The impacts of atmospheric icing on performance and behavior of a controlled large-scale wind turbine

IF 1.9 4区 工程技术 Q4 ENERGY & FUELS Journal of Renewable and Sustainable Energy Pub Date : 2023-11-01 DOI:10.1063/5.0161724
Mustafa Sahin, T. Farsadi
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Abstract

Icing degrades turbine performance by altering the geometry of blade airfoils, reducing turbine power output, and increasing structural loads. In this study, the impacts of atmospheric icing on the full performance and behavior of a controlled large-scale wind turbine are thoroughly investigated. Using the Mustafa Sahin bladed wind turbine simulation model, the National Renewable Energy Laboratory 5 MW turbine is simulated with and without iced blades. The turbine blades are considered fully covered by light icing at the leading edge, which causes a reduction of up to 9.27% in Cl and an increase of up to 48% in Cd data of blade airfoils. Turbine static performance and behavior are examined at different uniform winds between cut-in and cut-out wind speeds, while the dynamic performance and behavior are estimated under turbulent winds at below (region II) and above (region III) rated regions. Simulation results are presented in terms of various turbine parameters, such as rotor power, thrust, their coefficients, blade pitch angle, rotor speed, etc. Results show that such light icing alters the turbine's aerodynamic characteristics and dynamics, increasing the turbine's cut-in and rated wind speeds, and reducing the thrust and maximum power coefficients by 5.5% and 13.35%, respectively. Under the same uniform winds, due to icing, turbine static performance and behavior are drastically disrupted in below rated region, resulting in reduced rotor speed, turbine efficiency, thrust, and power output by up to 4.77%, 39.7%, 7.63%, and 40%, respectively. In region III, however, thrust increases by up to 15% although the power output, rotor speed, and turbine efficiency do not change considerably. When the dynamic responses are examined under turbulent wind with a mean of 7.9 m/s in region II, mean power and fluctuations reduce by 14.17% and 10.88%, respectively. The mean thrust decreases by 6.86%, while its fluctuations reduce by 11.33%. The mean rotor speed reduces by 3.83%, and its fluctuations decrease by 12.84%. Under turbulent wind with a mean of 15.7 m/s in region III, the mean power and fluctuations decrease by 0.053% and 1.95%, respectively. The mean thrust increases by 11.99% and its fluctuations drop by 0.84%. The mean rotor speed does not change much, but its fluctuations increase by 0.132%. The mean blade pitch angle reduces by 9.39%, while its fluctuations increase by 7.39%.
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大气结冰对受控大型风力涡轮机性能和行为的影响
结冰会改变叶片机翼的几何形状,降低涡轮机的功率输出,增加结构载荷,从而降低涡轮机的性能。本研究深入探讨了大气结冰对受控大型风力涡轮机的全部性能和行为的影响。利用 Mustafa Sahin 叶片风力涡轮机仿真模型,对国家可再生能源实验室 5 兆瓦涡轮机在叶片结冰和不结冰的情况下进行了仿真。涡轮机叶片的前缘被轻微结冰完全覆盖,这导致叶片翼面的 Cl 值降低达 9.27%,Cd 值增加达 48%。在切入风速和切出风速之间的不同匀风条件下,对涡轮机的静态性能和行为进行了检验,而在低于(II 区)和高于(III 区)额定区域的湍流风条件下,对涡轮机的动态性能和行为进行了估算。模拟结果以各种涡轮机参数的形式呈现,如转子功率、推力、其系数、叶片俯仰角、转子速度等。结果表明,这种轻度结冰会改变涡轮机的空气动力特性和动力学特性,提高涡轮机的切入风速和额定风速,并使推力系数和最大功率系数分别降低 5.5% 和 13.35%。在相同的匀风条件下,由于结冰,涡轮机的静态性能和行为在额定以下区域受到严重破坏,导致转子速度、涡轮机效率、推力和功率输出分别降低了 4.77%、39.7%、7.63% 和 40%。然而,在区域 III 中,虽然功率输出、转子速度和涡轮效率变化不大,但推力却增加了 15%。当在区域 II 中平均速度为 7.9 m/s 的湍流风下考察动态响应时,平均功率和波动分别降低了 14.17% 和 10.88%。平均推力降低了 6.86%,波动降低了 11.33%。平均转子速度降低了 3.83%,波动降低了 12.84%。在区域 III 平均风速为 15.7 m/s 的湍流风下,平均功率和波动分别降低了 0.053% 和 1.95%。平均推力增加了 11.99%,波动下降了 0.84%。平均转速变化不大,但波动增加了 0.132%。平均叶片俯仰角减小了 9.39%,波动则增加了 7.39%。
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来源期刊
Journal of Renewable and Sustainable Energy
Journal of Renewable and Sustainable Energy ENERGY & FUELS-ENERGY & FUELS
CiteScore
4.30
自引率
12.00%
发文量
122
审稿时长
4.2 months
期刊介绍: The Journal of Renewable and Sustainable Energy (JRSE) is an interdisciplinary, peer-reviewed journal covering all areas of renewable and sustainable energy relevant to the physical science and engineering communities. The interdisciplinary approach of the publication ensures that the editors draw from researchers worldwide in a diverse range of fields. Topics covered include: Renewable energy economics and policy Renewable energy resource assessment Solar energy: photovoltaics, solar thermal energy, solar energy for fuels Wind energy: wind farms, rotors and blades, on- and offshore wind conditions, aerodynamics, fluid dynamics Bioenergy: biofuels, biomass conversion, artificial photosynthesis Distributed energy generation: rooftop PV, distributed fuel cells, distributed wind, micro-hydrogen power generation Power distribution & systems modeling: power electronics and controls, smart grid Energy efficient buildings: smart windows, PV, wind, power management Energy conversion: flexoelectric, piezoelectric, thermoelectric, other technologies Energy storage: batteries, supercapacitors, hydrogen storage, other fuels Fuel cells: proton exchange membrane cells, solid oxide cells, hybrid fuel cells, other Marine and hydroelectric energy: dams, tides, waves, other Transportation: alternative vehicle technologies, plug-in technologies, other Geothermal energy
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