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CUI Donglin, SHA Wei, LIU Shujie, CHEN Qiuyang, WANG Nina. Case Study of "Wake Effect" of Adjacent Offshore Wind Farms[J]. SOUTHERN ENERGY CONSTRUCTION, 2023, 10(1): 21-28. DOI: 10.16516/j.gedi.issn2095-8676.2023.01.003
Citation: CUI Donglin, SHA Wei, LIU Shujie, CHEN Qiuyang, WANG Nina. Case Study of "Wake Effect" of Adjacent Offshore Wind Farms[J]. SOUTHERN ENERGY CONSTRUCTION, 2023, 10(1): 21-28. DOI: 10.16516/j.gedi.issn2095-8676.2023.01.003

Case Study of "Wake Effect" of Adjacent Offshore Wind Farms

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  • Received Date: October 12, 2021
  • Revised Date: December 29, 2021
  • Available Online: November 20, 2022
  •   Introduction  The purpose of this paper is to study the influence of real "wake effect" of adjacent offshore wind farms on generation loss.
      Method  The method is established with the wake scene classification based on the actual arrangement of wind farms under different wind direction and the real wake power loss of adjacent wind farms (with a spacing of more than 20D) in operation are analyzed, based on the actual SCADA data of wind turbines in large offshore wind farms and the measured wind data of LIDAR in the same period.
      Result  The results show that: for the large-scale offshore wind farms with regular arrangement, the power generation normalization of the actual SCADA data can better reflect the distribution characteristics of offshore wind energy resources and the difference of power generation capacity; Under the condition of highly centralized wind direction, the adjacent wind farms in the downwind are obviously affected by the "wake effect" of the upwind wind farm; The buffer zones with different distances of adjacent wind farms have an obvious effect on the recovery of wind speed which affected the power generating capacity. The power generating capacity can be improved but if the buffer zone can reach enough distance; In different scenes of this case, the buffer zone distance is between 23D and 44D, and the power loss of wake decreases by 27%~4%.
      Conclusion  This work can provide guidance for the planning of offshore wind power base and the optimization design of large offshore wind frams.
  • [1]
    ASTARIZ S, IGLESIAS G. Enhancing wave energy competitiveness through co-located wind and wave energy farms. a review on the shadow effect [J]. Energies, 2015(8): 7344-7366. DOI: 10.3390/en8077344.
    [2]
    HASAGER C B, VINCENT P, BADGER J, et al. Using satellite SAR to characterize the wind flow around offshore wind farms [J]. Energies, 2015(8): 5413-5439. DOI: 10.3390/en8065413.
    [3]
    FRANDSEN S, BARTHELMIE R, PRYOR S, et al. Analytical modelling of wind speed deficit in large offshore: wind farms [J]. Wind Energy, 2006, 9(1): 39-53. DOI: 10.1002/we.189.
    [4]
    陈树勇, 戴慧珠, 白晓民, 等. 尾流效应对风电场输出功率的影响 [J]. 中国电力, 1998, 31(11): 28-31.

    CHEN S Y, DAI H Z, BAI X M, et al. Impact of wind turbine wake on wind power output [J]. Electric Power, 1998, 31(11): 28-31.
    [5]
    刘沙, 王中权, 蔡彦枫. 海上风电场运行期尾流损失分析 [J]. 南方能源建设, 2019, 6(1): 66-70. DOI: 10.16516/j.gedi.issn2095-8676.2019.01.011.

    LIU S, WANG Z Q, CAI Y F. Wake loss analysis of offshore wind farm in operation [J]. Southern Energy Construction, 2019, 6(1): 66-70. DOI: 10.16516/j.gedi.issn2095-8676.2019.01.011.
    [6]
    温建民, 张新旺, 陈锋, 等. 基于风电场实测的风机尾流特征分析 [J]. 机械工程与自动化, 2021(1): 3-6. DOI: 10.3969/j.issn.1672-6413.2021.01.002.

    WEN J M, ZHANG X W, CHEN F, et al. Analysis of wind turbine wake characteristics based on wind farm field measurement [J]. Mechanical Engineering & Automation, 2021(1): 3-6. DOI: 10.3969/j.issn.1672-6413.2021.01.002.
    [7]
    李岩, 吴迪, 洪畅, 等. 大型海上风电场风机排布优化策略研究 [J]. 太阳能, 2020(2): 67-74. DOI: 10.3969/j.issn.1003-0417.2020.02.011.

    LI Y, WU D, HONG C, et al. Optimization of wind turbine layout in large-scale offshore wind farm [J]. Solar Enengy, 2020(2): 67-74. DOI: 10.3969/j.issn.1003-0417.2020.02.011.
    [8]
    郑建才, 万德成, 王尼娜, 等. 基于尾流叠加模型的风电场数值模拟 [C]// 《水动力学研究与进展》编委会, 中国力学学会流体力学专业委员会水动力学专业组, 集美大学, 等. 第三十一届全国水动力学研讨会, 中国福建厦门, 2020-10-30. 北京: 海洋出版社, 2020: 833-847. DOI: 10.26914/c.cnkihy.2020.037043.

    ZHEN J C, WAN D C, WANG N, et al. Numerical solution of wind farm wake based on wake interaction model [C]// Editorial Board of Research and Progress in Hydrodynamics, Hydrodynamics Professional Group of Hydromechanics Committee of Chinese Society of Mechanics, Jimei University, et al. Thirty-first National Symposium on Hydrodynamics, Xiamen, Fujian, China, 2020-10-30. Beijing: China Ocean Press, 2020: 833-847. DOI: 10.26914/c.cnkihy.2020.037043.
    [9]
    TC88. Wind turbines-part 12-1: power performance measurements of electricity producing wind turbines: IEC 61400-12-1 [S]. Genève: International Electrotechnical Commission, 2005.
    [10]
    杨昆, 姜婷婷, 朱金奎, 等. 大规模风电场实际尾流分析与算法研究 [C]// 中国农机工业协会风力机械分会. 第七届中国风电后市场交流合作大会, 中国江苏无锡, 2020-8-26. 北京: 中国农机工业协会风力机械分会, 2020: 81-86. DOI: 10.26914/c.cnkihy.2020.011484.

    Y K, J T T, ZHU J K, et al. Research on the actual wake of large scale wind farm and algorithms [C]// China Agricultural Machinery Industry Association Wind Machinery Branch. The 7th China Wind Power Aftermarket Exchange and Cooperation Conference, Wuxi, Jiangsu, China, 2020-8-26. Beijing: China Agricultural Machinery Industry Association Wind Machinery Branch, 2020: 81-86. DOI: 10.26914/c.cnkihy.2020.011484.
    [11]
    MITTELMEIER N, et al. An analysis of offshore wind farm SCADA measurements to identify key parameters influencing the magnitude of wake effects [J]. Wind Energy Science, 2017(2): 477-490. DOI: 10.5194/wes-2-477-2017.
    [12]
    许帅, 邓智文, 汪健文, 等. 偏航工况下风电机组尾流模型与风电场尾流叠加研究 [J]. 能源研究与利用, 2015(4): 27-30+49. DOI: 10.16404/j.cnki.issn1001-5523.2018.04.011.

    XU S, DENG Z W, WANG J W, et al. Study on wind turbine wake model and wake superposition under the yaw condition [J]. Energy Research & Utilization, 2015(4): 27-30+49. DOI: 10.16404/j.cnki.issn1001-5523.2018.04.011.
    [13]
    杨志超, 高丙团, 叶飞, 等. 基于尾流效应的风电场最大出力优化控制 [J]. 电力建设, 2017, 38(4): 96-102. DOI: 10.3969/j.issn.1000-7229.2017.04.013.

    YANG Z C, GAO B T, YE F, et al. Maximum output optimal control of wind farm based on wake effect [J]. Electric Power Construction, 2017, 38(4): 96-102. DOI: 10.3969/j.issn.1000-7229.2017.04.013.
    [14]
    MITTELMEIER N, BLODAU T, KÜHN M. Monitoring offshore wind farm power performance with SCADA data and an advanced wake model [J]. Wind Energy Science, 2017, 2(1): 175-187. DOI: 10.5194/wes-2-175-2017,2017.
    [15]
    李岩, 罗辛·费伊, 白雪. 基于运营风机scada数据的风电场尾流损失测量方法: CN106321368B [P]. 2019-02-15.

    LI Y, ROSIN F, BAI X. The method of measuring wake loss in wind farm based on scada data of operating wind turbines: CN106321368B [P]. 2019-02-15.
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