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A Novel Heating-Coating Hybrid Strategy for Wind Turbine Icing Mitigation
ISSN: 0148-7191, e-ISSN: 2688-3627
Published June 10, 2019 by SAE International in United States
This content contains downloadable datasetsAnnotation ability available
The electro-thermal method is most commonly used for wind turbine anti-/de-icing. The upmost drawback of such systems is the high power consumption. In the present study, we proposed to use a durable slippery liquid-infused porous surface (SLIPS) to effectively reduce the power requirement of the heating element during the anti-/de-icing process. The explorative study was conducted in the Icing Research Tunnel at Iowa State University (ISU-IRT) with a DU91-W2-250 wind turbine blade model exposed under severe icing conditions. During the experiments, while a high-speed imaging system was used to record the dynamic ice accretion process, an infrared (IR) thermal imaging system was also utilized to achieve the simultaneous surface temperature measurements over the test model. In comparison to the traditional electrical heating strategies to brutally heat massive area of entire turbine blades, a novel heating-coating hybrid strategy, i.e., combining a leading-edge (LE) heating element to cover the first 30% of the chord length (C) along with using SLIPS to coat entire blade surface, was found to be able to keep the entire blade surface completely free of ice, but with only an approximately 30% of the required energy consumption. The readily bouncing of the water droplets upon impinging onto the durable SLIPS and the much lower ice adhesion strength/capillary force over the SLIPS coated surface are believed to be the reasons to lead the better anti-/de-icing performance of the heating-coating hybrid strategy to prevent ice accretion/formation over the surfaces of the wind turbine blades.
CitationGao, L., Ma, L., Liu, Y., and Hu, H., "A Novel Heating-Coating Hybrid Strategy for Wind Turbine Icing Mitigation," SAE Technical Paper 2019-01-2029, 2019, https://doi.org/10.4271/2019-01-2029.
Data Sets - Support Documents
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