基于Windographer的某区域风电场风资源分析评估

根据甘肃省某区域风电场测风塔10 m、40 m、60 m、80 m高度的实测风数据,利用Windographer4.2风资源分析软件计算空气密度、平均风速和风功率密度年内变化和日变化、风速和风能频率分布、风向频率和风能频率方向分布、风切变指数、湍流强度和50年一遇最大风速等指标参数。其计算结果表明测风塔80 m高度年平均风速为6.93 m/s,年平均风功率密度为354 W/m~2,年有效风速(3.0～25.0 m/s)时数为7 200 h以上,盛行风向稳定。60～80 m高度湍流强度在0.072～0.080之间,小于0.12,湍流强度较小。综合判定该区域风能资源较为丰富,符合大型风电场建设条件,适宜进行大规模风电开发利用。     

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。     

基于WRF模式的四川省凉山州地区风能资源可开发区域研究

利用MERRA2再分析数据驱动WRF模式,对四川凉山州地区2020年全年进行风资源模拟分析,并用凉山州地区典型测风塔数据对模拟结果进行检验,并进行详细地风资源分析,再根据风电场开发8%基准内部收益率反推可开发风能资源的区域分布。结果表明：凉山州大部分地区100 m高度年平均风速在5 m/s以上,风速极大值一般位于山脊,凉山州风能最好的区域主要集中在会东县和宁南县。凉山州典型区域内均表现出受西南季风影响的特征,即冬、春季节风大,夏、秋季节风小,主风向呈强西南风状态,且风功率密度变化规律与风速的变化规律基本一致。凉山州山地区域可开发风能资源的平均风功率密度临界值为258 W/m²,这些区域主要集中在会理、会东、宁南、布拖、木里和盐源县境内。可开发区域分布图对指导凉山州地区风能开发提供科学参考。     

鄱阳湖区松门山-吉山风场风能资源特性分析

利用松门山-吉山风场70m测风塔2009年4月～2010年3月测风资料及都昌气象站近20a平均风速资料,对松门山-吉山地区的风能资源参数进行了详细计算和分析,并对松门山-吉山风能资源开发利用进行了可行性分析评价。结果表明:松门山-吉山测风塔各高度层全年盛行偏北风,主导风向为N和NNE,主导风向风能占总风能的90%左右。30~70m高度湍流强度和风切变指数较小。50、70m高度处风能资源有效小时百分率为73﹪~76%,风功率密度分别为302.8、326.7W/m2,风能资源等级为3级,属风能资源较丰富区,具备风电开发价值。     

鄱阳县小鸣咀风场风资源分析

利用鄱阳县小鸣咀风场60m测风塔风资料,计算了该区域的平均风速与风功率密度,评价了风能资源的风向分布特征,推算了当地70m处极大风与最大风。分析结果表明:该风场风能资源丰富,可用于并网发电。     

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。     

风资源评估中WindSim水平分辨率的敏感性试验

利用基于计算流体力学(CFD) 的风能资源评估系统软件WindSim,在不同水平网格分辨率条件下对我国黄土高原地区陕西靖边县境内某风电场2010年7月~2011年6月的风资源情况进行了模拟,并将模拟结果与测风塔观测结果进行了对比分析。结果表明,在低水平网格分辨率下,WindSim对风能资源的空间分布模拟主要以海拔高度为基础,对局地地形的影响并不能很好地反映,模拟风速误差较大;提高分辨率后,对风能资源空间分布的模拟能力明显提高,模拟风速的误差也显著减小。但不同分辨率下的风速频率和风向频率分布并无显著差别,不能很好地体现出风能特性。通过估算发电量发现,输入不同测风塔资料得到的发电量差异较大,说明在地形较为复杂的风电场,应多布设测风塔,以期得到较为准确的发电量结果。     

激光雷达在不同地形条件下进行风资源评估的适用性研究北大核心CSCD

为了验证WindCube激光雷达在不同地形和不同测量高度条件下替代测风塔评估风资源的可行性,文章采用WindCube激光雷达与测风塔在复杂山地、平原和沿海3种地形条件下的同步观测试验数据,对风速、风向、相对偏差和风廓线进行了对比分析。对比结果表明:WindCube测量高度越高,有效数据完整率越低,在90~120 m轮毂高度,有效数据完整率在90%以上,能满足风能资源评估要求;在复杂山地、平坦地形条件下,WindCube与测风塔风速相关系数达0.99以上,风向相关系数在0.85~0.90,两种仪器测得的10 min平均风速偏差在0.1 m/s以内,相对偏差在1%左右,WindCube可代替测风塔进行风能资源评估;沿海地形条件下,WindCube与测风塔风速相关系数达0.90以上,风向相关系数在0.90左右,WindCube与测风塔测得的10 min平均风速偏差较大,达0.5 m/s,相对偏差在10%左右,受下垫面影响,WindCube替代测风塔进行风能资源评估的可行性应根据项目实际情况进一步评估。     

中国典型地区风能资源特性研究

利用西北地区和东南沿海地区具有代表性的测风塔资料,对比分析其风能资源特性差异,结果发现:①即使西北和东南沿海地区的年平均风速相同,西北地区的年平均风功率密度和年风能密度均显著大于东南沿海地区,其风功率密度可大1～2个等级,造成这种显著差异的关键因子是西北地区"大风速"的出现频率较东南沿海地区多;②西北地区和东南沿海地区的风向变化主要以小角度变化为主,但两地区的风向变化特征明显不同:西北地区的小风向变差角出现频率略少于东南沿海地区,而较大的风向变差角出现频率明显多于东南沿海地区.两类地区不同的风资源特性将影响风电场选址和设计、风电机组选型以及建成后的运行管理模式,具有重要的现实意义和使用价值.     

风电场代表年数据订正方法的不确定性分析

选取陕西某复杂地形风电场测风塔2009~2011年3年逐时测风数据,利用16方位相关法计算得到该风电场测风塔代表年数据,利用该方法进行测风塔代表年数据订正过程中的不确定性,并对产生不确定性的原因进行分析。结果表明:若测风塔观测时段不同,得到的代表年数据也存在差异,说明测风塔和气象站在不同年份各风向风速差异上的不一致必然会对代表年数据计算造成一定的影响。另外,测风塔和气象站风速在月尺度和日尺度上的差异、风向变化上的差异也会导致测风塔代表年数据存在误差。利用MM5/CALMET模式提取测风塔所在位置2009~2011年3年逐时风速风向数据,将数值模拟结果、16方位相关法计算的代表年结果分别与测风塔实测数据进行对比,发现数值模拟结果误差明显小于用16方位相关法得到的代表年数据。因此认为在气象站数据与风电场测风塔数据风速风向变化一致性较差的情况下,可选择数值模拟技术对测风塔长期风况进行模拟,得到测风塔长期风况,较为准确客观地评价风电场的风能资源。     

Worldwide wind energy status and the characteristics of wind energy in Iran,case study: the province of Sistan and Baluchestan

In this paper, the recent trend of the worldwide wind energy utilisation is reviewed and the recent activities in using renewable energy sources in Iran are explained. As a case study, the wind characteristics of the province of Sistan and Baluchestan are statistically analysed. The wind characteristics such as the monthly mean wind speed and the wind power density of each station are presented. The monthly variation of the wind direction is presented and also the dominant wind direction is shown in a wind rose diagram. The values of turbulence intensity at different heights are calculated. The results show that the stations of Khash and Nosratabad are more suitable for limited off-grid utility applications. Lootak with the average annual wind power density of 388?W?m^?2 at the height of 40?m and constant wind direction is recommended for large-scale grid-connected wind turbines.     

世界风力发电现状与前景预测

全球可再生能源发电装机容量中风电占有压倒性优势,今后可望成为欧洲、亚洲、北美的主要电力来源.2011年中国以62GW的累计装机容量蝉联世界第一,按照我国“十二五”规划目标,预计到2015年风电装机容量将达到1×108kW,年发电量1900×108kW·h.GWEC和Greenpeace预测,今后20年风力发电将成为世界主力电源,2030年装机容量有可能达到23×108kW,可供应世界电力需求的22％.欧美正大力开发海上风电产业.欧洲是世界海上风电发展的先驱和产业中心,欧洲企业不仅拥有自己的核心技术,而且还向世界各地输出技术,今后欧洲海上风力发电将急速增长.美国采取与英国、德国等欧洲厂家相同的战略,大力发展海上风力发电.我国海上风电产业刚刚起步,预计2015年海上风电装机500×104kW.日本学者大岛教授推算了不同电源的发电成本:包括政府财政补贴,运行年限30年的核电站发电成本为12.06日元/(kW·h);按标准设备利用率,风力发电成本11.30日元/(kW·h),与核电相比已经有竞争力.假设风况好时设备利用率达到35％,发电成本为7.95日元/(kW·h),比核电低得多.     

Wind power potential in Oman

Solar energy and wind are likely to play an important role in the future energy generation in Oman. This article assesses wind power cost per kWh of energy produced using four types of wind machines at 27 locations within Oman. These sites cover all regions in Oman. Hourly values of wind speed recorded between 2000 and 2009, in most cases, were used for all 27 locations. Wind duration curves were developed and utilized to calculate the cost per kWh of energy generated from four chosen wind machines. It was found that the cost of energy is low in the south and middle regions of Oman compared with that in the north region. The most promising sites for the economic harnessing of wind power are Thumrait, Qairoon Hairiti, Masirah, and Sur, with an energy cost of less than 0.117 US$/kWh when 2000 kW, 1500 kW, 850 kW, or 250 kW wind turbines are used.     

国内外风电持续迅猛发展

国外统计数据表明,近几年世界风电持续高速发展。据国内统计数据,我国2006年、2007年风电装机容量连续两年翻番。我国内资风电设备制造企业已形成3个梯队,2007年我国内资风电设备制造企业所占市场份额首次超过外资企业。介绍了我国风能资源的最新评估,在假设条件下,全国陆上风能可开发资源量为8×10^8kW,近海为1．5×10^8kw：陆上和近海合计可提供风电电量约为2×10^12kW·h。预计我国风电装机容量2010年和2020年只有分别达到2000×10^4kW和1×10^8kw时才能实现非水电可再生能源发电量的强制性市场份额目标。     

Wind energy evaluation for electricity generation using WECS in seven selected locations in Nigeria

This paper statistically examine wind characteristics from seven meteorological stations within the North-West (NW) geo-political region of Nigeria using 36-year (1971–2007) wind speed data measured at 10 m height subjected to 2-parameter Weibull analysis. It is observed that the monthly mean wind speed in this region ranges from 2.64 m/s to 9.83 m/s. The minimum monthly mean wind speed was recorded in Yelwa in the month of November while the maximum value is observed in Katsina in the month of June. The annual wind speeds range from 3.61 m/s in Yelwa to 7.77 m/s in Kano. It is further shown that Sokoto, Katsina and Kano are suitable locations for wind turbine installations with annual mean wind speeds of 7.61, 7.45 and 7.77 m/s, respectively. The results also suggest that Gusau and Zaria should be applicable for wind energy development using taller wind turbine towers due to their respective annual mean speeds and mean power density while Kaduna is considered as marginal. In addition, higher wind speeds were recorded in the morning hours than afternoon periods for this region. A technical electricity generation assessment using four commercial wind turbines were carried out. The results indicate that, while the highest annual power is obtained with Nordex N80–2.5 MW as 14233.53 kW/year in Kano, the lowest is in Yelwa having 618.06 kW/year for Suzlon S52. It is further shown that the highest capacity factor is 64.95% for Suzlon S52–600 kW in Kano while the lowest is 3.82% for Vestas V80–2 MW in Yelwa.     

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。     

The potential of electricity generation on the east coast of Red Sea in Egypt

Wind characteristics have been analyzed based on long-term measured data of monthly mean wind speed of seven meteorological stations along the east coast of Red Sea in Egypt. It was found that the windiest stations (Region A) namely (Zafarana, Abu Darag, Hurghada and Ras Benas) have annual mean wind speeds (7.3, 7.2, 6.4 and 5.5 m/s) at 10 m height, respectively.Numerical estimations using measured wind speeds and frequencies to calculate the two Weibull parameters were carried out and two methods were applied.The methodical analysis for the corrected monthly wind power density at a height of 10 m above ground level, over roughness class 0 (water), for each station was done. The recommended correlation equation was also stated for Red Sea zone in Egypt. Also the corrected annual wind power density at the heights (50–70) m was obtained for all stations. Moreover, calculations show that the four stations in (Region A) have a huge energy potential available (430–1000 W/m²) at 70 m height, while Quseir and Suez stations (Region B) have good wind power density (170–190 W/m²) at 50 m height.A technical and economic assessment has been made of electricity generation from two turbines machines having capacity of (1000 and 600 kW) considered in Regions A & B, respectively, using WASP program. The yearly energy output, capacity factor and the electrical energy cost of kWh produced by the two different turbines in each region were estimated. The production costs of four stations in Region A was found to be less than 2€ cent/kWh and compared with retail tariff.     

关于中国风能资源储量的质疑

目前普遍认为中国的风能资源为20×10^8kW。1980年第一次风能资源普查得出我国风能资源储量约为1．6×10^8kW的结论。1984年9月至1987年7月开展了第二次风能资源详查,1995年国家气象局对外公布．我国陆上10m高度处风能资源总储量为32．26×10^8kW,技术可开发资源量为2．53×10^8kW。2004年进行了第三次陆上风能资源普查。结果为我国陆上风能资源总储量43．5×10^8kW,其中技术可开发量为2．97×10^8kW。近期中国气象局公布．我国风能开发潜力逾25×10^8kW,5-25m水深线以内近海区域海平面以上50m高度可装机2×10^8kW,推翻了此前我国海上风能资源是陆上3倍的说法。中国风能资源的前3次普查都只是对陆上的风能资源进行了测算．而且只测算了陆上10m高度处风能资源的理论蕴藏量,再根据理论蕴藏量推算出风能的技术可开发资源量．数据是很粗略的。陆上风能技术可开发资源量估计偏高,风能资源经济可开发量尚需很好地测算,海上风能资源评估缺乏依据,风力发电机组高度和风电的年可利用小时数也存在问题。我国要加强风能资源利用的研究,研究重点应放在风能资源的经济可开发量、气候变化对风能资源的影响、台风和灾害性天气对风电开发的影响、能够用于发展风电的土地面积等方面。     

Wind characteristics and energy potentials for Owerri, Nigeria

Wind characteristics and wind energy resource potentials for Owerri, Nigeria are presented. These were evaluated using routine wind data measurements at a height of 10 m above ground level at the Lake Nwebere Campus, Federal University of Technology, Owerri between 1988 and 1992. The most prevailing wind is from the Southwest and the average wind speed and its variation are 2.80 and 0.81 m s⁻¹, respectively.Accordingly, the maximum annual mean power density exploitable from the wind at this site is 7.66 ± 0.15 W m⁻² out of the estimated available annual mean wind power density of 12.91 ± 0.26 W m⁻². The annual mean energy density available in the wind was found to be 60.29 kW h m⁻². Thus, the potential for year-round wind energy utilization in Owerri, Nigeria is rather low.