吉林长岭风场区风能资源统计评估

利用30 a风场数据作为基础研究资料,对吉林省长岭县风场区风能资源进行全面评估。评估结果发现,长岭县风场区风能资源蕴藏较为丰富,场区所在区域风向、风能分布相对集中,每年的3,4,5,10,11月,风场风速和风功率密度较高,1,7,8,12月较低。115 m高度处、80 m高度处的测风塔年平均风速、风功率密度分别为6.33,5.91 m/s和285.7,232.9 W/m²。115 m高度处、80 m高度处的虚拟测风塔年平均风速、风功率密度分别为6.42,6.00 m/s和299.1,243.8 W/m²。80 m处测风塔与虚拟测风塔风功率密度等级分别为1级和2级。了解长岭县风能资源分布规律,对于进一步合理开发利用吉林省可再生能源以及推进风电项目顺利开展具有一定的指导意义。     

一种基于大气稳定度的风资源评估方法

在风资源评估过程中,平均风速、风切变指数、风功率密度等是必须测量的特性参数,这些参数的测量均受地形地貌、大气稳定度、测风时间、测风设备的影响。在目前的风资源评估中,大气稳定度的影响基本都被忽略,因此,影响了风资源评估的准确性,甚至会带来选址的决策性失误。文章研究了大气稳定度对风资源特性的影响,并以美国某地4年的测风数据为例,研究大气稳定度对风切变指数,风能玫瑰图,风功率密度等的影响,建立了考虑大气稳定度的轮毂高度风速外推模型,解决了目前风资源评估中外推轮毂高度风速时由于使用整个风电场的平均风切变指数而带来风资源评估误差的问题。算例结果表明,该模型结构简单,外推结果精度高,具有较强的工程实用价值。     

基于ArcGIS与多因子模型的风力发电场选址评估

基于地理信息系统，研究并提出一种基于ArcGIS与多因子模型的风力发电场选址评估方法，以实现对不同地区风能资源空间分布情况、开发适宜性和理论发电量的有效评估，进而为风电场的选址提供理论依据。首先，基于不同地区的风资源气象数据，通过引入地形、道路等地理限制因素，提出一种多因子模型，以实现对不同地区风能资源开发适宜性评估。然后，基于10 m高度处的风速分布，通过风速外推得到80 m高度处的风速分布，进而用于评估80 m高度处的风能理论发电量。最后，综合上述开发适宜性和理论发电量评估结果，可较为准确地给出计及风速、风功率密度、地形、道路等多因子模型的风电场选址建议。结果发现：风电场选址主要集中在西北部、东北部以及内蒙古等地。     

基于热稳定度风向标准差法的风速外推模型研究

针对风能评估中外推轮毂高度处风速的问题,分析了高层风切变指数特性,建立了基于风向标准差法的风速外推模型。该模型首先剔除小于3 m/s的低风速数据及大于25 m/s的高风速数据,再利用风向标准差法对该地区风资源进行热稳定度分类,计算相应的风切变指数,并进行轮毂高度处风速推算。计算结果表明,相对于没有进行数据筛选的计算模型,推算精度提高了5.46%,加强了风能评估的准确性,对风电场的风资源评估具有一定的指导意义。     

典型风电场地形大气稳定度对风机出力的影响

[目的]分析了大气稳定度对风机出力的影响,为提高计算流体动力学（Computational Fluid Dynamics,CFD）风能资源模拟精度提供技术参考。[方法]选取立于平坦和复杂山地两类典型地形上的两座测风塔不同高度的风速、气温、气压等观测数据,使用莫宁-奥布霍夫长度法分别计算两座测风塔所在区域的大气稳定度,参照Irwin大气稳定分类标准对稳定度计算结果分类,再根据分类结果进行两座测风塔轮毂高度处出力分析。[结果]结果表明：在近地面层,复杂山地大气热效应造成的表层垂直混合作用更为明显,造成的大气不稳定性较为强烈,但垂直混合作用不充分;复杂山地大气稳定度对风机出力的影响大于平坦地形,其不确定性更强。[结论]在进行CFD风电场流体建模时需要考虑大气稳定度的影响,特别是超低风速复杂山地场址条件下,大气稳定度的评估对风机选型及发电量仿真精度尤为重要。     

陕北典型风能特性分析

该文分析了榆林靖边与定边2处风电场2019年测风塔观测数据,发现两地风速、风向分布具有较强局地性,靖边风电场年平均风速明显小于定边风电场年平均风速,靖边地区风速概率属于单峰分布,定边地区风速分布更加均匀,靖边风电场70 m平均风速呈现V字型分布,定边地区风速分布呈现浅U字型。靖边与定边均呈现出冬季平均风速大,夏季风速最小,风功率密度冬春季最大,夏秋季明显降低的分布特点,且两地70 m风功率密度与陕西年负荷在春、夏、秋3季均呈现较明显的反向分布。     

新疆达坂城风电场风能资源特性分析

对新疆达坂城风电场的风能资源特性进行了详细的研究。基于在达坂城风电场实测的10m和24m高程的10min平均风速数据,分析了原始风速的分布特性。根据地表风速沿高度呈风剪指数分布的特性,计算了在各个轮毂高度上的风速分布。采用最小误差逼近算法原理,计算了风速韦布尔分布的参数以及平均风速和分布方差。通过对韦布尔分布的分析,计算了各个高度上风电场的平均风功率密度、有效平均风功率密度和可利用小时数等风能资源特性参数,为当地的风能开发提供分析基础。     

二参数Weibull分布在风能资源参数长年代订正中的应用探讨

选择代表平原、丘陵和山区的6个气象站分别作为参证站和订正站,采用二参数Weibull分布法和线性回归法进行30 a订正效果检验,结果表明:短期资料进行风电场风能资源评估,误差较大;二参数Weibull分布法适宜不同地形风能资源参数长年代平均订正,年平均风功率密度的订正效果更好;线性回归法适宜于订正站和参证站线性相关性较好的长年代平均订正;使用2 a以上的观测资料,订正效果较1 a资料有所提高。     

利用STRM和NCEP数据提高风电场宏观选址的准确性

利用STRM数据得出风电场宏观地形,利用NCEP数据提取出风电场的气象数据,在WASP813软件的支持下,计算出描述风资源概况的风速、风功率密度和威布尔分布参数值的分布概况。根据风速、风功率密度分布可以直观地看出风资源的分布情况．根据威布尔分布参数值能够计算出初步的发电量,进而为风电场的宏观选址和下一步测风塔的建立提供依据。     

用矩法估算Weibull分布三参数

通过对三参数Ｗｅｉｂｕｌｌ风频分布模型中风速Ｖ的α次矩、２α次矩和３α次矩的研究，导出了参数的估算公式。     

Potential wind power generation in the State of Kuwait

The wind characteristics of six locations in the State of Kuwait have been assessed. The annual average wind speed for the considered sites ranged from 3.7 to 5.5 m/s and a mean wind power density from 80 to 167 W/m² at standard height of 10 m. The Weibull parameters and power density of each station have been determined using Weibull distribution. The wind data at heights 15, 20, 25 and 30 m were obtained by extrapolation of the 10 m data using the Power-Law. The potential wind energy at different heights was estimated using Weibull parameters. Maximum power density is found at 30 m height which varies between 130 and 275 W/m² with 70% increase from the standard height indicating fairly potential wind energy especially in the northern part of the country. The highest potential wind power was found during the summer season which is the peak demand season of electricity in Kuwait.     

A survey on the assessment of wind energy potential in Egypt

In this paper, wind data obtained from the Egyptian Meteorological Authority are used to assess monthly and annual wind power and wind energy. The study is based on data from 15 anemometer meteorological stations, distributed all over Egypt and covering a period ranging from 1973 to 1994. For these stations the wind data are summarized. The wind energy potential at the 25 m height was obtained by extrapolation of data at 10 m using a power-law expression. The result presents the mean wind energy density estimates and potential for application in Egypt. The analysis showed that along Red Sea coasts, the annual wind energy flux is found to be high, which indicates that these coastal stations are possible locations for wind energy utilization. On both the Mediterranean coast and in the interior parts of Egypt, some stations are of low available wind energy, while others are found to be rather high. Also, the two Weibull distribution parameters have been estimated from the wind speed data for some meteorological stations and the wind power density is calculated using the values of these parameters.     

Extrapolating wind speed time series vs. Weibull distribution to assess wind resource to the turbine hub height: A case study on coastal location in Southern Italy

Increasing knowledge on wind shear models to strengthen their reliability appears as a crucial issue, markedly for energy investors to accurately predict the average wind speed at different turbine hub heights, and thus the expected wind energy output. This is particularly helpful during the feasibility study to abate the costs of a wind power project, thus avoiding installation of tall towers, or even more expensive devices such as LIDAR or SODAR.The power law (PL) was found to provide the finest representation of wind speed profiles and is hence the focus of the present study. Besides commonly used for vertical extrapolation of wind speed time series, the PL relationship between “instantaneous” wind profiles was demonstrated by Justus and Mikhail to be consistent with the height variation of Weibull distribution. Therefore, in this work a comparison is performed between these two different PL–based extrapolation approaches to assess wind resource to the turbine hub height: (i) extrapolation of wind speed time series, and (ii) extrapolation of Weibull wind speed distribution. The models developed by Smedman–Högström and Högström (SH), and Panofsky and Dutton (PD) were used to approach (i), while those from Justus and Mikhail (JM) and Spera and Richards (SR) to approach (ii). Models skill in estimating wind shear coefficient was also assessed and compared.PL extrapolation models have been tested over a flat and rough location in Apulia region (Southern Italy), where the role played by atmospheric stability and surface roughness, along with their variability with time and wind characteristics, has been also investigated. A 3-year (1998–2000) 1–h dataset, including wind measurements at 10 and 50 m, has been used. Based on 10–m wind speed observations, the computation of 50–m extrapolated wind resource, Weibull distribution and energy yield has been made. This work is aimed at proceeding the research issue addressed within a previous study, where PL extrapolation models were tested and compared in extrapolating wind resource and energy yield from 10 to 100 m over a complex–topography and smooth coastal site in Tuscany region (Central Italy). As a result, wind speed time series extrapolating models proved to be the most skilful, particularly PD, based on the similarity theory and thus addressing all stability conditions. However, comparable results are returned by the empirical JM Weibull distribution extrapolating model, which indeed proved to be preferable as being: (i) far easier to be used, as z₀–, stability–, and wind speed time series independent; (ii) more conservative, as wind energy is underpredicted rather than overpredicted.     

Assessment of the wind energy resource in the South Banat region,Serbia

The wind energy resources in the South Banat region are analyzed. The analyses have been carried out on the basis of the wind parameter measurements at the site of village Bavani?te. The data were collected at the heights of 10, 40, 50, and 60 m during 2009 and 2010. The statistical analyses of the measured data covered the wind speed and direction, average wind speed and power density, and Weibull distribution parameters (c and k). On the basis of the determined standard deviation of the wind speed, an analysis is performed of the wind turbulence at the measurement site. Based on the method of sum of least squares, a mathematical method for estimation of the vertical wind speed profile has been developed. By applying this model, an analysis of the vertical wind speed profile at the measurement site has been performed. On the basis of the available measurement data, the electrical energy production in the targeted region by three test models of the wind turbines has been estimated. The obtained results show that the region of South Banat possesses good wind energy potential and that it represents a promising region for development of the projects of wind farms.     

基于风速误差校正和ALO-LSSVM的风电功率预测

风资源的随机波动性引起的相位滞后性问题,导致风电功率预测精度不高,尤其是风速变化较快时,滞后性引起的预测误差较大。考虑到风速波动与风功率变化密切相关,提出一种非参数核密度估计和数值天气预报(NWP)相结合的方法,并对预测风速误差进行校正,改善了预测风速的相位滞后性;然后将校正后的风速和风功率作为输入数据进行风电功率预测;采用蚁狮算法(ALO)优化最小二乘支持向量机(LSSVM)参数,从而建立基于风速误差校正和ALO-LSSVM组合的风电功率预测模型。算例结果表明,所提方法风功率预测精度更高。     

An onsite demonstration and validation of LiDAR technology for wind energy resource assessment

The investigation of wind resource at higher heights is very crucial in planning wind power project. Normally, this involves the installation of a high and costly meteorological mast with a cup anemometer and wind vanes. This investigation uses the new ground-based remote-sensing technique Light Detection and Ranging (LiDAR) to investigate the wind resource at higher heights. This paper describes the LiDAR technology principle and examines the potential of LiDAR measurement to estimate the wind resource at higher heights by conducting a measurement campaign at Tamil Nadu, India. The wind statistics were determined using the 10?min average time-series wind data monitored by ZephIR LiDAR. These include the Weibull parameters, daily mean wind speed, wind power density, wind energy density, vertical wind speed profile and capacity factor. The investigation reveals that the vertical wind speed profile measured from the LiDAR system has approximate closer values to the standard meteorological measurement.     

A surface-layer wind speed correction: A case-study of Darling station

In previous study, the vertical wind speed extrapolation from measurement station to modern turbine hubs over an open homogenous terrain was considered. It was presented that an assumption of wind shear exponent under different stability conditions was an inaccurate representation of the actual wind climates as the precise knowledge of the site's wind characteristics at different levels and seasons are essential for planning and implementation of a proposed energy project. In this study, the surface-layer wind speed correction at Darling using the WRF modeling with mesoscale terrain corrections is presented. An hourly mesoscale modeled winds at 3 km grid spacing obtained for one month are postprocessed for estimation of local wind speed profiles at 10 and 50 m height AGL. The sensitivity of the modeled winds to surface terrain corrections is investigated using mesoscale topography parameterizations. Furthermore, 6-hourly mesoscale modeled and satellite observed winds as well as measurements from Darling station are utilized for validation of the statistical downscaling method utilized for the postprocessing of the boundary layer winds over land. It is presented that the precision of the mesoscale modeled winds for local wind speed estimates at potential site without historical measurements can be significantly improved. The confidence in the validity of this methodology for local wind speed correction is estimated at 96–98%.     

测风数据的时间间隔对风速概率分布参数计算的影响

风电场风速概率分布是体现风能资源统计特性的重要指标.文章在认为风速服从双参数威布尔分布的前提下,对于不同时间间隔所记录的风数据,分别应用最小二乘法、平均风速和标准差估算法、平均风速和最大风速估算法求解风速概率分布参数,由此估算出能直接体现风能资源状况的风能特征指标值.比较由风速概率分布推算出风能特征指标的估计值与由记录...