Projected near-surface wind speed and wind energy over Central Asia using dynamical downscaling with bias-corrected global climate models

Wind energy development in Central Asia can help alleviate drought and fragile ecosystems.Nevertheless,current studies mainly used the global climate models(GCMs)to project wind speed and energy.The simulated biases in GCMs remain prominent,which induce a large uncertainty in the projected results.To reduce the uncertainties of projected near-surface wind speed(NSW)and better serve the wind energy development in Central Asia,the Weather Research and Forecasting(WRF)model with bias-corrected GCMs was employed.Compared with the outputs of GCMs,dynamical downscaling acquired using the WRF model can better capture the high-and low-value centres of NSWS,especially those of Central Asia's mountains.Meanwhile,the simulated NSWS bias was also reduced.For future changes in wind speed and wind energy,under the Representative Concentration Pathway 4.5(RCP4.5)scenario,NSWS during 2031-2050 is projected to decrease compared with that in 19862005.The magnitude of NSwS reduction during 2031-2050 willreach 0.1 m s^(-1).and the maximum reduction is projected to occur over the central and western regions(>0.2 m s^(-1)).Furthermore,future wind power density(WPD)can reveal nonstationarity and strong volatility,although a downward trend is expected during 2031-2050.In addition,the higher frequency of wind speeds at the turbine hub height exceeding 3.0 m s^(-1)can render the plain regions more suitable for wind energy development than the mountains from 2031 to 2050.This study can serve as a guide in gaining insights into future changes in wind energy across Central Asia and provide a scientific basis for decision makers in the formulation of policies for addressing climate change.

A Statistical Analysis of Wind Speed and Power Density Based on Weibull and Rayleigh Models of Jumla, Nepal

In the present study, wind speed data of Jumla, Nepal have been statistically analyzed. For this purpose, the daily averaged wind speed data for 10 year period (2004-2014: 2012 excluded) provided by Department of Hydrology and Meteorology (DHM) was analyzed to estimate wind power density. Wind speed as high as 18 m/s was recorded at height of 10 m. Annual mean wind speed was ascertained to be decreasing from 7.35 m/s in 2004 to 5.13 m/s in 2014 as a consequence of Global Climate Change. This is a subject of concern looking at government’s plan to harness wind energy. Monthly wind speed plot shows that the fastest wind speed is generally in month of June (Monsoon Season) and slowest in December/January (Winter Season). Results presented Weibull distribution to fit measured probability distribution better than the Rayleigh distribution for whole years in High altitude region of Nepal. Average value of wind power density based on mean and root mean cube seed approaches were 131.31 W/m2/year and 184.93 W/m2/year respectively indicating that Jumla stands in class III. Weibull distribution shows a good approximation for estimation of power density with maximum error of 3.68% when root mean cube speed is taken as reference.

Probability distribution of wind power volatility based on the moving average method and improved nonparametric kernel density estimation

In the process of large-scale,grid-connected wind power operations,it is important to establish an accurate probability distribution model for wind farm fluctuations.In this study,a wind power fluctuation modeling method is proposed based on the method of moving average and adaptive nonparametric kernel density estimation(NPKDE)method.Firstly,the method of moving average is used to reduce the fluctuation of the sampling wind power component,and the probability characteristics of the modeling are then determined based on the NPKDE.Secondly,the model is improved adaptively,and is then solved by using constraint-order optimization.The simulation results show that this method has a better accuracy and applicability compared with the modeling method based on traditional parameter estimation,and solves the local adaptation problem of traditional NPKDE.

Near-Surface Wind-Speed Stilling in Alaska during 1984-2016 and Its Impact on the Sustainability of Wind Power

Based on wind-speed records of Alaska’s 19 first-order weather stations, we analyzed the near-surface wind-speed stilling for January 1, 1984 to December 31, 2016. With exception of Big Delta that indicates an increase of 0.0157 m·s–1·a–1, on average, all other first-order weather stations show declining trends in the near-surface wind speeds. In most cases, the average trends are less then?–0.0300?m·s–1·a–1. The strongest average trend of?–0.0500?m·s–1·a–1 occurred at Homer, followed by?–0.0492?m·s–1·a–1 at Bettles, and?–0.0453?m·s–1·a–1 at Yakutat, while the declining trend at Barrow is marginal. The impact of the near-surface wind-speed stilling on the wind-power potential expressed by the wind-power density was predicted and compared with the wind-power classification of the National Renewable Energy Laboratory and the Alaska Energy Authority. This wind-power potential is, however, of subordinate importance because wind turbines only extract a fraction of the kinetic energy from the wind field characterized by the power efficiency. Since wind turbine technology has notably improved during the past 35 years, we hypothetically used seven currently available wind turbines of different rated power and three different shear exponents to assess the wind-power sustainability under changing wind regimes. The shear exponents 1/10, 1/7, and 1/5 served to examine the range of wind power for various conditions of thermal stratification. Based on our analysis for January 1, 1984 to December 31, 2016, Cold Bay, St. Paul Island, Kotzebue, and Bethel would be very good candidates for wind farms. To quantify the impact of a changing wind regime on wind-power sustainability, we predicted wind power for the periods January 1, 1984 to December 31, 1994 and January 1, 2006 to December 31, 2016 as well. Besides Big Delta that suggests an increase in wind power of up to 12% for 1/7, predicted wind power decreased at all sites with the highest decline at Annette (≈38%), Kodiak (≈30%), King Salmon (≈26%), and Kotzebue (≈24%), where the effect of the shear exponents was marginal. Bethel (up to 20%) and Cold Bay (up to 14%) also show remarkable decreases in predicted wind power.

Investigations into Some Simple Expressions of the Gamma Function in Wind Power Theoretical Estimate by the Weibull Distribution

The Weibull distribution is a probability density function (PDF) which is widely used in the study of meteorological data. The statistical analysis of the wind speed v by using the Weibull distribution leads to the estimate of the mean wind speed , the variance of v around and the mean power density in the wind. The gamma function Γ is involved in those calculations, particularly Γ (1+1/k), Γ (1+2/k) and Γ (1+3/k). The paper reports the use of the Weibull PDF f(v) to estimate the gamma function. The study was performed by looking for the wind speeds related to the maximum values of f(v), v2 f(v) and v3 f(v). As a result, some approximate relationships were obtained for Γ (1+1/k), Γ (1+2/k) and Γ (1+3/k), that use some fitting polynomial functions. Very good agreements were found between the exact and the estimated values of Γ (1+n/k) that can be used for the estimation of the mean wind speed , the variance σ2 of the wind speed v;around the mean speed and the average wind power density.

新疆达坂城风区顺风向脉动风功率谱

为研究新疆乌鲁木齐所处达坂城风区的复杂脉动风环境,基于实测风场风速数据分析并拟合了该风区的顺风向脉动风功率谱。结果表明:以反比例函数拟合山区峡谷地形平均风速与湍流强度的关系误差较小;山区峡谷地形湍流积分尺度分布较离散,但整体随平均风速的增大而增大;考虑地形系数的Kaimal修正谱在含能区和惯性子区间能较好地表征实测谱,在耗能区选用三参数拟合描述实测谱效果良好;选用过渡函数来描述惯性子区间与耗能区接触区域的功率谱,拟合效果较为理想。可见达坂城风区具有特殊顺风向脉动风特性,以修正谱和拟合谱分段构成的函数模型可用于表征该风区顺风向脉动风功率谱。

随机脉动风场作用下输电塔线体系的动力响应分析

输电杆塔及塔线体系(简称塔线体系)是整个电力系统中输电环节的核心部分,沿海地区的强风对塔线体系有着重要影响。为研究在随机脉动风场作用下塔线体系的动力响应特性,文中以广东某地区的1W2C9型鼓型自立式输电杆塔为研究对象,建立输电杆塔的单塔及一塔两线的塔线耦联有限元模型,结合Davenport风速谱与四阶自回归法模拟具有空间相关性的单塔9节点及塔线体系49节点的脉动风场,研究在此脉动风场下的单塔及塔线体系的动力响应,并探究不同风向角对其动力响应的影响。研究结果表明:单塔及塔线体系的动力响应最大值大于其拟静力响应;由于塔线耦联效应的存在,输电线会增加塔线体系的稳定性,降低其动力响应;90°是输电杆塔单塔及塔线体系动力响应的最不利风向角。

Analysis of offshore wind energy resources of China

With the economic development, the problems of energy shortage become increasingly severe. As offshore wind energy has advantages, namely it is clean, renewable, not accounting for land area, without noise pollution, with large reserves, etc., which gradually attracts people＇s attention. In this paper, China＇s offshore annual average wind field and monthly average wind field under the mean climate state conditions are obtained, and the corresponding wind density distribution is calculated. China＇s offshore wind energy reserves and distribution conditions through the analysis of wind energy density distribution are summarized, and finally some suggestions for coastal offshore wind energy development and utilization in China are put forward.

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/m^(2),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。

基于改进LSTM神经网络的风电功率短期预报算法

[目的]风能的波动性和间歇性给大规模的风电并网提出了挑战,解决这一问题的有效途径是能够提供准确的风电功率预报。[方法]针对这一挑战,提出了一种新的基于改进LSTM(长短期记忆)架构的深度学习神经网络的风功率预报模型,包含自主研制的数据异常检测与处理、风速特征提取、超参数调优于一体的风电功率预报方法。为了使神经网络模型能更加准确地学习风速特征对风电功率的影响,还定义了一种使用特征筛选以及特征倍增相结合的特征工程方法。[结果]仿真结果表明:所提出的数据清洗及数据增强算法在各种机器学习算法上可以将准确率提升约5%。提出的改进LSTM神经网络模型在数据清洗后与传统算法以及业内主流神经网络算法进行对比,可以将准确率提升2.5%。[结论]改进的方法不但具有较好的噪声数据清洗能力,而且在所有的试验中,改进模型在预报准确性方面优于其他所有算法,可以为实际应用提供指导。

高速高功率密度无轴承永磁薄片电机设计与优化

传统无轴承电机在高速和高功率密度之间难以取得平衡,为此围绕高速高功率密度无轴承永磁薄片电机,对其拓扑结构、绕组形式、主要尺寸等方面进行优化设计,在保证转速和功率密度的基础上有效地提升悬浮性能。通过对运行工况的分析,得出电机拓扑结构需具备的基本特点,提出一种采用环形集成绕组的表贴式无轴承永磁薄片电机。在兼顾转矩和悬浮力输出性能、机械防护可靠性的基础上,对电机的电磁气隙长度和永磁体参数等主要尺寸进行优化设计。针对电机饱和、绕组端部伸出等不利因素,分别采取了超前角弱磁、定子略长的性能提升策略,有效地避免了悬浮力的大幅度跌落。搭建20 000 r/min的无轴承永磁薄片电机有限元仿真模型并制造实物样机。通过对电磁转矩和主、被动悬浮力的分析,证明了本文设计的无轴承永磁薄片电机兼具良好的转矩与悬浮力输出性能,单位幅值电流产生的电磁转矩、主动悬浮力分别为0.166 N·m、4.4 N,电机输出功率10 kW、功率密度5.2 kW/kg。

Investigating the impacts of spatial-temporal variation features of air density on assessing wind power generation and its fluctuation in China

Air density plays an important role in assessing wind resource.Air density significantly fluctuates both spatially and temporally.But literature typically used standard air density or local annual average air density to assess wind resource.The present study investigates the estimation errors of the potential and fluctuation of wind resource caused by neglecting the spatial-temporal variation features of air density in China.The air density at 100 m height is accurately calculated by using air temperature,pressure,and humidity.The spatial-temporal variation features of air density are firstly analyzed.Then the wind power generation is modeled based on a 1.5 MW wind turbine model by using the actual air density,standard air densityρst,and local annual average air densityρsite,respectively.Usingρstoverestimates the annual wind energy production(AEP)in 93.6%of the study area.Humidity significantly affects AEP in central and southern China areas.In more than 75%of the study area,the winter to summer differences in AEP are underestimated,but the intra-day peak-valley differences and fluctuation rate of wind power are overestimated.Usingρsitesignificantly reduces the estimation error in AEP.But AEP is still overestimated(0-8.6%)in summer and underestimated(0-11.2%)in winter.Except for southwest China,it is hard to reduce the estimation errors of winter to summer differences in AEP by usingρsite.Usingρsitedistinctly reduces the estimation errors of intra-day peak-valley differences and fluctuation rate of wind power,but these estimation errors cannot be ignored as well.The impacts of air density on assessing wind resource are almost independent of the wind turbine types.

考虑风向相关性的风电机组山地湍流风场模拟研究

为了更加准确地进行风电机组结构时程响应计算,考虑风剪切、塔影和山地环境等对平均风速的影响,文章基于Kaimal自功率谱和纵向与竖向脉动风速分量互功率谱,采用谐波叠加法通过湍流相干模型建立空间三维且具备风向相关性的非平稳风场。选取某风电场2 MW风电机组为例进行实例分析,对模拟方法进行验证,并与不考虑风向相关性进行对比。模拟结果表明,风速时程数据特征符合预期,得到的模拟功率谱与目标谱吻合较好,考虑风向相关性可提高模拟吻合度。从而证明了模拟方法的准确性和必要性,实现了三维非平稳脉动风场的模拟。

基于混合自适应核密度估计的风电波动特性分析

分析掌握风电出力波动特性的内在规律有利于提高风电出力的预测精度,进而指导电网调度部门合理安排发电计划,提高系统运行的经济性。为描述风电出力波动的概率密度分布特性,文章首先分别修正由经验法及无偏交叉验证法得到的固定带宽,建立两种自适应带宽核密度估计模型;然后,将上述两种模型进行组合优化;最后,建立基于混合自适应核密度估计(HAKDE)的风电出力波动量概率密度分布模型。采用多种概率密度分布模型对华北某省风电场的不同时空尺度下的风电出力波动量进行拟合,算例结果表明,HAKDE模型的拟合效果最优,从而验证了HAKDE模型的有效性。

更快速度下周期性短波不平顺引起的轮轨高频振动特性及控制限值

随着列车运行速度的不断加快,轮轨高频振动引起的车辆、轨道部件伤损问题更加突出,尤以周期性的短波不平顺最为常见。为了掌握轮轨高频振动自下而上的传递衰减规律以及制定合理的钢轨打磨策略,有必要针对车辆系统在高频激励条件下的耦合振动特性开展深入的理论研究。本文通过对大量实测数据的拟合,得到了更宽频段范围内的轨道高低不平顺谱拟合公式,并通过反演得到了0.002~100 m波长范围内的高低不平顺样本;在此基础上建立了高速动车组-轨道刚柔耦合动力学模型,其中对轮对、钢轨均考虑了弹性体振动模态,仿真分析了周期性短波不平顺引起的轮轨高频振动特性。结果表明,车辆各部件的振动频率分布范围为30~1390 Hz,且自下至上呈逐层衰减趋势。通过提取周期性短波不平顺幅值变化对轮轨相互作用的影响规律,进一步提出了适应400 km/h高速铁路的典型波长周期性短波不平顺的量化控制限值要求。

风洞试验流场特性的模拟及分析

建筑围护结构相对于主体结构在风荷载作用下更易发生破坏,因此研究建筑周围流场对于结构抗风至关重要。通过组合不同形状、尺寸的流场试验装置研究流场分布特性,根据不同工况组合模拟出相同地貌下不同湍流度分布可控的流场,以及同一地貌下3种不同缩尺比在参考高度处流场分布特性一致的流场,为开展建筑围护结构表面风压分布特征及抗风措施研究奠定了可靠的基础。

Short-term local prediction of wind speed and wind power based on singular spectrum analysis and locality-sensitive hashing

With the growing penetration of wind power in power systems, more accurate prediction of wind speed and wind power is required for real-time scheduling and operation. In this paper, a novel forecast model for shortterm prediction of wind speed and wind power is proposed,which is based on singular spectrum analysis(SSA) and locality-sensitive hashing(LSH). To deal with the impact of high volatility of the original time series, SSA is applied to decompose it into two components: the mean trend,which represents the mean tendency of the original time series, and the fluctuation component, which reveals the stochastic characteristics. Both components are reconstructed in a phase space to obtain mean trend segments and fluctuation component segments. After that, LSH is utilized to select similar segments of the mean trend segments, which are then employed in local forecasting, so that the accuracy and efficiency of prediction can be enhanced. Finally, support vector regression is adopted forprediction, where the training input is the synthesis of the similar mean trend segments and the corresponding fluctuation component segments. Simulation studies are conducted on wind speed and wind power time series from four databases, and the final results demonstrate that the proposed model is more accurate and stable in comparison with other models.

Wind Power Fluctuation Compensation by Variable Speed Pumped Storage Plants in Grid Integrated System:Frequency Spectrum Analysis

Electrical power generation from wind technology is the most rapidly growing technology due to its ample characteristics.Nevertheless,because of its stochastic feature,it has the unnecessary impact on the operations and stability of the power grid system.The fluctuation of the grid frequency problem,for example,is more pronounced.The fluctuation of the frequency in turn impacts even the collapse of the power system.To minimize such problems,a droop-vector control strategy applied on a doubly-fed induction machine based(DFIM)variable speed pumped storage(VSPS)system is proposed in this paper.This method is should be used as a wind power fluctuation compensation solution in the wind farm-grid integration system.The system model is made on the basis of the technique called a phasor model.The frequency spectrum analysis approach is used in the VSPS plant for determining the dynamic performances of the grid in case of contingencies including wind power fluctuation compensation.The software platform MATLAB/Simulink is used for verifying the performance of the proposed system.The results show that the method of the frequency spectrum analysis technique is effective for determining the wind power fluctuation and stability requirements in large power networks.The control strategy proposed in this paper implementing the VSC-DFIM based VSPS plant integrated with the power gird and wind farm network achieves a well-controlled power flow and stable grid frequency with the deviations being in acceptable ranges.

Analysis of vibration and frequency transmission of high speed EMU with flexible model

When the operation speed of the high-speed train increases and the weight of the carbody becomes lighter,not only does the sensitivity of the wheel/rail contact get higher,but also the vibration frequency range of the vehicle system gets enlarged and more frequencies are transmitted from the wheelset to the carbody.It is important to investigate the vibration characteristics and the dynamic frequency transmission from the wheel/rail interface to the carbody of the high-speed electric multi-uint（EMU）.An elastic highspeed vehicle dynamics model is established in which the carbody,bogieframes,and wheelsets are all dealt with as flexible body.A rigid high-speed vehicle dynamics model is set up to compare with the simulation results of the elastic model.In the rigid vehicle model,the carbody,bogieframes and wheelsets are treated as rigid component while the suspension and structure parameters are the same as used in the elastic model.The dynamic characteristic of the elastic high speed vehicle is investigated in time and frequency domains and the di ff erence of the acceleration,frequency distribution and transmission of the two types of models are presented.The results show that the spectrum power density of the vehicle decreases from the wheelset to the carbody and the acceleration transmission ratio is approximately from 1%to 10%for each suspension system.The frequency of the wheelset rotation is evident in the vibration of the flexible model and is transmitted from the wheelset to the bogieframe and to thecarbody.The results of the flexible model are more reasonable than that of the rigid model.A field test data of the high speed train are presented to verify the simulation results.It shows that the simulation results are coincident with the field test data.

Analysis and Assessment of Wind Energy Potential of Almukalla in Yemen

Energy is an essential element for any civilized country’s social and economic development,but the use of fossil fuels and nonrenewable energy forms has many negative impacts on the environment and the ecosystem.The Republic of Yemen has very good potential to use renewable energy.Unfortunately,we find few studies on renewable wind energy in Yemen.Given the lack of a similar analysis for the coastal city,this research newly investigates wind energy’s potential near the Almukalla area by analyzing wind characteristics.Thus,evaluation,model identification,determination of available energy density,computing the capacity factors for several wind turbines and calculation of wind energy were extracted at three heights of 15,30,and 50meters.Average wind speeds were obtained only for the currently available data of five recent years,2005–2009.This study involves a preliminary assessment of Almukalla’s wind energy potential to provide a primary base and useful insights for wind engineers and experts.This research aims to provide useful assessment of the potential of wind energy in Almukalla for developing wind energy and an efficient wind approach.The Weibull distribution shows a perfect approximation for estimating the intensity of Yemen’s wind energy.Depending on both theWeibullmodel and the results of the annual wind speed data analysis for the study site in Mukalla,the capacity factor for many turbines was also calculated,and the best suitable turbine was selected.According to the International Wind Energy Rating criteria,Almukalla falls under Category 7,which is,rated“Superb”most of the year.