Vertical axis wind turbine operation in icing conditions: A review study

Tahir, Syed Abdur Rahman; Virk, Muhammad Shakeel

doi:10.1177/0309524x211061828

Cited by 3 publications

(2 citation statements)

References 35 publications

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“…VAWT (Vertical axis wind turbine) is more suitable for generating electricity in human living area because of its low noise and easy maintenance [1][2][3]. When the VAWT works, the blade AOA (Angle of attack) changes all the time.…”

Section: Introductionmentioning

confidence: 99%

Study on the Influence of Protuberance Amplitude on the Performance of Vertical Axis Wind Turbines

Chang,

Li,

Wang

et al. 2024

J. Phys.: Conf. Ser.

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The performance of vertical axis wind turbine (VAWT) is mainly affected by the dynamic stall process of the blade. Inspired by the anti-stall performance of the humpback whale flipper, leading edge protuberances (LEPs) are applied to 2-blade VAWT. Based on computational fluid dynamics simulation method, the effects of LEPs amplitude on VAWT performance are investigated when blade tip speed ratio is 2.19. The results show that the larger the amplitude of the LEP, the lower the average power coefficient. When the number of protuberances is 3, the average power coefficient of the VAWT with a protuberance amplitude of 6.625mm is 1.8% higher than prototype blade. Considering the impact of increasing the chord length of biomimetic blades, the average tangential force coefficient of all biomimetic VAWTs decreases. The peak section performance of the bionic blade decreases significantly while the trough section performance increases significantly. The difference between the peak section and trough section of the LEPS plays an important role in improving the performance. This study provides a reference for the application of bionic protuberances in VAWTs.

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Section: Introductionmentioning

confidence: 99%

Study on the Influence of Protuberance Amplitude on the Performance of Vertical Axis Wind Turbines

Chang,

Li,

Wang

et al. 2024

J. Phys.: Conf. Ser.

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“…When icing conditions are met, water droplets in the air, rainfall, drizzle, or wet snow freeze or stick to wind turbine blades, resulting in the formation of ice. Wind turbine ice can shorten the life of components by causing uneven blade mass distribution and higher blade loading [7]. While moderate freezing can have an effect on the aerodynamic qualities of wind turbine blades, significant icing can cause the wind turbine to shut down completely, decreasing the efficiency of wind resource utilization [8].…”

Section: Introductionmentioning

confidence: 99%

A Review of Wind Turbine Icing Prediction Technology

Zhang,

Xu,

Zhao

2023

Wind Turbine Icing - Recent Advances in Icing Characteristics and Protection Technology

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The global wind energy business has grown considerably in recent years. Wind energy has a bright future as a major component of the renewable energy sector. However, one of the major barriers to the growth of wind energy is the freezing of wind turbine blades. The major solution to overcome the aforementioned problem will be to foresee wind turbine ice using existing anti-icing technologies. As a result, improving wind turbine ice prediction technology can assist wind farms in achieving more precise operation scheduling, avoiding needless shutdowns, and increasing power generation efficiency. Traditional wind turbine icing prediction methods have problems such as misjudgment and omission, while machine learning algorithms have higher accuracy and precision. Because of the rapid advancement of deep learning technology, machine learning algorithms have become an important tool for predicting wind turbine icing. However, in real applications, machine learning algorithms still face obstacles and limits such as inadequate data and poor model interpretability, which require additional study and refinement. This chapter discusses the application of machine learning algorithms in wind turbine icing prediction, provides a comprehensive description of the applicability and accuracy of various machine learning algorithms in wind turbine icing prediction, and summarizes the applications and advantages.

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