Effect of leading-edge erosion on the performance of offshore horizontal axis wind turbine using BEM method

被引:0
|
作者
Mian, H. H. [1 ]
Siddiqui, M. S. [1 ]
Yang, L. [2 ]
Keprate, A. [3 ]
Badar, A. W. [4 ]
机构
[1] Norwegian Univ Life Sci, Dept Mech Engn & Technol Management, N-1432 As, Norway
[2] Cranfield Univ, Div Energy & Sustainabil, Cranfield, Beds, England
[3] Oslo Metropolitan Univ, Dept Mech Elect & Chem Engn, Oslo, Norway
[4] Univ Bahrain, Dept Mech Engn, Zallaq, Bahrain
来源
EERA DEEPWIND CONFERENCE 2023 | 2023年 / 2626卷
关键词
GEOMETRIC APPROXIMATIONS; TURBULENCE;
D O I
10.1088/1742-6596/2626/1/012028
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
This research focuses on the effect of leading-edge erosion on the performance of wind turbines, specifically the GE1.5XLE horizontal axis wind turbine. The blade element momentum (BEM) method is used to predict the performance of the eroded blade configurations, and the open-source code QBLADE is used for simulation. The importance of including the effects of blade erosion in the design phase is highlighted, as it can optimize turbine performance and ensure operational efficiency. The high blade tip velocity in large rotors, which can reach 90-110 m/s, makes them susceptible to sand and rain erosion, which can significantly affect the turbine's performance. The research compares the performance of clean and eroded blade configurations, with different levels of leading-edge erosion as percentages of the chord (0.5%, 1.0%, 1.5%, and 2.0%). The results show that the worst-case scenario of 2.0% leading-edge erosion reduced the lift-to-drag ratio of an airfoil by 65% and reduced the power output by 20%. The low-fidelity analysis methodology presented in this research is fast and can be easily implemented in the early design phase of wind turbines to predict the effect of leading-edge blade erosion. This allows for cost-effective and efficient design solutions that take into account the effects of erosion on wind turbine performance. The research provides valuable insights for the wind energy industry to improve the reliability and performance of wind turbines.
引用
收藏
页数:12
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