小型风电场风力和尾流特性对风力机负荷影响的敏感性分析

IF 3.6 Q3 GREEN & SUSTAINABLE SCIENCE & TECHNOLOGY
K. Shaler, A. Robertson, J. Jonkman
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引用次数: 2

摘要

摘要风力涡轮机的设计使用一组模拟来确定疲劳和极限载荷,这些模拟通常只关注风力涡轮机的无唤醒运行。这些结构荷载会受到风流入条件的显著影响。当涡轮机位于上游涡轮机的尾流中时,会经历改变的流入条件,这可能会额外影响疲劳和极限载荷。了解不确定性对无尾流和有尾流涡轮机产生的负荷的影响是很重要的。本工作的目的是评估在一个三涡轮风电场中,哪些与风流入和尾迹相关的参数对涡轮机正常运行时的疲劳和极限载荷影响最大。采用基本效应敏感性分析方法对28个风入流和尾流参数进行筛选,找出导致各涡轮疲劳载荷和极限载荷变化最大的参数。本研究使用国家可再生能源实验室(NREL)的5兆瓦基线风力涡轮机,使用OpenFAST进行模拟,并基于国际电工委员会(IEC) Kaimal湍流谱和IEC指数相干模型,使用NREL工具TurbSim综合产生流入。虽然考虑了参数之间的相互作用,但重点是对单个参数的敏感性,以及在有迹和无迹涡轮机之间的敏感性差异。研究结果表明,对于有迹和无迹涡轮,主风向的环境湍流度和切变是影响涡轮疲劳和极限载荷的最敏感参数。所有涡轮机的次要重要参数被确定为偏航失调,流向积分长度,以及IEC相干模型的指数和流向分量。有导流和无导流涡轮的重要三级参数是不同的。第三次效应占尾流涡轮极限载荷重要事件的9.0%,包括转向、IEC相干模型的非流向分量、雷诺应力、风向、空气密度和几个尾流校准参数。对于疲劳载荷,三级效应占重要事件的5.4%,包括垂直湍流标准偏差、横向和垂直风积分长度、IEC相干模型的非流向分量、雷诺兹应力、风向和所有尾流校准参数。这一信息表明,非流向风分量和尾迹参数在下游涡轮的疲劳和极限负荷敏感性中的重要性日益增加。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Sensitivity analysis of the effect of wind and wake characteristics on wind turbine loads in a small wind farm
Abstract. Wind turbines are designed using a set of simulations to determine the fatigue and ultimate loads, which are typically focused solely on unwaked wind turbine operation. These structural loads can be significantly influenced by the wind inflow conditions. Turbines experience altered inflow conditions when placed in the wake of upstream turbines, which can additionally influence the fatigue and ultimate loads. It is important to understand the impact of uncertainty on the resulting loads of both unwaked and waked turbines. The goal of this work is to assess which wind-inflow-related and wake-related parameters have the greatest influence on fatigue and ultimate loads during normal operation for turbines in a three-turbine wind farm. Twenty-eight wind inflow and wake parameters are screened using an elementary effects sensitivity analysis approach to identify the parameters that lead to the largest variation in the fatigue and ultimate loads of each turbine. This study uses the National Renewable Energy Laboratory (NREL) 5 MW baseline wind turbine, simulated with OpenFAST and synthetically generated inflow based on the International Electrotechnical Commission (IEC) Kaimal turbulence spectrum with the IEC exponential coherence model using the NREL tool TurbSim. The focus is on sensitivity to individual parameters, though interactions between parameters are considered, and how sensitivity differs between waked and unwaked turbines. The results of this work show that for both waked and unwaked turbines, ambient turbulence in the primary wind direction and shear are the most sensitive parameters for turbine fatigue and ultimate loads. Secondary parameters of importance for all turbines are identified as yaw misalignment, streamwise integral length, and the exponent and streamwise components of the IEC coherence model. The tertiary parameters of importance differ between waked and unwaked turbines. Tertiary effects account for up to 9.0 % of the significant events for waked turbine ultimate loads and include veer, non-streamwise components of the IEC coherence model, Reynolds stresses, wind direction, air density, and several wake calibration parameters. For fatigue loads, tertiary effects account for up to 5.4 % of the significant events and include vertical turbulence standard deviation, lateral and vertical wind integral lengths, non-streamwise components of the IEC coherence model, Reynolds stresses, wind direction, and all wake calibration parameters. This information shows the increased importance of non-streamwise wind components and wake parameters in the fatigue and ultimate load sensitivity of downstream turbines.
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来源期刊
Wind Energy Science
Wind Energy Science GREEN & SUSTAINABLE SCIENCE & TECHNOLOGY-
CiteScore
6.90
自引率
27.50%
发文量
115
审稿时长
28 weeks
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