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Quantification of power losses due to wind turbine wake interactions through SCADA, meteorological and wind LiDAR data

机译:通过SCADA,气象和风力LiDAR数据量化由于风力涡轮机尾流相互作用而导致的功率损耗

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摘要

Power production of an onshore wind farm is investigated through supervisory control and data acquisition data, while the wind field is monitored through scanning light detection and ranging measurements and meteorological data acquired from a met-tower located in proximity to the turbine array. The power production of each turbine is analysed as functions of the operating region of the power curve, wind direction and atmospheric stability. Five different methods are used to estimate the potential wind power as a function of time, enabling an estimation of power losses connected with wake interactions. The most robust method from a statistical standpoint is that based on the evaluation of a reference wind velocity at hub height and experimental mean power curves calculated for each turbine and different atmospheric stability regimes. The synergistic analysis of these various datasets shows that power losses are significant for wind velocities higher than cut-in wind speed and lower than rated wind speed of the turbines. Furthermore, power losses are larger under stable atmospheric conditions than for convective regimes, which is a consequence of the stability-driven variability in wake evolution. Light detection and ranging measurements confirm that wind turbine wakes recover faster under convective regimes, thus alleviating detrimental effects due to wake interactions. For the wind farm under examination, power loss due to wake shadowing effects is estimated to be about 4% and 2% of the total power production when operating under stable and convective conditions, respectively. However, cases with power losses about 60-80% of the potential power are systematically observed for specific wind turbines and wind directions. Copyright (c) 2017 John Wiley & Sons, Ltd.
机译:通过监督控制和数据采集数据来研究陆上风电场的发电,同时通过扫描光检测和测距测量以及从位于涡轮机阵列附近的塔式气象塔获取的气象数据来监视风场。根据功率曲线的工作区域,风向和大气稳定性来分析每个涡轮机的发电量。可以使用五种不同的方法来估算随时间变化的潜在风力,从而可以估算与尾流相互作用有关的功率损耗。从统计的角度来看,最可靠的方法是基于对轮毂高度处的参考风速的评估以及针对每个涡轮机和不同的大气稳定性制度计算的实验平均功率曲线。对这些各种数据集的协同分析表明,对于高于切入风速和低于涡轮机额定风速的风速,功率损耗是显着的。此外,在稳定的大气条件下的功率损耗比对流形式的功率损耗要大,这是尾流演变中由稳定性驱动的可变性的结果。光检测和测距测量证实,在对流状态下,风力涡轮机的尾流恢复更快,从而减轻了由于尾流相互作用而产生的有害影响。对于正在检查的风电场,当在稳定和对流条件下运行时,由于尾迹遮蔽效应而导致的功率损失估计分别约为总发电量的4%和2%。但是,对于特定的风力涡轮机和风向,系统地观察到功率损失约为潜在功率的60-80%的情况。版权所有(c)2017 John Wiley&Sons,Ltd.

著录项

  • 来源
    《Wind Energy》 |2017年第11期|1823-1839|共17页
  • 作者单位

    Univ Texas Dallas, Dept Mech Engn, Wind Fluids & Expt WindFluX Lab, Richardson, TX 75083 USA;

    Univ Texas Dallas, Dept Mech Engn, Wind Fluids & Expt WindFluX Lab, Richardson, TX 75083 USA;

    Univ Texas Dallas, Dept Mech Engn, Wind Fluids & Expt WindFluX Lab, Richardson, TX 75083 USA;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    wind turbine wakes; wake interaction; power loss; SCADA; met-tower; LiDAR;

    机译:风力发电机尾流;尾流相互作用;功率损耗;SCADA;塔式塔;LiDAR;

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