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1.
Accurate and reliable assessment of wind energy potential has important implication to the wind energy industry. Most previous studies on wind energy assessment focused solely on wind speed, whereas the dependence of wind energy on wind direction was much less considered and documented. In this paper, a copula-based method is proposed to better characterize the direction-related wind energy potential at six typical sites in Hong Kong. The joint probability density function (JPDF) of wind speed and wind direction is constructed by a series of copula models. It shows that Frank copula has the best performance to fit the JPDF at hilltop and offshore sites while Gumbel copula outperforms other models at urban sites. The derived JPDFs are applied to estimate the direction-related wind power density at the considered sites. The obtained maximum direction-related wind energy density varies from 41.3 W/m2 at an urban site to 507.9 W/m2 at a hilltop site. These outcomes are expected to facilitate accurate micro-site selection of wind turbines, thereby improving the economic benefits of wind farms in Hong Kong. Meanwhile, the developed copula-based method provides useful references for further investigations regarding direction-related wind energy assessments at various terrain regions. Notably, the proposed copula-based method can also be applied to characterize the direction-related wind energy potential somewhere other than Hong Kong. 相似文献
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Fredrik Raak Yoshihiko Susuki Kazuhisa Tsuboki Masaya Kato Shinya Eguchi Takashi Hikihara 《风能》2018,21(7):531-543
Wind conditions and output power characteristics of a wind farm in Japan are evaluated with highly resolved weather predictions from the so‐called cloud resolving storm simulator. One year of 30‐hour‐ahead predictions with 2‐km spatial resolution and 1‐hour time resolution are evaluated against 10‐minute averaged measurements (averaged to hourly data) from the wind farm. Also, extremely detailed shorter‐term predictions with 200‐m spatial resolution and 1‐second time resolution are evaluated against 1‐Hz measurements. For the hourly data, wind speeds are predicted with an RMSE of 3.0 to 3.5 m/s, and wind power with about 0.3 per unit. Wind direction is predicted with a standard deviation of errors of 16° to 28° for hourly data, and generally below 10° for the 1‐Hz data. We show that wind power variability—here in terms of increments—can be assessed on the timescale of several hours. The measured and predicted wind spectra are found similar on both short and long timescales. 相似文献
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Three functions have so far predominantly been used for fitting the measured wind speed probability distribution in a given location over a certain period of time, typically monthly or yearly. In the literature, it is common to fit these functions to compare which one fits the measured distribution best in a particular location. During this comparison process, parameters on which the suitability of the fit is judged are required. The parameters that are mostly used are the mean wind speed or the total wind energy output (primary parameters). It is, however, shown in the present study that one cannot judge the suitability of the functions based on the primary parameters alone. Additional parameters (secondary parameters) that complete the primary parameters are required to have a complete assessment of the fit, such as the discrepancy between the measured and fitted distributions, both for the wind speed and wind energy (that is the standard deviation of wind speed and wind energy distributions). Therefore, the secondary statistical parameters have to be known as well as the primary ones to make a judgement about the suitability of the distribution functions analysed. The primary and secondary parameters are calculated from the 12-month of measured hourly wind speed data and detailed analyses of wind speed distributions are undertaken in the present article. 相似文献
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M. A. SALAM M. G. YAZDANI Q. M. RAHMAN Dk NURUL S. F. MEI Syeed HASAN 《Frontiers in Energy》2019,13(4):731
Conventional power generation mainly depends on natural gas and diesel oil in Brunei Darussalam. The power utility company is now thinking of power generation using natural wind. In this paper, wind energy, being one of the most readily available renewable energy sources, was studied. The wind characteristic, velocity and directions were studied using Weibull distribution based on the measurement of wind speed at two different locations in Brunei Darussalam. These wind speed distributions were modeled using the Wind Power program. The wind rose graph was obtained for the wind direction to analyze the wind power density onshore and offshore. Based on this analysis, it has been found that the wind speed of 3 to 5 m/s has a probability of occurrence of 40%. Besides, the annual energy production at a wind speed of 5 m/s has been found to be in the range between 1000 and 1500 kWh for both the locations in Brunei Darussalam. 相似文献
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The current IEC standard for wind turbine power performance measurement only requires measurement of the wind speed at hub height assuming this wind speed to be representative for the whole rotor swept area. However, the power output of a wind turbine depends on the kinetic energy flux, which itself depends on the wind speed profile, especially for large turbines. Therefore, it is important to characterize the wind profile in front of the turbine, and this should be preferably achieved by measuring the wind speed over the vertical range between lower and higher rotor tips. In this paper, we describe an experiment in which wind speed profiles were measured in front of a multimegawatt turbine using a ground–based pulsed lidar. Ignoring the vertical shear was shown to overestimate the kinetic energy flux of these profiles, in particular for those deviating significantly from a power law profile. As a consequence, the power curve obtained for these deviant profiles was different from that obtained for the ‘near power law’ profiles. An equivalent wind speed based on the kinetic energy derived from the measured wind speed profile was then used to plot the performance curves. The curves obtained for the two kinds of profiles were very similar, corresponding to a significant reduction of the scatter for an undivided data set. This new method for power curve measurement results in a power curve less sensitive to shear. It is therefore expected to eventually reduce the power curve measurement uncertainty and improve the annual energy production estimation. Copyright © 2011 John Wiley & Sons, Ltd. 相似文献
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In this paper, a procedure for the probabilistic treatment of solar irradiance and wind speed data is reported as a method of evaluating, at a given site, the electric energy generated by both a photovoltaic system and a wind system. The aim of the proposed approach is twofold: first, to check if the real probability distribution functions (PDFs) of both clearness index and wind speed overlap with Hollands and Huget and Weibull PDFs, respectively; and then to find the parameters of these two distributions that best fit the real data. Further, using goodness‐of‐fit tests, these PDFs are compared with another set of very common PDFs, namely the Gordon and Reddy and Lognormal functions, respectively. The results inform the design of a pre‐processing stage for the input of an algorithm that probabilistically optimizes the design of hybrid solar wind power systems. In this paper, the validity of the proposed procedure was tested using long‐term meteorological data from Acireale (Italy). Copyright © 2010 John Wiley & Sons, Ltd. 相似文献
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对陕西省宝鸡市陇县金润河北镇风电场气象条件、风功率密度、平均风速、主导风向等风能参数进行分析评价.结果表明,测风塔100m高度月平均风速、月平均风功率密度最大均出现在4月,最小均出现在8月;测风塔100m高度主导风向为SSW(南西南),主要风能方向为SSW(南西南),风电场风功率密度等级为1级.风电场安装20台2500... 相似文献
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Wilfried G.J.H.M. Van Sark Henrik C. Van der Velde Jan P. Coelingh Wim A.A.M. Bierbooms 《风能》2019,22(6):745-763
The use of the rotor equivalent wind speed for determination of power curves and annual energy production for wind turbines is advocated in the second edition of the IEC 61400‐12‐1 standard. This requires the measurements of wind speeds at different heights, for which remote sensing equipment is recommended in addition to meteorological masts. In this paper, we present a theoretical analysis that shows that the relevance of the rotor equivalent wind speed method depends on turbine dimensions and wind shear regime. For situations where the ratio of rotor diameter and hub height is smaller than 1.8, the rotor equivalent wind speed method is not needed if the wind shear coefficient at the location of the wind turbine has a constant value between ?0.05 and 0.4: in these cases, the rotor equivalent wind speed and the wind speed at hub height are within 1%. For complex terrains with high wind shear deviations are larger. The effect of non‐constant wind shear exponent, ie, different wind shear coefficients for lower and upper half of the rotor swept area especially at offshore conditions is limited to also about 1%. 相似文献
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Wind power forecasting for projection times of 0–48 h can have a particular value in facilitating the integration of wind power into power systems. Accurate observations of the wind speed received by wind turbines are important inputs for some of the most useful methods for making such forecasts. In particular, they are used to derive power curves relating wind speeds to wind power production. By using power curve modeling, this paper compares two types of wind speed observations typically available at wind farms: the wind speed and wind direction measurements at the nacelles of the wind turbines and those at one or more on‐site meteorological masts (met masts). For the three Australian wind farms studied in this project, the results favor the nacelle‐based observations despite the inherent interference from the nacelle and the blades and despite calibration corrections to the met mast observations. This trend was found to be stronger for wind farm sites with more complex terrain. In addition, a numerical weather prediction (NWP) system was used to show that, for the wind farms studied, smaller single time‐series forecast errors can be achieved with the average wind speed from the nacelle‐based observations. This suggests that the nacelle‐average observations are more representative of the wind behavior predicted by an NWP system than the met mast observations. Also, when using an NWP system to predict wind farm power production, it suggests the use of a wind farm power curve based on nacelle‐average observations instead of met mast observations. Further, it suggests that historical and real‐time nacelle‐average observations should be calculated for large wind farms and used in wind power forecasting. Copyright © 2011 John Wiley & Sons, Ltd. 相似文献
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Several known statistical distributions can describe wind speed data, the most commonly used being the Weibull family. In this paper, a new law, called ‘M‐Rice’, is proposed for modeling wind speed frequency distributions. Inspired by recent empirical findings that suggest the existence of some cascading process in the mesoscale range, we consider that wind speed can be described by a seasonal AutoRegressive Moving Average (ARMA) model where the noise term is ‘multifractal’, i.e. associated with a random cascade. This leads to the distribution of wind speeds according to the M‐Rice probability distribution function, i.e. a Rice distribution multiplicatively convolved with a normal law. A comparison based on the estimation of the mean wind speed and power density values as well as on the different goodness‐of‐fit tests (the Kolmogorov–Smirnov test, the Kuiper test and the quantile–quantile plot) was made between this new distribution and the Weibull distribution for 35 data sets of wind speed from the Netherlands and Corsica (France) sites. Accordingly, the M‐Rice and Weibull distributions provided comparable performances; however, the quantile–quantile plots suggest that the M‐Rice distribution provides a better fit of extreme wind speed data. Beyond these good results, our approach allows one to interpret the observed values of Weibull parameters. Copyright © 2011 John Wiley & Sons, Ltd. 相似文献
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新疆达坂城风电场风能资源特性分析 总被引:13,自引:0,他引:13
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。 相似文献
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E. García‐Bustamante J. F. González‐Rouco P. A. Jiménez J. Navarro J. P. Montávez 《风能》2009,12(7):640-659
Monthly wind energy estimations obtained by means of three different methodologies are evaluated. Hourly wind and wind power production data measured at five wind farms in the Northeast of Spain within the period spanning from June 1999 to June 2003 were employed for this purpose. One of the approaches is based on the combined contribution of the hourly wind speed frequency distribution and the corresponding power production. Several alternatives to represent the empirical wind power versus wind speed relationship are considered and their impacts on the error of monthly energy estimations assessed. Two more approaches derive monthly energy estimates directly from monthly wind values: one uses the theoretical power curve to obtain interpolated monthly wind power production values and the other consists in a simple linear regression between the observed wind speed and wind power monthly pairs, which serves as an approximation to the global power curve. The three methodologies reproduce reliably the total monthly wind energy. Results also reveal that linearity is a reasonable assumption for the relation between wind speed and power production at monthly timescales. This approach involves a simplification with respect to other standard procedures that require finer temporal resolution data. Copyright © 2009 John Wiley & Sons, Ltd. 相似文献
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针对风电场风速预测准确度不高的问题,提出一种基于风速波动特征提取的超短期风速预测方法。首先建立风速-风速变化量联合概率密度模型,分析风速的不确定性特征;根据风速波动特征,应用集合经验模态分解(EEMD)和风速分量样本熵(SampEn)值,将风速分解重组为波动量和趋势量;应用人工鱼群算法(AFSA)优化小波神经网络(WNN)进行趋势量预测;应用改进非线性自回归(INARX)神经网络对风速波动量进行预测,进而得到预测风速。通过实际风电场风速仿真预测,并与多种预测方法对比,表明该预测方法预测结果误差较小,可准确地进行超短期风速预测。 相似文献
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Zhang Jie Mohammad Reza Farahani Muhammad Imran Shu-Wen Wang 《Energy Sources, Part B: Economics, Planning, and Policy》2018,13(1):1-5
Environmental problems, population growth, and the recent energy crisis have emphasized the need for zero-emission technologies while also ensuring economic feasibility. This work presents the economic advantages of using wind energy for power generation in Iran. A theoretical model is developed, which predicts the output power under various geographical and operating conditions. The wind data (speed and direction) of 2-h interval long-term period from December 2010 to October 2015 was adopted and analyzed to evaluate the levelized costs of electricity (COE) for power generation from wind farms (Arsanjan, Lamerd, and Abadeh) for the year 2018 per time. The influence of two important geographical factors namely winds speed and air humidity on output power also was studied. The results showed that the output power increases continuously when the wind speed varies from 2.0 to 2.6 m/s probably due to the compression of air passing through the wind turbine. 相似文献
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Aditya Choukulkar Yelena Pichugina Christopher T. M. Clack Ronald Calhoun Robert Banta Alan Brewer Michael Hardesty 《风能》2016,19(8):1439-1452
The spurt of growth in the wind energy industry has led to the development of many new technologies to study this energy resource and improve the efficiency of wind turbines. One of the key factors in wind farm characterization is the prediction of power output of the wind farm that is a strong function of the turbulence in the wind speed and direction. A new formulation for calculating the expected power from a wind turbine in the presence of wind shear, turbulence, directional shear and direction fluctuations is presented. It is observed that wind shear, directional shear and direction fluctuations reduce the power producing capability, while turbulent intensity increases it. However, there is a complicated superposition of these effects that alters the characteristics of the power estimate that indicates the need for the new formulation. Data from two field experiments is used to estimate the wind power using the new formulation, and results are compared to previous formulations. Comparison of the estimates of available power from the new formulation is not compared to actual power outputs and will be a subject of future work. © 2015 The Authors. Wind Energy published by John Wiley & Sons, Ltd. 相似文献
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This paper presents a simplified algorithm to estimate the monthly performance of autonomous small-scale wind energy systems with battery storage. The novel model is drawn based on the simulation results, using eight-year long hour-by-hour measured wind speed data from five different locations throughout the world. An hourly constant load profile is used. The renewable energy simulation program (ARES) of the Cardiff School of Engineering is used. The ARES simulates the battery state of voltage (SoV) and is able to predict the system performance.The monthly performance values obtained from the simulations are plotted against increasing energy to load ratios for varying battery storage capacities to obtain performance curves. The novel method correlates the monthly system performance with the parameters of the Weibull distribution function, thus offering a universal use. The monthly performance curves are mathematically represented using a 2-parameter function. The novel method is validated by comparing the simulated performance values with those estimated from the simplified algorithm. The standard errors calculated in estimation of the system performance using the simplified algorithm are further presented for each battery capacity. 相似文献
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针对风向对风力机塔筒疲劳产生影响的问题,基于实测数据对考虑风速风向联合概率分布的风电塔筒结构的风致疲劳寿命展开研究。首先结合甘肃安西地区37 a的实测风速风向数据,给出风速风向联合概率分布。然后利用主S-N曲线法分别对不同风向和不同风速下风力机塔架结构法兰及门洞区域的响应规律进行分析。最后考虑风速风向联合概率分布,对风电塔筒结构风致疲劳寿命展开研究。结果表明:门洞朝向与风轮朝向的夹角变化和风速的改变均对风电塔筒的风致疲劳寿命有一定影响,其中门洞朝向与风轮朝向夹角为225°时疲劳寿命最长,风速为10~14 m/s时疲劳寿命变化幅度最大;考虑风速风向联合概率分布能更准确地计算风力机结构的风致疲劳寿命,且以此为依据对门洞朝向进行调整可延长其疲劳寿命,因此建议对风电塔架进行设计时,应考虑风电场所在地区的风速风向联合概率分布。 相似文献