共查询到20条相似文献，搜索用时 15 毫秒
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Rebecca Barthelmie Gunner Larsen Sara Pryor Hans Jrgensen Hans Bergstrm Wolfgang Schlez Kostas Rados Bernhard Lange Per Vlund Sren Neckelmann Sren Mogensen Gerard Schepers Terry Hegberg Luuk Folkerts Mikael Magnusson 《风能》2004,7(3):225-245
While experience gained through the offshore wind energy projects currently operating is valuable, a major uncertainty in estimating power production lies in the prediction of the dynamic links between the atmosphere and wind turbines in offshore regimes. The objective of the ENDOW project was to evaluate, enhance and interface wake and boundary layer models for utilization offshore. The project resulted in a significant advance in the state of the art in both wake and marine boundary layer models, leading to improved prediction of wind speed and turbulence profiles within large offshore wind farms. Use of new databases from existing offshore wind farms and detailed wake profiles collected using sodar provided a unique opportunity to undertake the first comprehensive evaluation of wake models in the offshore environment. The results of wake model performance in different wind speed, stability and roughness conditions relative to observations provided criteria for their improvement. Mesoscale model simulations were used to evaluate the impact of thermal flows, roughness and topography on offshore wind speeds. The model hierarchy developed under ENDOW forms the basis of design tools for use by wind energy developers and turbine manufacturers to optimize power output from offshore wind farms through minimized wake effects and optimal grid connections. The design tools are being built onto existing regional‐scale models and wind farm design software which was developed with EU funding and is in use currently by wind energy developers. Copyright © 2004 John Wiley & Sons, Ltd. 相似文献
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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. 相似文献
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Justin E. Stopa;Doug Vandemark;Ralph Foster;Marc Emond;Alexis Mouche;Bertrand Chapron; 《风能》2024,27(11):1340-1352
Measuring boundary layer stratification, wind shear, and turbulence remains challenging for wind resource assessment. In particular, larger eddy scales have the greatest impact on turbine load fluctuations, and there are few in situ methods to observe them adequately. Satellite remote sensing using synthetic aperture radar (SAR) is an alternative approach. In this study, eddy-related signatures in 704 high-resolution images are related to stratification through a bulk Richardson number (Ri$$ Ri $$) measured by a buoy near Martha's Vineyard, the US epicenter of offshore wind. Variations in SAR-observed atmospheric boundary layer eddies, or lack of them, correspond to specific Ri$$ Ri $$ regimes. Accounting for strong vertical wind shear, typically under stable stratification, is critical for energy production and turbine loads, and SAR directly identifies these conditions by the absence of energetic eddies. SAR also provides a regional climatology of atmospheric stratification for offshore wind assessment, complementing other observations, and with potential application worldwide. 相似文献
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Wind resource assessments are used to estimate a wind farm's power production during the planning process. It is important that these estimates are accurate, as they can impact financing agreements, transmission planning, and environmental targets. Here, we analyze the challenges in wind power estimation for onshore farms. Turbine wake effects are a strong determinant of farm power production. With given input wind conditions, wake losses typically cause downstream turbines to produce significantly less power than upstream turbines. These losses have been modeled extensively and are well understood under certain conditions. Most notably, validation of different model types has favored offshore farms. Models that capture the dynamics of offshore wind conditions do not necessarily perform equally as well for onshore wind farms. We analyze the capabilities of several different methods for estimating wind farm power production in 2 onshore farms with non‐uniform layouts. We compare the Jensen model to a number of statistical models, to meteorological downscaling techniques, and to using no model at all. We show that the complexities of some onshore farms result in wind conditions that are not accurately modeled by the Jensen wake decay techniques and that statistical methods have some strong advantages in practice. 相似文献
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Yuko Takeyama Teruo Ohsawa Katsutoshi Kozai Charlotte Bay Hasager Merete Badger 《风能》2013,16(6):865-878
Wind direction is required as input to the geophysical model function (GMF) for the retrieval of sea surface wind speed from a synthetic aperture radar (SAR) images. The present study verifies the effectiveness of using the wind direction obtained from the weather research and forecasting model (WMF) as input to the GMF to retrieve accurate wind fields in coastal waters adjacent to complex onshore terrain. The wind speeds retrieved from 42 ENVISAT ASAR images are validated based on in situ measurements at an offshore platform in Japan. Accuracies are also compared with cases using wind directions: the meso‐analysis of the Japan Meteorological Agency (MANAL), the SeaWinds microwave scatterometer on QuikSCAT and the National Center for Environmental Prediction final operational global analysis data (NCEP FNL). In comparison with the errors of the SAR‐retrieved wind speeds obtained using the WRF, MANAL, QuikSCAT and NCEP FNL wind directions, the magnitudes of the errors do not appear to be correlated with the errors of the wind directions themselves. In addition to wind direction, terrain factors are considered to be a main source of error other than wind direction. Focusing on onshore winds (blowing from the sea to land), the root mean square errors on wind speed are found to be 0.75 m s ? 1 (in situ), 0.96 m s ? 1 (WRF), 1.75 m s ? 1 (MANAL), 1.58 m s ? 1 (QuikSCAT) and 2.00 m s ? 1 (NCEP FNL), respectively, but the uncertainty is of the same order of magnitude because of the low number of cases. These results indicate that although the effectiveness of using the accurate WRF wind direction for the wind retrieval is partly confirmed, further efforts to remove the error due to factors other than wind direction are necessary for more accurate wind retrieval in coastal waters. Copyright © 2012 John Wiley & Sons, Ltd. 相似文献
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This paper investigates the correlation between the frequency components of the wind speed Power Spectral Density. The results extend an already existing power fluctuation model that can simulate power fluctuations of wind power on areas up to several kilometers and for time scales up to a couple of hours, taking into account the spectral correlation between different wind turbines. The modelling is supported by measurements from two large wind farms, namely Nysted and Horns Rev. Measurements from individual wind turbines and meteorological masts are used. Finally, the models are integrated into an aggregated model which is used for estimating some electrical parameters as power ramps and reserves requirements, showing a quite good agreement between simulations and measurement. The comparison with measurements generally show that the inclusion of the correlation between low frequency components is an improvement, but the effect is relatively small. The effect of including the low frequency components in the model is much more significant. Therefore, that aggregated model is useful in the power system planning and operation, e.g. regarding load following and regulation. Copyright © 2009 John Wiley & Sons, Ltd. 相似文献
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The method of extracting offshore wind field from SAR satellite images for offshore wind resource assessment shows some discrepancies in the calculated wind speed depending on which of the CMOD algorithms is used. This paper compared different algorithms, such as CMOD_IFR2, CMOD4, CMOD5, in order to find the suitable CMOD algorithm for the southern offshore area of the Korean Peninsula, which belongs to the zone influenced by the archipelago, by calculating the relative errors with reference to the Korea wind map of representative weather days by season. The result is that CMOD-IFR2 shows a tendency towards excessive estimation of wind speed, while CMOD4 shows the lowest RMSE values of wind speed differences with respect to the Korea wind map. Based on this result, we have concluded that, for the southern offshore area of the Korean Peninsula which belongs to the medium-range wind speed zone, CMOD4 is the suitable algorithm. 相似文献
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R. J. Barthelmie S. T. Frandsen M. N. Nielsen S. C. Pryor P.‐E. Rethore H. E. Jørgensen 《风能》2007,10(6):517-528
Understanding of power losses and turbulence increase due to wind turbine wake interactions in large offshore wind farms is crucial to optimizing wind farm design. Power losses and turbulence increase due to wakes are quantified based on observations from Middelgrunden and state‐of‐the‐art models. Observed power losses due solely to wakes are approximately 10% on average. These are relatively high for a single line of wind turbines due in part to the close spacing of the wind farm. The wind farm model Wind Analysis and Application Program (WAsP) is shown to capture wake losses despite operating beyond its specifications for turbine spacing. The paper describes two methods of estimating turbulence intensity: one based on the mean and standard deviation (SD) of wind speed from the nacelle anemometer, the other from mean power output and its SD. Observations from the nacelle anemometer indicate turbulence intensity which is around 9% higher in absolute terms than those derived from the power measurements. For comparison, turbulence intensity is also derived from wind speed and SD from a meteorological mast at the same site prior to wind farm construction. Despite differences in the measurement height and period, overall agreement is better between the turbulence intensity derived from power measurements and the meteorological mast than with those derived from data from the nacelle anemometers. The turbulence in wind farm model indicates turbulence increase of the order 20% in absolute terms for flow directly along the row which is in good agreement with the observations. Copyright © 2007 John Wiley & Sons, Ltd. 相似文献
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德国海上风电VSC-HVDC技术分析 总被引：1，自引：0，他引：1
系统地总结和梳理了德国海上风电并网情况及发展特点,分析阐述了德国海上风电场群集中并网的技术特征和经验,比较分析了高压交流输电和VSC—HVDC技术在海上风电并网应用的优缺点。最后,结合德国经验和中国发展需要,提出了海上风电并网分析模型。 相似文献
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Karl Nilsson Stefan Ivanell Kurt S. Hansen Robert Mikkelsen Jens N. Sørensen Simon‐Philippe Breton Dan Henningson 《风能》2015,18(3):449-467
The power production of the Lillgrund wind farm is determined numerically using large‐eddy simulations and compared with measurements. In order to simulate realistic atmospheric conditions, pre‐generated turbulence and wind shear are imposed in the computational domain. The atmospheric conditions are determined from data extracted from a met mast, which was erected prior to the establishment of the farm. In order to allocate most of the computational power to the simulations of the wake flow, the turbines are modeled using an actuator disc method where the discs are imposed in the computational domain as body forces which for every time step are calculated from tabulated airfoil data. A study of the influence of imposed upstream ambient turbulence is performed and shows that higher levels of turbulence results in slightly increased total power production and that it is of great importance to include ambient turbulence in the simulations. By introducing ambient atmospheric turbulence, the simulations compare very well with measurements at the studied inflow angles. A final study aiming at increasing the farm production by curtailing the power output of the front row turbines and thus letting more kinetic energy pass downstream is performed. The results, however, show that manipulating only the front row turbines has no positive effect on the farm production, and therefore, more complex curtailment strategies are needed to be tested. Copyright © 2014 John Wiley & Sons, Ltd. 相似文献
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针对漂浮式海上风电机组接地系统所处的深海环境及特殊的系泊系统,综合考虑纵荡运动对入流风速和尾流区域膨胀的影响,基于二维BP工程尾流模型,提出一种三维尾流模型（3Dksg_BP）,将该模型用于全尾流区域横向和垂向风速剖面的预测。预测结果与风洞实验数据对比发现,下游1.7 D 、 2.3 D 、 5.0 D 10.0 D D
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The North Sea is becoming increasingly attractive to wind energy developers and investors, with 38 wind farms belonging to five different countries and representing over€35 billion of assets. Concerns about offshore wind turbines being damaged by extreme windstorms pose a challenge to insurers, investors and regulators. Catastrophe modeling can adequately quantify the risk. In this study, a Monte Carlo simulation approach is used to assess the number of turbines that buckle using maximum wind speeds reaching each wind farm. Damage assessment is undertaken for each wind farm using a log‐logistic damage function and a left‐truncated Weibull distribution. The risk to offshore wind power in the North Sea is calculated using an exceedance probability (EP) curve for the portfolio of wind farms. The European Union Solvency II directive requires insurance companies to hold sufficient capital to guard against insolvency. The solvency capital requirement (SCR) is based on a value‐at‐risk measure calibrated to a 99.5% confidence level over a 1‐year time horizon. The SCR is estimated at €0.049 billion in the case of yawing turbines. Simulations are repeated for different climate change scenarios. If wind speeds grow by 5% and the frequency of storms increases by 40%, the SCR is seen to rise substantially to €0.264 billion. Relative to the total value of assets, the SCR is 0.14% compared with 0.08% for European property, confirming that these wind farm assets represent a relatively high risk. Furthermore, climate change could increase the relative SCR to levels as high as 0.75%. 相似文献
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Presently, less than a handful of papers have analysed the attitude towards offshore wind farms in a population living in an area with offshore wind farms. This leaves the experience-based attitude and demographic relations analysis relatively unexplored. The present studies aims at covering some of that seemingly uncharted territory by analysing attitudes from a sample of more than 1000 respondents. Applying an Ordered Probit Model, the results show general positive attitudes towards offshore wind farms and that the attitude formation seems to be a function of the gender, income, level of education, visit frequency and type of visit to the beach and the view to on-land turbines from the residence. Interestingly and perhaps the most interesting results, the observed relations between demographics and attitude are found to be dependent on the type and frequency of usage of the beach among the respondents. Attitudes towards offshore wind farms and demographic associations are thus found to be more evident in the case that respondents do use not the beach for walking on a relatively frequent basis but much weaker if the respondent use the beach on a frequent basis. However, these results are sensitive to the type of beach usage. This suggests that attitude formation towards offshore wind farms appear to be dependent on a combination of the type and frequency of use of the beach. To the author's knowledge these findings are novel, as such relation has not yet been identified in the literature. As such, the results shed light on a new angle in both the literature focusing on the opposition formation towards wind power projects in general and offshore wind farms in particular. 相似文献
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Accurate modelling of transient wind turbine wakes is an important component in the siting of turbines within wind farms because of wake structures that affect downwind turbine performance and loading. Many current industry tools for modelling these effects are limited to empirically derived predictions. A technique is described for coupling transient wind modelling with an aero‐elastic simulation to dynamically model both turbine operation and wake structures. The important feature of this approach is a turbine model in a flow simulation, which actively responds to transient wind events through the inclusion of controller actions such as blade pitching and regulation of generator torque. The coupled nature of the aero‐elastic/flow simulation also allows recording of load and control data, which permits the analysis of turbine interaction in multiple turbine systems. An aero‐elastic turbine simulation code and a large eddy simulation (LES) solver using an actuator disc model were adapted for this work. Coupling of the codes was implemented with the use of a software framework to transfer data between simulations in a synchronous manner. A computationally efficient simulation was developed with the ability to model turbines exhibiting standard baseline control operating in an offshore environment. Single and multiple wind turbine instances were modelled in a transient flow domain to investigate wake structures and wake interaction effects. Blade loading data were analysed to quantify the increased fluctuating loads on downwind turbines. The results demonstrate the successful implementation of the coupled simulation and quantify the effect of the dynamic‐turbine model. Copyright © 2012 John Wiley & Sons, Ltd. 相似文献
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考虑实际工程需求,开发一种几何约束条件下海上风电场智能布局优化方法。该方法使用Gaussian模型计算风力机尾流区的速度亏损,并以最大化风电场年发电量为目标采用差分进化算法进行优化,可满足海上风电场布局时的各类几何约束。利用该方法分别在3行、4行、7行几何约束下对中国某海上风电场的风力机排布方式进行优化。结果显示,相比于原始布局方案,在考虑海缆铺设成本增加的情况下布局优化方案可提升风电场年发电量2.13%～2.64%。进一步分析表明,布局优化过程中可行解数量的设置需综合考虑智能算法寻优难度的影响。 相似文献
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The protection of offshore wind farms (OWFs) against overvoltages, especially resonant overvoltage, is of paramount importance because of poor accessibility and high repair costs. In this paper, we study how switching overvoltages at the wind turbine transformer (WTT) medium voltage (MV) side can lead to high overvoltages on the low voltage (LV) side. The effect of overvoltage protective devices is analyzed. A detailed model of an OWF row is developed in electromagnetic transients program–alternative transients program (EMTP‐ATP), including interconnecting cables, WTT, surge arresters and resistive–capacitive filters. A parameterized black‐box WTT model is obtained from measurements and is used for investigating the transfer of resonant overvoltages from the MV to the LV side. The model is capable of shifting systematically the frequencies and adjusting the transformer input impedance. Simulation results show that wind turbine energization in an OWF can lead to overvoltages on the LV terminals. The rate of rise of overvoltages (du/dt) is in the range of 300–500 pu/µs. It is found that resistive–capacitive filters should be installed on both MV and LV terminals of WTTs to decrease both resonant overvoltages and du/dt, which is unachievable by surge arrester alone. Copyright © 2014 John Wiley & Sons, Ltd. 相似文献