考虑流动时滞效应的风电场偏航协同控制研究

葛铭纬, 陈迪, 常斯语, 李莉

太阳能学报 ›› 2026, Vol. 47 ›› Issue (6) : 424-429.

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太阳能学报 ›› 2026, Vol. 47 ›› Issue (6) : 424-429. DOI: 10.19912/j.0254-0096.tynxb.2025-0189

考虑流动时滞效应的风电场偏航协同控制研究

  • 葛铭纬1, 陈迪1, 常斯语1,2, 李莉1
作者信息 +

RESEARCH ON COOPERATIVE YAW CONTROL OF WIND FARM CONSIDERING FLOW DELAY EFFECTS

  • Ge Mingwei1, Chen Di1, Chang Siyu1,2, Li Li1
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文章历史 +

摘要

为减少风电场内尾流损失,提升整场发电量,基于偏航控制的整场协同控制已成为当前的研究热点。针对现有研究未能充分考虑来流的动态变化和风电场流动的时滞效应等问题,采用高保真大涡模拟方法对风电场流动进行数值仿真,通过流场和邻近机组功率时空相关性确定机组间流动延迟时间,考虑流场流动延迟时间,提出一种湍流入流条件下的风电机组动态偏航控制策略。模拟结果表明,稳态偏航和最佳的动态偏航控制下,风电机组阵列总发电量比无偏航控制下分别提高11.5%和12.5%。相较于稳态偏航控制,动态偏航控制下风电机组间尾流发展更充分,尾流速度恢复更快。

Abstract

In order to reduce the wake loss in the wind farm and enhance the whole field power generation, the whole field cooperative control based on yaw control has become a current research hotspot. To address issues such as existing studies not fully considering the dynamic changes in incoming flow and the time-lag effects of wind farm flow, a high-fidelity large eddy simulation method is used to numerically simulate the wind farm flow, and the flow delay time between units is determined by the spatial and temporal correlation between the flow field and the power of the neighboring units. Considering the flow delay time of the flow field, a dynamic yaw control strategy is proposed for the wind turbine under the turbulent inflow conditions. The large eddy simulation results show that the total power generation of the wind turbine array under static yaw and optimal dynamic yaw control is increased by 11.5% and 12.5%, respectively, compared with that under no yaw control. Compared to the static yaw control, the wake development between the wind turbine array is more fully developed and the wake velocity recovery is faster under dynamic yaw control.

关键词

风电场 / 大涡模拟 / 尾流 / 偏航控制 / 动态入流 / 流场时空相关性

Key words

wind farm / large eddy simulation / wakes / yaw control / dynamic inflow / flow field spatial-temporal correlation

引用本文

导出引用
葛铭纬, 陈迪, 常斯语, 李莉. 考虑流动时滞效应的风电场偏航协同控制研究[J]. 太阳能学报. 2026, 47(6): 424-429 https://doi.org/10.19912/j.0254-0096.tynxb.2025-0189
Ge Mingwei, Chen Di, Chang Siyu, Li Li. RESEARCH ON COOPERATIVE YAW CONTROL OF WIND FARM CONSIDERING FLOW DELAY EFFECTS[J]. Acta Energiae Solaris Sinica. 2026, 47(6): 424-429 https://doi.org/10.19912/j.0254-0096.tynxb.2025-0189
中图分类号: TK614   

参考文献

[1] SAIDUR R, ISLAM M R, RAHIM N A, et al.A review on global wind energy policy[J]. Renewable and sustainable energy reviews, 2010, 14(7): 1744-1762.
[2] ARCHER C L, VASEL-BE-HAGH A, YAN C, et al. Review and evaluation of wake loss models for wind energy applications[J]. Applied energy, 2018, 226: 1187-1207.
[3] THOMSEN K, MADSEN H A, LARSEN G C, et al.Comparison of methods for load simulation for wind turbines operating in wake[J]. Journal of physics: conference series, 2007, 75(1): 012072.
[4] BOERSMA S, DOEKEMEIJER B, VALI M, et al.A control-oriented dynamic wind farm model: WFSim[J]. Wind energy science, 2018, 3(1): 75-95.
[5] SHAKOOR R, HASSAN M Y, RAHEEM A, et al.Wake effect modeling: a review of wind farm layout optimization using Jensen?s model[J]. Renewable and sustainable energy reviews, 2016, 58: 1048-1059.
[6] 李雄威, 徐家豪, 朱润泽, 等. 基于偏航尾流模型的风电场功率协同优化研究[J]. 太阳能学报, 2022, 43(10): 144-151.
LI X W, XU J H, ZHU R Z, et al.Study on power collaborative optimization of wind farm based on yaw wake model[J]. Acta energiae solaris sinica, 2022, 43(10): 144-151.
[7] 顾波, 胡昊, 刘永前, 等. 考虑尾流效应的风电场优化控制技术研究[J]. 太阳能学报, 2018, 39(2): 359-368.
GU B, HU H, LIU Y Q, et al.Study of wind farm optimal control technology considering wake effect[J]. Acta energiae solaris sinica, 2018, 39(2): 359-368.
[8] ADARAMOLA M S, KROGSTAD P Å.Experimental investigation of wake effects on wind turbine performance[J]. Renewable energy, 2011, 36(8): 2078-2086.
[9] FLEMING P A, GEBRAAD P M O, LEE S, et al. Evaluating techniques for redirecting turbine wakes using SOWFA[J]. Renewable energy, 2014, 70: 211-218.
[10] FLEMING P, GEBRAAD P M O, LEE S, et al. Simulation comparison of wake mitigation control strategies for a two-turbine case: simulation comparison of wake mitigation control strategies for a two-turbine case[J]. Wind energy, 2015, 18(12): 2135-2143.
[11] PARK J, LAW K H.A data-driven, cooperative wind farm control to maximize the total power production[J]. Applied energy, 2016, 165: 151-165.
[12] GEBRAAD P M O, TEEUWISSE F W, VAN WINGERDEN J W, et al. Wind plant power optimization through yaw control using a parametric model for wake effects-a CFD simulation study: wind plant optimization by yaw control using a parametric wake model[J]. Wind energy, 2016, 19(1): 95-114.
[13] MA H L, GE M W, WU G X, et al.Formulas of the optimized yaw angles for cooperative control of wind farms with aligned turbines to maximize the power production[J]. Applied energy, 2021, 303: 117691.
[14] BUSINGER J A, WYNGAARD J C, IZUMI Y, et al.Flux-profile relationships in the atmospheric surface layer[J]. Journal of the atmospheric sciences, 1971, 28(2): 181-189.
[15] SHAPIRO C R, GAYME D F, MENEVEAU C.Modelling yawed wind turbine wakes: a lifting line approach[J]. Journal of fluid mechanics, 2018, 841: R1.

基金

国家重点研发计划(2023YFB4203200)

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