NUMERICAL SIMULATION OF OFFSHORE WIND ENERGY RESOURCES BASED ON CFD

Zhao Siyu; Jin Jiayi; Han Pengfei

doi:10.19912/j.0254-0096.tynxb.2024-0426

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Acta Energiae Solaris Sinica ›› 2025, Vol. 46 ›› Issue (7) : 378-385. DOI: 10.19912/j.0254-0096.tynxb.2024-0426

Special Topics of Academic Papers at the 65th Annual Meeting of the China Association for Science and Technology

NUMERICAL SIMULATION OF OFFSHORE WIND ENERGY RESOURCES BASED ON CFD

Zhao Siyu, Jin Jiayi, Han Pengfei

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Abstract

Based on the finite volume method in computational fluid dynamics （CFD）, a wind field model is established considering the effects of terrain, roughness, and other influential factors. The standard k-ε turbulence model and a single linear wake model are combined, and the RANS equations are used to solve the computational domain, resulting in wind resource maps and annual electricity generation of wind turbines. A comprehensive wind resource assessment is conducted in the vicinity of the Shengshan Station in Shanghai as a case study. The results show that the prevailing wind directions in the area are north-south, southeast, and east, with an increasing gradient of velocity in the north-south direction （Y） as the height increases. Wind speeds are higher during winter, indicating significant potential for wind energy development. This study provides a scientific basis and useful reference for wind power planning in similar regions.

Key words

wind power / offshore wind power / computational fluid dynamics / wind energy resource assessment / linear wake loss

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Zhao Siyu, Jin Jiayi, Han Pengfei. NUMERICAL SIMULATION OF OFFSHORE WIND ENERGY RESOURCES BASED ON CFD[J]. Acta Energiae Solaris Sinica. 2025, 46(7): 378-385 https://doi.org/10.19912/j.0254-0096.tynxb.2024-0426

References

[1] DE ASSIS TAVARES L F, SHADMAN M, DE FREITAS ASSAD L P, et al. Assessment of the offshore wind technical potential for the Brazilian Southeast and South regions[J]. Energy, 2020, 196: 117097.
[2] 林玉鑫, 张京业. 海上风电的发展现状与前景展望[J]. 分布式能源, 2023, 8(2): 1-10.
LIN Y X, ZHANG J Y.Development status and prospect of offshore wind power[J]. Distributed energy, 2023, 8(2): 1-10.
[3] MURTHY K S R, RAHI O P. A comprehensive review of wind resource assessment[J]. Renewable and sustainable energy reviews, 2017, 72: 1320-1342.
[4] VEERS P, DYKES K, LANTZ E, et al. Grand challenges in the science of wind energy[J]. Science, 2019, 366(6464): eaau2027.
[5] ARGIN M, YERCI V.Offshore wind power potential of the Black Sea region in Turkey[J]. International journal of green energy, 2017, 14(10): 811-818.
[6] KHAN T, THEPPAYA T, TAWEEKUN J.Wind resource assessment of northern part of Thailand[J]. Ain Shams engineering journal, 2023, 14(7): 102025.
[7] DAYAL K K, CATER J E, KINGAN M J, et al.Wind resource assessment and energy potential of selected locations in Fiji[J]. Renewable energy, 2021, 172: 219-237.
[8] 叶瑶, 袁熹, 王逸奇. 基于WRF模式的四川省凉山州地区风能资源可开发区域研究[J]. 太阳能学报, 2024, 45(2): 158-163.
YE Y, YUAN X, WANG Y Q.Study on developable regions of wind energy resources in Liangshan Prefecture, Sichuan Province based on WRF model[J]. Acta energiae solaris sinica, 2024, 45(2): 158-163.
[9] 朱蓉, 徐红, 龚强, 等. 中国风能开发利用的风环境区划[J]. 太阳能学报, 2023, 44(3): 55-66.
ZHU R, XU H, GONG Q, et al.Wind environmental regionalization for development and utilization of wind energy in China[J]. Acta energiae solaris sinica, 2023, 44(3): 55-66.
[10] 易侃, 张子良, 张皓, 等. 海上风能资源评估数值模拟技术现状及发展趋势[J]. 分布式能源, 2021, 6(1): 1-6.
YI K, ZHANG Z L, ZHANG H, et al.Technical status and development trends of numerical modeling for offshore wind resource assessment[J]. Distributed energy, 2021, 6(1): 1-6.
[11] JU B, JENOG J, KO K.Assessment of wind atlas analysis and application program and computational fluid dynamics estimates for power production on a Jeju Island wind farm[J]. Wind engineering, 2016, 40(1): 59-68.
[12] GOMES DA SILVA A F, REGINA DE ANDRASE C, ZAPAROLI E L. Wind power generation prediction in a complex site by comparing different numerical tools[J]. Journal of wind engineering and industrial aerodynamics, 2021, 216: 104728.
[13] TABAS D, FANG J, PORTE-AGEL F.Wind energy prediction in highly complex terrain by computational fluid dynamics[J]. Energies, 2019, 12(7): 1311.
[14] IEA. World Energy Outlook 2023[R]. Paris: IEA, 2023.