in wind farms using a thermal based ice sensor. This proposed method was calibrated using the equivalent effective LWC obtained from image analysis of ice accretion on a reference cylinder. Over the winter of 2018-2019, on a Canadian site, 8 icing events were retained to provide calibration data. An increase of more than 10 mm of ice frontal thickness was observed during the daylight for all the events. The thermal based ice sensor proved to be coherent with the camera observations while presenting a more robust method with better sensitivity and accuracy. Having a reliable LWC estimation method not only presents an advantage for wind turbine operation but could also potentially help the site assessment process where the numerical weather predictions are not able to capture intra-site variations of the icing severity.

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