WRF模式在江苏省沿海风能预报系统中的应用

为研究WRF模式在沿海风能预报系统中的应用能力,以江苏省大丰市某70m高测风塔的2006年观测记录为例,基于4种不同近地面层-边界层参数化方案的组合,运用WRF模式分别模拟了该塔1、4、7、10月的逐小时风速,评估了不同近地面层-边界层参数化方案组合对沿海风电场轮毂高度风速的模拟效果,分析了WRF模式模拟沿海风电场风速的误差特征。结果表明,不同近地面-边界层参数化方案组合的总体模拟效果不同,MM5similarity近地面层和YSU边界层参数化方案组合的方案A效果稍好;4种参数化方案组合对秋、冬季节的风电场风速模拟精度都要明显好于春、夏季节,存在明显的季节性;WRF模式对海向风的模拟好于陆向风,且其模拟误差存在明显的方向性,沿海地区特殊的地形分布对其有显著的影响。     

变桨距风力发电机额定风速的确定方法

根据风速的Weibull分布特性和变桨距风力发电机的发电特性,构建不同额定风速下风力发电机年发电量计算方法.应用美国可再生能源实验室(NREL)对风力发电成本的研究成果,建立了变桨距风力发电机发电的度电成本数学模型,提出了以度电成本最低为目标的额定风速确定方法,为变桨距风力发电机的额定风速最优选择提供了计算依据.     

Wind environment at a roof-mounted wind turbine on a peaked roof building

Knowledge of the wind resource above peaked roofs is necessary to determine whether installing small wind turbines on low-rise peaked roof buildings is feasible. The wind characteristics at a representative peaked roof barn in southern Ontario, Canada were investigated using a boundary layer wind tunnel and computational fluid dynamics. Field measurements at the barn were collected using sonic anemometers and compared with the simulation results. Wind speed amplification was confined to a region immediately above the roof and was relatively low for wind energy purposes. The presence of nearby trees or buildings adversely impacted wind speed amplification. Considering only wind-related factors, the placing of micro-wind turbines on roof peaks may be warranted. However, if sufficient space is available, it is recommended to place small turbines on a tower rather than on the peaked roof of a low-rise building.     

考虑风速风向联合概率分布的风电塔筒结构风致疲劳寿命评估

针对风向对风力机塔筒疲劳产生影响的问题,基于实测数据对考虑风速风向联合概率分布的风电塔筒结构的风致疲劳寿命展开研究。首先结合甘肃安西地区37 a的实测风速风向数据,给出风速风向联合概率分布。然后利用主S-N曲线法分别对不同风向和不同风速下风力机塔架结构法兰及门洞区域的响应规律进行分析。最后考虑风速风向联合概率分布,对风电塔筒结构风致疲劳寿命展开研究。结果表明：门洞朝向与风轮朝向的夹角变化和风速的改变均对风电塔筒的风致疲劳寿命有一定影响,其中门洞朝向与风轮朝向夹角为225°时疲劳寿命最长,风速为10~14 m/s时疲劳寿命变化幅度最大;考虑风速风向联合概率分布能更准确地计算风力机结构的风致疲劳寿命,且以此为依据对门洞朝向进行调整可延长其疲劳寿命,因此建议对风电塔架进行设计时,应考虑风电场所在地区的风速风向联合概率分布。     

陕西省金润河北镇风电场风能资源开发评估

对陕西省宝鸡市陇县金润河北镇风电场气象条件、风功率密度、平均风速、主导风向等风能参数进行分析评价。结果表明,测风塔100 m高度月平均风速、月平均风功率密度最大均出现在4月,最小均出现在8月;测风塔100 m高度主导风向为SSW(南西南),主要风能方向为SSW(南西南),风电场风功率密度等级为1级。风电场安装20台2500 kW的风电机组,装机容量50 MW,年设计发电量1.33485×108 kW·h,年出厂电量9.5426×107 kW·h。结果可为其他风电场选址和发电量估算提供参考。     

风电场中多台风力机的数值模拟

将NREL 5 MW风力机作为基本机型,使用致动线模型和大涡模拟相结合的数值方法,在中性大气边界层中模拟含有多台风力机的风电场。为了模拟风电场的复杂入流条件,首先模拟体积为3000 m(长)×3000 m(宽)×1000m(高)的大气边界层,并对模拟结果进行验证,结果表明:在覆盖逆温层以下,不同高度处的位温不变,平均风速满足剪切特性,脉动风速满足湍流谱特性;然后,分析了致动线模型中风轮直径上的网格节点数量(N)和高斯分布因子(ε)的取值规律,发现ε以网格尺度(η)为自变量取值时,N越大,η的系数越大,当N取63时,η的系数可取2或3,但N取25时,η只能取1.2;最后,使用致动线模型在大气边界层中布置8台风力机,模拟风电场,并对风力机间的相互干扰进行分析,发现第一排风力机功率明显大于其他风力机功率输出,占风场总功率输出的40.3%。     

Assessment of offshore wind farm characteristics with the cloud resolving storm simulator: A case study in Japan

Wind conditions and output power characteristics of a wind farm in Japan are evaluated with highly resolved weather predictions from the so‐called cloud resolving storm simulator. One year of 30‐hour‐ahead predictions with 2‐km spatial resolution and 1‐hour time resolution are evaluated against 10‐minute averaged measurements (averaged to hourly data) from the wind farm. Also, extremely detailed shorter‐term predictions with 200‐m spatial resolution and 1‐second time resolution are evaluated against 1‐Hz measurements. For the hourly data, wind speeds are predicted with an RMSE of 3.0 to 3.5 m/s, and wind power with about 0.3 per unit. Wind direction is predicted with a standard deviation of errors of 16° to 28° for hourly data, and generally below 10° for the 1‐Hz data. We show that wind power variability—here in terms of increments—can be assessed on the timescale of several hours. The measured and predicted wind spectra are found similar on both short and long timescales.     

不同类型漂浮式风电场内机组塔基载荷研究

构建基于NREL 5 MW 风电机组的海上固定式风电场和不同类型的漂浮式风电场,考虑不同类型风电机组尾流特性、平台漂浮特性的差异,在不同工况下对风电场内机组动力学响应进行仿真计算。通过时域分析与箱线图分析,对风电场内各位置处机组在风、浪、尾流联合作用下的塔基载荷进行对比研究。结果表明：在相同工况下,Spar式风电场内机组风轮与平台位移值、塔基载荷在来流方向上最大;在中低风速下,风电场内机组塔基载荷相差较大;高风速时,塔基载荷相近;随着风速的增大,漂浮式机组塔基载荷呈先增大后减小的规律。     

Influence of atmospheric stability on wind turbine loads

Simulations of wind turbine loads for the NREL 5 MW reference wind turbine under diabatic conditions are performed. The diabatic conditions are incorporated in the input wind field in the form of wind profile and turbulence. The simulations are carried out for mean wind speeds between 3 and 16 m s ^{? 1} at the turbine hub height. The loads are quantified as the cumulative sum of the damage equivalent load for different wind speeds that are weighted according to the wind speed and stability distribution. Four sites with a different wind speed and stability distribution are used for comparison. The turbulence and wind profile from only one site is used in the load calculations, which are then weighted according to wind speed and stability distributions at different sites. It is observed that atmospheric stability influences the tower and rotor loads. The difference in the calculated tower loads using diabatic wind conditions and those obtained assuming neutral conditions only is up to 17%, whereas the difference for the rotor loads is up to 13%. The blade loads are hardly influenced by atmospheric stability, where the difference between the calculated loads using diabatic and neutral input wind conditions is up to 3% only. The wind profiles and turbulence under diabatic conditions have contrasting influences on the loads; for example, under stable conditions, loads induced by the wind profile are larger because of increased wind shear, whereas those induced by turbulence are lower because of less turbulent energy. The tower base loads are mainly influenced by diabatic turbulence, whereas the rotor loads are influenced by diabatic wind profiles. The blade loads are influenced by both, diabatic wind profile and turbulence, that leads to nullifying the contrasting influences on the loads. The importance of using a detailed boundary‐layer wind profile model is also demonstrated. The difference in the calculated blade and rotor loads is up to 6% and 8%, respectively, when only the surface‐layer wind profile model is used in comparison with those obtained using a boundary‐layer wind profile model. Finally, a comparison of the calculated loads obtained using site‐specific and International Electrotechnical Commission (IEC) wind conditions is carried out. It is observed that the IEC loads are up to 96% larger than those obtained using site‐specific wind conditions.Copyright © 2012 John Wiley & Sons, Ltd.     

基于等效风速的风电机组参数对输出功率波动和功率损失特性的影响

以大型三叶风电机组为例,研究发电机组参数对输出功率波动及功率损失的影响。首先建立包括风剪切和塔影效应的等效风速模型,推导输出功率和功率系数的数学模型,研究叶轮半径、塔筒高度、塔筒直径和叶片到塔筒中线的悬垂距离等相关参数对功率波动的频率、幅值、波长、波动区域等特性影响规律。然后建立功率损失的数学模型,研究风电机组参数通过风剪切和塔影效应对功率损失造成的影响规律。结果表明:不同参数通过风剪切和塔影效应对输出功率周期性波动及功率损失的影响规律不同,功率周期性波动的幅值及波长受塔筒直径和悬垂距离2个参数影响较大,而功率损失受叶轮半径和塔筒高度2个参数影响较大,但其作用效果相反:功率损失程度随叶轮半径的增大而增大,但随塔筒高度的增大而减小。