Research on Effect of Icing Degree on Performance of NACA4412
Airfoil Wind Turbine

Jia, Yuhao; Cheng, Bin; Li, Xiyang; Zhang, Hui; Dong, Yinglong

doi:10.32604/ee.2020.012019

Cited by 2 publications

(2 citation statements)

References 13 publications

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“…Highaltitude regions are often selected as ideal sites for wind farms because of their substantial wind energy potential and the high density of cold air [3]. However, these areas are also vulnerable to blade icing, which can reduce power generation, increase component stress, affect the lifespan of turbines [4], and even pose safety hazards due to potential ice detachment from the rotating blades, thus potentially resulting in injuries or fatalities [5]. Currently, several commercial wind turbines utilize the deviations between the actual and theoretical powers of the wind turbine as a criterion to identify blade icing.…”

Section: Introductionmentioning

confidence: 99%

Research on the Icing Diagnosis of Wind Turbine Blades Based on FS–XGBoost–EWMA

Guo,

Song,

Liu

et al. 2024

ENERGY

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In winter, wind turbines are susceptible to blade icing, which results in a series of energy losses and safe operation problems. Therefore, blade icing detection has become a top priority. Conventional methods primarily rely on sensor monitoring, which is expensive and has limited applications. Data-driven blade icing detection methods have become feasible with the development of artificial intelligence. However, the data-driven method is plagued by limited training samples and icing samples; therefore, this paper proposes an icing warning strategy based on the combination of feature selection (FS), eXtreme Gradient Boosting (XGBoost) algorithm, and exponentially weighted moving average (EWMA) analysis. In the training phase, FS is performed using correlation analysis to eliminate redundant features, and the XGBoost algorithm is applied to learn the hidden effective information in supervisory control and data acquisition analysis (SCADA) data to build a normal behavior model. In the online monitoring phase, an EWMA analysis is introduced to monitor the abnormal changes in features. A blade icing warning is issued when the monitored features continuously exceed the control limit, and the ambient temperature is below 0°C. This study uses data from three icing-affected wind turbines and one normally operating wind turbine for validation. The experimental results reveal that the strategy can promptly predict the icing trend among wind turbines and stably monitor the normally operating wind turbines.

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Section: Introductionmentioning

confidence: 99%

Research on the Icing Diagnosis of Wind Turbine Blades Based on FS–XGBoost–EWMA

Guo,

Song,

Liu

et al. 2024

ENERGY

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“…With the rapid development of wind power technology, various problems faced by wind turbines during the operation are also emerging. Among them, the problem of wind turbine blade icing is one of the focuses of current research in the wind power industry [1,2]. For the icing of wind turbine blades, coating is currently one of the most popular solutions.…”

Section: Introductionmentioning

confidence: 99%

Multi-Scale Superhydrophobic Anti-Icing Coating for Wind Turbine Blades

Bao¹,

He²,

Chen³

et al. 2021

Energy Engineering

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As a surface functional material, super-hydrophobic coating has great application potential in wind turbine blade anti-icing, self-cleaning and drag reduction. In this study, ZnO and SiO 2 multi-scale superhydrophobic coatings with mechanical flexibility were prepared by embedding modified ZnO and SiO 2 nanoparticles in PDMS. The prepared coating has a higher static water contact angle (CA is 153°) and a lower rolling angle (SA is 3.3°), showing excellent super-hydrophobicity. Because of its excellent superhydrophobic ability and micro-nano structure, the coating has good anti-icing ability. Under the conditions of −10 C and 60% relative humidity, the coating can delay the freezing time by 1511S, which is 10.7 times slower than the normal freezing time. More importantly, due to the mechanical properties provided by SiO 2 and the synergistic effect of micro-nano particles, the coating has excellent mechanical durability. After 10 wear tests, the contact angle of the coating is still as high as 141°and the rolling angle is 6.8°. This research provides a theoretical reference for the preparation of a mechanically stable coating with a simple preparation process, as well as a basic research on the anti-icing behavior of the coating.

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Research on Effect of Icing Degree on Performance of NACA4412 Airfoil Wind Turbine

Cited by 2 publications

References 13 publications

Research on the Icing Diagnosis of Wind Turbine Blades Based on FS–XGBoost–EWMA

Research on the Icing Diagnosis of Wind Turbine Blades Based on FS–XGBoost–EWMA

Multi-Scale Superhydrophobic Anti-Icing Coating for Wind Turbine Blades

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