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.     

尖山子风电场风能资源评价

根据尖山子风电场1999年7月～2000年6月测风资料，对风电场的风能资源各参数进行了详细地计算和分析，从而得出尖山子地区风能资源丰富，适宜建设大型风电场，具有较大的开发利用价值的结论。     

佳木斯风能资源形成分布探讨

风能资源是清洁的可再生能源,风能发电是新能源领域中技术最成熟、最具规模开发条件和商业化发展前景的发电方式之一,也是目前清洁能源中利用最方便、最快捷、最少投入的可再生能源之一。已经成为世界能源可持续发展战略的重要组成部分。因此本文从风的形成原因、影响风速大小的因素、佳木斯风能资源的分布状况和可建风电规模（发展目标）等方面予以阐述,为佳木斯的风电发展提供理论参考根据。     

老爷庙风电场风能资源评价

本文利用老爷庙风电场2001年4月～2002年4月逐时平均风向、风速资料，对老爷庙风电场的风能资源各参数进行了计算和分析，并与附近星子气象站累年或同期资料进行比较，对老爷庙风电场风能资源进行评价。     

中国风能资源贮量估算

为了解决了我国风能资源贮量到底有多大这一基本背景问题,根据全国900余个气象台站实测资料作出的多年年平均风能密度分布图,首次完整细致地估算出各省及全国离地面10m高度层上的风能资源储量,我国的风能资源总贮量为32.26×10     

崇明岛风力资源分析与评价

根据风能密度、风能频率分布、风向频率等气象参数,对上海崇明岛风力资源状况和风力发电前景进行了分析与评价.结果显示,崇明岛50m高度处的年平均风速为7.0m/s.年平均风能密度为339.1W/m2,年有效风速小时数为8418h,年可利用风能小时数为2208h,主风向较为稳定,风能分布较为集中.分析表明,崇明岛风力资源丰富,达到开发标准,适宜发展风力发电.文章为开发崇明风力资源提供了有价值的参考.     

云南风能资源的评估研究

分析了云南各地有效风能功率密度和风能可利用小时数等多个风能资源评估中的主要物理量,说明了云南风能资源的特殊性和可利用性。     

全球海域风能资源储量分析

利用高精度、较高时空分辨率的CCMP风场,计算了近22年全球海域的风能密度、有效风速出现频率、风能密度变化趋势、风能资源储量,以期为海上风力发电等风能资源的开发利用提供定量的科学依据。全球大部分海域的风能密度在200W/m2以上,仅在赤道附近小范围海域低于200W/m2,大值区分布于南北半球西风带海域,中国大部分海域的风能密度都在200W/m2以上;全球大部分海域的有效风速出现频率很高,基本都在90%以上,即使出现频率偏低的海域也基本都在50%以上,中国海域的有效风速出现频率大多在80%以上;近22年间全球大部分海域的风能密度呈显著性逐年线性递增趋势,仅部分零星海域的变化趋势不显著或呈显著性逐年线性递减趋势,这对于风能资源的开发利用是有利的;全球海域的风能资源总储量、有效储量和技术开发量分布特征都较为一致,大值区均分布于南北半球西风带海域,向低纬度逐渐递减,中国大部分海域的风能技术开发量都在2×103kW.h/m2以上。     

对福建省陆地风能资源的评估

对我国福建省福州和厦门2座城市进行了风能开发潜力的评估.基于对该地区近15年的日平均风速的统计分析,计算了各月的风能密度,拟合出了Weibull分布密度函数的特征参数.用Weibull分布密度函数预测了各月的风能密度.并与实测值进行了对比及相关性分析,结果证明了Weibull函数对实测数据有很好的拟合性,同时也表明福建省陆地风力资源的不足,对该地区风力资源的调查重点应放在沿海滩涂及浅海.     

智利风能资源评估与开发前景分析

为方便我国风电设备制造商及发电企业参与智利风能资源开发,搜集气象观测和风电并网消纳相关资料,进行了智利风能评估与开发前景的分析。首先选取33个地面气象观测站点的典型年份,然后根据典型年气象数据评估了风能资源的地域分布;然后结合用电负荷、电网建设和已有电源情况,分析了各区域发展风力发电的并网与消纳条件,总结适合进行风电投资的目标区域。最后还分析了当地进行风电开发的扶持政策和制约因素,总结了我国能源企业赴智利开发风电的优势和适宜采用的方式。     

Assessment of solar and wind energy resources in Ethiopia. II. Wind energy

Using wind data from 21 meteorological stations with hourly or 3-hourly readings and 60 stations with monthly means, together with data from previous studies of neighbouring countries, a series of analyses were undertaken to illustrate the general availability of wind energy across Ethiopia. In order to calculate the wind energy density, firstly these 21 stations, along with 12 stations from neighbouring countries with hourly readings, were used to calculate the Weibull parameters, c and k. The Weibull distribution is shown to be a good approximation for the observed values in a majority of cases. Isopleths of the k values were then plotted, and from this the remaining 60 stations with monthly readings were then assigned k values. The wind energy density for each station was then calculated. Although the quantity of wind data is somewhat lacking, the results show that there is a potential for wind energy utilisation in some regions of Ethiopia.     

Wind power statistics and an evaluation of wind energy density

In this paper the statistical data of fifty days' wind speed measurements at the MERC-solar site are used to find out the wind energy density and other wind characteristics with the help of the Weibull probability distribution function. It is emphasized that the Weibull and Rayleigh probability functions are useful tools for wind energy density estimation but are not quite appropriate for properly fitting the actual wind data of low mean speed, short-time records. One has to use either the actual wind data (histogram) or look for a better fit by other models of the probability function.     

Compilation and evaluation of solar and wind energy resources in Sudan

A number of years worth of data concerning the solar radiation on a horizontal surface, sunshine duration and wind speed in Sudan have been compiled, evaluated and presented in this article.Measurements of global solar radiation on a horizontal surface at 16 stations for several years are compared with predictions made by several independent methods. In the first method the Angstrom formula was used to correlate relative global solar irradiance to the corresponding relative duration of bright sunshine.Regression coefficients are obtained and used for prediction of global solar irradiance. The predicted values were consistent with measured values (± 8.01% variation).In the second method, by Barbaro et al. [Solar Energy, 1978, 20, 431] sunshine duration and minimum air mass were used to drive an empirical correlation for the global radiation. The predicted values compared well with measured values (± 12% variation).The diffuse solar irradiance is estimated. The results of two formulas have close agreement. A radiation map of Sudan was prepared from the estimated radiation values. The annual daily mean global radiation ranges from 3.05 to 7.62 kW h m⁻² per day.Routine wind data from 70 stations were analyzed. Monthly averaged wind speed and average powers were determined for each station. The derived annual average speeds range from 1.53 to 5.07 m s⁻¹. Maximum extractable average wind powers were found to vary between 1.35 and 49.5 W m⁻². A wind map of Sudan was also prepared.Sudan possessed a relatively high abundance of sunshine and moderate wind speed. It is concluded that Sudan is blessed with abundant solar and wind energy.     

江苏淮北沿海风能资源分析

根据气象部门几十年观测的历史资料和响水县陈家港1年设点观测的完整资料分析:江苏淮北沿海盛行SE风和ESE风,风能密度最大方向为N向.10,40,60,70 m高度的年平均风速和年风功率密度分别为5.2 m/s和175 W/m2;6.3 m/s和271 W/m2;6.6 m/s和301 W/m2:6.8 m/s和323 W/m2.江苏淮北是风能可以利用地区之一.     

风 风能 风力发电——21世纪新型清洁能源

一风的一般属性１风的形成风是人们非常熟悉的一种自然现象，人人都能感觉到它的存在。春风和煦，给万物带来生机；夏风吹拂，使人心旷神怡；秋风送爽，带来丰收的喜悦；冬风呼啸，迎来漫天飞雪。那么风是怎样形成的呢？众所周知，人类生活的地球表面被大气所包围，来自太阳的辐射不断传送到地球表面，因太阳辐射受热情况不同，地球表面各处的气温不同。在影响气压高低的因素中，气温起着最重要的作用。温度高的地区空气受热上升，气压减小；温度低的地方，空气下降，气压增大，于是产生了气压差。和水往低处流一样，空气也从气压高处向气压…     

Wind energy resources in the Ionian Sea

The wind speed and direction as well as the availability, the duration and the diurnal variation of two offshore sites, Zakinthos and Pylos (BZK and BPY) in the Ionian Sea were assessed. For an analysis period of two years, the mean wind speed at 10 m was determined as 5.7 ± 0.1 m s^?1 and 5.8 ± 0.1 m s^?1 for the BZK and BPY sites, respectively. The wind speed variations over the hours of the day were quite small. The monthly variation in the average wind speeds was between 4.3 (May) and 7.5 m s^?1 (December) for the BZK site and 4.4 (August) and 7.3 m s^?1 (December) for the BPY site. Moreover, QuikSCAT satellite mean values for the grids of the two buoy regions were systematically overestimated in comparison to the buoy data with differences in the range from 8 to 13%. Statistical analysis revealed the high QuikSCAT data uncertainty for wind speeds less than 5 m s^?1 as the major factor of the observed mean value differences. The mean wind power densities were calculated with the buoy wind speed measurements and were found more than 250 W m^?2 at 10 m, suggesting the suitability of the sites for offshore wind energy applications. Capacity factors of up to 48% for energy production were calculated with the existing offshore turbines technology at a hub height of 100 m. Furthermore, the energy yield for different wind turbines and a service life of 20 years were determined from 6.5 to 8.7 and the energy pay-back periods from 2.8 to 2.1 years, respectively. The maximum avoided greenhouse emissions were 140 kt CO₂-e for an offshore turbine generator of 5 MW and a period of 20 years.     

Wind energy and assessment of wind energy potential in Turkey

In this study, the potential of wind energy and assessment of wind energy systems in Turkey were studied. The main purpose of this study is to investigate the wind energy potential and future wind conversion systems project in Turkey. The wind energy potential of various regions was investigated; and the exploitation of the wind energy in Turkey was discussed. Various regions were analyzed taking into account the wind data measured as hourly time series in the windy locations. The wind data used in this study were taken from Electrical Power Resources Survey and Development Administration (EIEI) for the year 2010. This paper reviews the assessment of wind energy in Turkey as of the end of May 2010 including wind energy applications. Turkey's total theoretically available potential for wind power is around 131,756.40 MW and sea wind power 17,393.20 MW annually, according to TUREB (TWEA). When Turkey has 1.5 MW nominal installed wind energy capacity in 1998, then this capacity has increased to 1522.20 MW in 2010. Wind power plant with a total capacity of 1522.20 MW will be commissioned 2166.65 MW in December 2011.     

山西风能资源及风电发展综述

依据山西省风能资源评价和风电规划,介绍了山西省的风能资源、风电规划、风电发展状况,提出了山西发展风电产业的建议。     

Wind energy resources on Phuquoc Island,Vietnam

This study analyzes the wind energy resources on Phuquoc Island, Vietnam. Daily wind data are collected from 2005 to 2011 in this study. The annual mean speed and power density are 6 m/s and 355 W/m², respectively. Results show that more than 35% of the wind energy comes from the northwest. In this study, a 75 MW wind farm with 25 wind turbines is simulated by using the WAsP 10 program. The wind farm can produce over 189.636 GWh annually. In addition, the effects of wind disturbance and three-phase short circuit of the grid are analyzed using the ETAP 7.0 program.     

Wind characteristics and wind energy potential in Morocco

The wind characteristics of 11 sites in the windy regions in Morocco have been analysed. The annual average wind speed for the considered sites ranged from 5 m/s to 10 m/s and the average power density from 100 W/m² to 1000 W/m², which might be suitable for electrical power production by installing wind farms. On an annual scale the observations of the distribution of hourly wind speed are better fitted by the Weibull hybrid distribution in contrast to the Weibull distribution.The wind power is estimated to be 1817 MW, that is to say, the exploitable wind energy is 15198 GWh, which represents theoretically 11% of the total consumed energy in Morocco in 1994.