袁飞, 夏德喜, 汪正军. 基于SCADA数据的风电机组群尾流效应计算与验证研究[J]. 智慧电力, 2023, 51(7): 23-30.
引用本文: 袁飞, 夏德喜, 汪正军. 基于SCADA数据的风电机组群尾流效应计算与验证研究[J]. 智慧电力, 2023, 51(7): 23-30.
YUAN Fei, XIA De-xi, WANG Zheng-jun. Calculation and Verification of Wake Effect on Wind Turbine Based on SCADA Data[J]. Smart Power, 2023, 51(7): 23-30.
Citation: YUAN Fei, XIA De-xi, WANG Zheng-jun. Calculation and Verification of Wake Effect on Wind Turbine Based on SCADA Data[J]. Smart Power, 2023, 51(7): 23-30.

基于SCADA数据的风电机组群尾流效应计算与验证研究

Calculation and Verification of Wake Effect on Wind Turbine Based on SCADA Data

  • 摘要: 准确评估风电机组尾流导致的发电量损失是风电场设计的重要环节。基于高斯尾流模型,根据动量守恒,引入有效风速衰减计算叶轮面内风速衰减,利用国内某海上风电场SCADA数据,从径向和轴向尾流损失分布两方面进行验证和分析。结果表明,高斯有效风速衰减尾流模型模拟的尾流分布更符合实测尾流损失规律,径向和轴向模拟结果与实测结果相关性超过0.92,有效风速衰减法的精度比叶轮中心风速衰减法提升30%~40%;与Jensen和Frandsen模型相比,高斯有效风速衰减尾流模型的表现更为稳定,有效风速衰减法提高了高斯模型计算精度,更适用于风电场产能评估。

     

    Abstract: Accurate evaluation of the generation loss caused by wind turbine wake is an important part of wind farm design. Based on Gaussian wake model and momentum conservation,the effective wind speed deficit is introduced to calculate wind speed deficit in the impeller of wind turbine. Using the SCADA data of an offshore wind farm in China,the verification and analysis are carried out from radial and axial wake loss distribution. The results show that the wake distribution simulated by the Gaussian effective wind speed deficit method is more consistent with the measured wake loss law. The correlation coefficient between the radial and axial wake simulation results and the measured results exceeds 0.92,and the accuracy of effective wind speed deficit method is improved by 30%~40% compared with the impeller center wind speed deficit method. Compared with the Jensen and Frandsen models,the Gaussian effective wind speed deficit model is more stable. The effective wind speed deficit method improves the calculation accuracy of Gaussian model and makes it more suitable for wind farm power generation.

     

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