欧洲风电发展现状（二）

欧洲依然是全球风电发展的主要市场。2004年以来，世界风电产业加速发展，特别是美国、印度和中国，但是，欧洲仍然是世界上主要的风电市场和设备供应商。2006年全球风电装机容量达到了74GW，其中欧盟25国总量为48．55GW，占65％。在全球风电制造业中，欧洲企业占据主导地住，在2006年全球已安装的风机中，欧洲企业生产的产品份额占85％。     

欧盟风电产业的发展及对我国的启示

欧洲风电发展取得了很大的成就,建立了世界最大的风电市场和产业,制定和实施了有效的支持政策,促进了风电技术的迅速发展和成本的持续下降,风电开始在欧洲成为主要的替代能源.文章介绍了欧洲风电技术、产业和市场发展状况及趋势;实施强制上网、价格激励、税收优惠、资源普查、电网建设等政策的经验,提出了我国具有世界最重要的风电潜在市场,应该借鉴欧洲经验,加快在完善价格体系、风机标准化和检测、资源普查、电网建设等方面的工作步伐,支持我国风电产业的发展.     

美国风电发展面临四大挑战

美国是世界上的风电发展大国。2012年6月,美国风电累计装机容量超过5000万千瓦,全国约2.9%的电力来自于风电。美国还制定了一项更宏伟的目标,即到2030年,能源消费总量中将有20%来自风电。这意味着美国风电的发展将继续高歌猛进。但事实上,这几年美国的风电产业并不如意。2010年和2011年美国年均新增风电装机量较2009年下降30%以上。未来,面临不确定的补贴政策、持续低廉的天然气价格、地域劣势以及民众的抗议,美国风电发展面临着众多挑战。不确定的补贴政策美国的风电产业是在税收减免政策的扶持下成长的。     

美国大力支持浮式海上风电发展

正作为未来海上风电发展的重要方向,漂浮式风电技术得到越来越多的关注。在国际能源署最近发布的《2019年海上风能展望》报告中指出,浮式风电可能会改变未来海上风电市场,世界上一些最大的经济体将来可能完全依靠浮式风电场来提供电力。美国和英国正在通过国家层面支持该领域的创新,以期引领未来海上风电发展。     

美国风电市场投资模式

美国是世界最主要的风电市场之一,也是中国重要的投资地,投资美国风电行业如何才能减少损失,规避风险？     

风电产业发展年度报告

2010年对于我国风电产业而言,是极具里程碑意义的一年:作为"十一五"的最后一年,经过近五年时间的大发展,我国风电装机在"十二五"到来之前终于超过美国跃居世界第一;我国风电技术进入了国际先进行列,各类型风机均可实现国产化,大容量机组相继出现;风电产业高度市场化,国有、民营、外资企业共同发展,独资、合资多种     

快速前进中的中国风电

中国风电产业自从2005年开始进入快速增长期,在连续五年装机容量翻番后,2010年中国年装机达到了1900万千瓦以上。这一成绩使得中国成为全球风电新增市场和累计市场的第一名。2010年当年,中国贡献了全球超过一半的新增装机容量。美国风电市场受累于金融危机和页岩天然气市场的双重影响,进展减缓。而中国当之无愧地成为拉动全球风电市场的核心动力。     

海上风电发展迅速

<正>截至2016年底,英国是世界上最大的海上风电市场,装机占全球的近36%;其次是德国,占29%;我国海上风电装机占全球的11%,位居第三;丹麦占8.8%,荷兰占7.8%,比利时占5%,瑞典占1.4%;此外,还有芬兰、爱尔兰、西班牙、日本、韩国、美国和挪威等市场。估计到2018年,全球新增3.9GW海上风电并网容量。2009年,我国东海大桥海上示范风电场建成     

风电成长的烦恼

对风电企业来说,2011年或许是变数最为诡异的一年。仅2011年上半年,中国新增风电装机容量已超过600万千瓦,继续巩固世界最大风电市场的位置。据国家发改委能源研究所与国际能源署（IEA）联合发布的《中国风电发展路线图2050》,到2020年,陆地风电的成本将与煤电持平,这之后,风电将逐步脱离国家补贴.     

2013全球风电统计

正全球风能理事会(GWEC)近期发布了2013全球风电发展统计数据,全球风电累计装机容量达到31813.7万千瓦,在过去五年(2009年—2013年),全球风电市场规模几乎增长了2亿千瓦。然而,2013年新增风电装机3546.7万千瓦,比2012年的增量下降了约1000万千瓦。导致2013年新增容量下降的主要原因是美国PTC政策(风电税额抵免政策)在2012年底中断。对于整个产业12.5%的累积增长率,2013年又是一个风电发展的艰难年份,     

风电场风电机组的接地设计

较系统地介绍了风电场风电机组对接地电阻的要求、接地设计思路及方法,并提供实际工程中接地网布置图实例作为参考。     

Evaluation of wind farm efficiency and wind turbine wakes at the Nysted offshore wind farm

Here, we quantify relationships between wind farm efficiency and wind speed, direction, turbulence and atmospheric stability using power output from the large offshore wind farm at Nysted in Denmark. Wake losses are, as expected, most strongly related to wind speed variations through the turbine thrust coefficient; with direction, atmospheric stability and turbulence as important second order effects. While the wind farm efficiency is highly dependent on the distribution of wind speeds and wind direction, it is shown that the impact of turbine spacing on wake losses and turbine efficiency can be quantified, albeit with relatively large uncertainty due to stochastic effects in the data. There is evidence of the ‘deep array effect’ in that wake losses in the centre of the wind farm are under‐estimated by the wind farm model WAsP, although overall efficiency of the wind farm is well predicted due to compensating edge effects. Copyright © 2010 John Wiley & Sons, Ltd.     

分散式风力发电机组的电压控制

风电的分散式开发不同于大规模开发和分布式开发,由于分散风电靠近负荷中心,直接接入配电网,且不加装无功补偿调节装置SVC,配网中较大的电压波动给分散风电的并网运行带来影响。文章讨论了配网对分散风电的电压控制特点和要求,结合风电机组无功控制能力,并推导出满足配网电压调节要求的风电机组无功控制范围和对机组设备的要求。     

适用于特殊风区的风电机组塔架的再设计

由于IECⅠ级机型性能不能满足超Ⅰ类风区的要求,因此以IECⅠ级机型塔架的结构为基础,对其进行了再设计,并利用有限元方法,对再设计后的塔架的静强度、模态、稳定性进行了分析。分析结果表明:再设计后的塔架的强度、固有频率和刚度均满足要求;以满足强度、频率特性和刚度为约束条件,以减轻重量、降低成本为目标的塔架的再设计是可靠的。     

某风电场风力发电机组故障诊断

为了准确判断风电机组的运行状态及故障,提出了基于常规分析—振动幅值分析—波形频谱分析的故障诊断流程,阐述了针对风电机组的幅值分析方法和波形频谱分析方法,并通过对某机组异响的根源探究实例,准确地诊断出机组异响来源于齿轮箱太阳轮,可为风电机组故障诊断技术提供依据。     

Simulation of hourly wind speed and array wind power

Statistical summaries of wind speed are sufficient to compute many characteristics of turbine-generated power, such as the mean, variance and reliability of various power levels. However, a wind speed time series is necessary to produce a sequence of power values as used for investigating load matching and storage requirements. Since a long historical record of wind speed may not be available at a wind turbine candidate site, it is desirable to be able to generate a simulated numerical sequence of hourly wind speed values. Two such approximate procedures are developed in this paper. One procedure generates sequential wind speed values at a site based on the Weibull parameters of hourly wind speed and the lag-one autocorrelation of hourly wind speed values. Comparison with historical data at a site is made. The second procedure generates sequential hourly wind power values for a regional array of wind turbines. It utilizes the typical site wind characteristics, the spatial and lag-one cross correlation and autocorrelation of hourly wind speed values and an equivalent linearized relationship between array average wind speed and array power. Comparison with results for six different wind turbines in three different regional arrays indicates good agreement for wind power histograms, autocorrelation function and mean persistence.     

Characterization of wind speed data according to wind direction

Knowledge of the wind speed distribution and the most frequent wind directions is important when choosing wind turbines and when locating them. For this reason wind evaluation and characterization are important when forecasting output power. The data used here were collected from eleven meteorological stations distributed in Navarre, Spain. We obtained data for the period extending from 1992 to 1995, with each datum encompassing 10 minutes of time. Wind speed data of each station were gathered in eight directional sectors, each one extended over 45 degrees according to the direction from which the wind blows. The stations were grouped in two blocks: those under the influence of the Ebro valley and those in mountainous areas. For each group the Weibull parameters were estimated, (according to the Weibull probability paper because the Weibull distribution gives the best fit in this region). Kurtosis and skewness coefficients were estimated as well. The Weibull parameters, especially the scale parameter c, depend strongly on the direction considered, and both Weibull parameters show an increasing trend as the direction considered moves to the more dominant direction, while both kurtosis and skewness show a corresponding decreasing trend.     

Assessment of wind characteristics and wind turbine characteristics in Taiwan

Wind characteristics and wind turbine characteristics in Taiwan have been thoughtfully analyzed based on a long-term measured data source (1961–1999) of hourly mean wind speed at 25 meteorological stations across Taiwan. A two-stage procedure for estimating wind resource is proposed. The yearly wind speed distribution and wind power density for the entire Taiwan is firstly evaluated to provide annually spatial mean information of wind energy potential. A mathematical formulation using a two-parameter Weibull wind speed distribution is further established to estimate the wind energy generated by an ideal turbine and the monthly actual wind energy generated by a wind turbine operated at cubic relation of power between cut-in and rated wind speed and constant power between rated and cut-out wind speed. Three types of wind turbine characteristics (the availability factor, the capacity factor and the wind turbine efficiency) are emphasized. The monthly wind characteristics and monthly wind turbine characteristics for four meteorological stations with high winds are investigated and compared with each other as well. The results show the general availability of wind energy potential across Taiwan.     

Dynamic models of wind farms with fixed speed wind turbines

The increasing wind power penetration on power systems requires the development of adequate wind farms models for representing the dynamic behaviour of wind farms on power systems. The behaviour of a wind farm can be represented by a detailed model including the modelling of all wind turbines and the wind farm electrical network. But this detailed model presents a high order model if a wind farm with high number of wind turbines is modelled and therefore the simulation time is long. The development of equivalent wind farm models enables the model order and the computation time to be reduced when the impact of wind farms on power systems is studied. In this paper, equivalent models of wind farms with fixed speed wind turbines are proposed by aggregating wind turbines into an equivalent wind turbine that operates on an equivalent wind farm electrical network. Two equivalent wind turbines have been developed: one for aggregated wind turbines with similar winds, and another for aggregated wind turbines under any incoming wind, even with different incoming winds.The proposed equivalent models provide high accuracy for representing the dynamic response of wind farm on power system simulations with an important reduction of model order and simulation time compare to that of the complete wind farm modelled by the detailed model.     

Design of wind farm layout for maximum wind energy capture

Wind is one of the most promising sources of alternative energy. The construction of wind farms is destined to grow in the U.S., possibly twenty-fold by the year 2030. To maximize the wind energy capture, this paper presents a model for wind turbine placement based on the wind distribution. The model considers wake loss, which can be calculated based on wind turbine locations, and wind direction. Since the turbine layout design is a constrained optimization problem, for ease of solving it, the constraints are transformed into a second objective function. Then a multi-objective evolutionary strategy algorithm is developed to solve the transformed bi-criteria optimization problem, which maximizes the expected energy output, as well as minimizes the constraint violations. The presented model is illustrated with examples as well as an industrial application.