• Wind and Structures
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• v.20 no.5
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• pp.609-622
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• 2015

This study presents a dynamic response analysis of operational and parked wind turbines in order to gain better understanding of the roles of wind loads on turbine blades and tower in the generation of turbine response. The results show that the wind load on the tower has a negligible effect on the blade responses of both operational and parked turbines. Its effect on the tower response is also negligible for operational turbine, but is significant for parked turbine. The tower extreme responses due to the wind loads on blades and tower of parked turbine can be estimated separately and then combined for the estimation of total tower extreme response. In current wind turbine design practice, the tower extreme response due to the wind loads on blades is often represented as a static response under an equivalent static load in terms of a concentrated force and a moment at the tower top. This study presents an improved equivalent static load model with additional distributed inertial force on tower, and introduces the square-root-of-sum-square combination rule, which is shown to provide a better prediction of tower extreme response.

• Wind and Structures
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• v.25 no.2
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• pp.101-129
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• 2017

Local transient extreme wind loads caused by group tower-related interference are among the major reasons that lead to wind-induced damage of super-large cooling towers. Four-tower arrangements are the most commonly seen patterns for super-large cooling towers. We considered five typical four-tower arrangements in engineering practice, namely, single row, rectangular, rhombic, L-shaped, and oblique L-shaped. Wind tunnel tests for rigid body were performed to determine the influence of different arrangements on static and dynamic wind loads and extreme interference effect. The most unfavorable working conditions (i.e., the largest overall wind loads) were determined based on the overall aerodynamic coefficient under different four-tower arrangements. Then we calculated the one-, two- and three-dimensional aerodynamic loads under different four-tower arrangements. Statistical analyses were performed on the wind pressure signals in the amplitude and time domains under the most unfavorable working conditions. On this basis, the non-Gaussian distribution characteristics of aerodynamic loads on the surface of the cooling towers under different four-tower arrangements were analyzed. We applied the Sadek-Simiu procedure to the calculation of two- and three-dimensional aerodynamic loads in the cooling towers under the four-tower arrangements, and the extreme wind load distribution patterns under the most unfavorable working conditions in each arrangement were compared. Finally, we proposed a uniform equation for fitting the extreme wind loads under the four-tower arrangements; the accuracy and reliability of the equation were verified. Our research findings will contribute to the optimization of the four-tower arrangements and the determination of extreme wind loads of super-large cooling towers.

• Wind and Structures
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• v.33 no.6
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• pp.423-435
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• 2021

Although existing algorithms can predict wind speed using historical observation data, for engineering feasibility, most use moment methods and probability density functions to estimate fitted parameters. However, extreme wind speed prediction accuracy for long-term return periods is not always dependent on how the optimized frequency distribution curves are obtained; long-term return periods emphasize general distribution effects rather than marginal distributions, which are closely related to potential extreme values. Moreover, there are different wind speed parent sample types; how to theoretically select the proper extreme value distribution is uncertain. The influence of different sampling time intervals has not been evaluated in the fitting process. To overcome these shortcomings, updated steps are introduced, involving parameter sensitivity analysis for different sampling time intervals. The extreme value prediction accuracy of unknown parent samples is also discussed. Probability analysis of mean wind is combined with estimation of the probability plot correlation coefficient and the maximum likelihood method; an iterative estimation algorithm is proposed. With the updated steps and comparison using a Monte Carlo simulation, a fitting policy suitable for different parent distributions is proposed; its feasibility is demonstrated in extreme wind speed evaluations at Longhua and Chuansha meteorological stations in Shanghai, China.

• Journal of Electrical Engineering and Technology
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• v.13 no.5
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• pp.1841-1851
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• 2018

For the safe and stable operation of the power system, accurate wind power prediction is of great significance. A wind power prediction method based on empirical mode decomposition and improved extreme learning machine is proposed in this paper. Firstly, wind power time series is decomposed into several components with different frequency by empirical mode decomposition, which can reduce the non-stationary of time series. The components after decomposing remove the long correlation and promote the different local characteristics of original wind power time series. Secondly, an improved extreme learning machine prediction model is introduced to overcome the sample data updating disadvantages of standard extreme learning machine. Different improved extreme learning machine prediction model of each component is established. Finally, the prediction value of each component is superimposed to obtain the final result. Compared with other prediction models, the simulation results demonstrate that the proposed prediction method has better prediction accuracy for wind power.

• Wind and Structures
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• v.18 no.6
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• pp.633-650
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• 2014

The uncertainty of extreme wind speeds is one key contributor to the uncertainty of wind loads and their effects on structures. The probability distribution of annual extreme wind speeds may be characterized using a classical Gumbel Type distribution. The expression that establishes the relationship between the extreme wind speeds at different recurrence periods and the corresponding coefficients of variation is formulated, and its efficacy is validated. The coefficients of variation are calibrated to be about 0.125 and 0.184 according to defined Chinese and US design specifications, respectively. Based on the wind data of 54 cities in China, 49 meteorological stations in the US, 3 stations in Singapore, the coefficients span intervals of (0.1, 0.35), (0.08, 0.20) and (0.06, 0.14), respectively. For hurricanes in the US, the coefficients range approximately from 0.3 to 0.4. This convenient technique is recommended as one alternative tool for coefficient of variation analyses in the future revisions of related codes. The sensitivities of coefficients of variation for 49 meteorological stations in the US are quantified and demonstrated. Some contradictions and incompatibilities can be clearly detected and illustrated by comparing the coefficients of variation obtained with different combinations of recurrence period wind data.

• Wind and Structures
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• v.8 no.4
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• pp.269-281
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• 2005

The paper describes the work of the IAWE Working Group WGF - Extreme Wind Prediction and Zoning, one of the international codification working groups set up in 2000. The topics covered are: the international database of extreme winds, quality assurance and data quality, averaging times, return periods, probability distributions and fitting methods, mixed wind climates, directionality effects, the influence of orography, rare events and simulation methods, long-term climate change, and zoning and mapping. Recommendations are given to promote the future alignment of international codes and standards for wind loading.

• Wind and Structures
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• v.15 no.2
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• pp.163-176
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• 2012

Damaging winds, associated with a variety of weather phenomena, are frequently experienced in New Zealand. Observations and modelling of two recent extreme wind events; the Taranaki tornado outbreak of July 2007, and the Greymouth down-slope easterly wind storm of July 2008 are described in detail here. Post-event engineering damage surveys, rare for New Zealand, were done for these storms and the results are summarized here. Finally, the issue of sampling extreme wind events is raised and the need to include detailed numerical modelling analysis to understand wind gust climatologies at observing sites and extending these to wider regions is discussed.

• Journal of Wind Energy
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• v.5 no.1
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• pp.22-32
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• 2014

The structural design of a wind turbine must show the verification of the structural integrity of all load-carrying components. Also, design load calculations shall be performed using appropriate and accurate methods. In this study, advanced numerical approach for the calculation of design loads based on unsteady computational fluid dynamics (CFD) is presented considering extreme design load conditions such as the extreme coherent gust (ECG) and the 50 year extreme operating gust (EOG). Unsteady aerodynamic loads are calculated based on Reynolds average Navier-Stokes (RANS) equations with shear-stress transport k-ω(SST k-ω) turbulent model. A full three-dimensional 5 MW offshore wind-turbine model with rotating blades, hub, nacelle, and tower configuration is practically considered and its aerodynamic interference effect among blades, nacelle, and tower is also accurately considered herein. Calculated blade loads based on unsteady CFD method with respect to blade azimuth angle are compared with those by NREL FAST code and physically investigated in detail.

• Wind and Structures
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• v.32 no.3
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• pp.193-204
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• 2021

The estimation of the extreme wind load (effect) under a mean recurrence interval (MRI) is an important task in the wind-resistant design for the structure. It can be predicted by either first-order method or full-order method, depending on the accuracy and complexity requirement. Although the first-order method with the consideration of wind directionality has been proposed, less work has been done on the full-order method, especially with the wind directionality. In this study, the full-order method considering the wind directionality is proposed based on multivariate joint probability distribution. Meanwhile, considering two wind directions, the difference of the corresponding results based on the first-order method and full-order method is analyzed. Finally, based on the measured wind speed data, the discrepancy between these two methods is investigated. Results show that the difference between two approaches is not obvious under larger MRIs while the underestimation caused by the first-order method can be larger than 15% under smaller MRIs. Overall, the first-order method is sufficient to estimate the extreme wind load (effect).

• 한국신재생에너지학회:학술대회논문집
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• 2008.10a
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• pp.262-267
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• 2008

The long-term wind data are reconstructed from the short-term meteorological data to design the 4 MW offshore wind park which will be constructed at Woljeong-ri, Jeju island, Korea. Using two MCP (Measure-Correlate-Predict) models, the relative deviation of wind speed and direction from two neighboring reference weather stations can be regressed at each azimuth sector. The validation of the present method is checked about linear and matrix MCP models for the sets of measured data, and the characteristic wind turbulence is estimated from the ninety-percent percentile of standard deviation in the probability distribution. Using the Gumbel's model, the extreme wind speed of fifty-year return period is predicted by the reconstructed long-term data. The predicted results of this analysis concerning turbulence intensity and extreme wind speed are used for the calculation of fatigue life and extreme load in the design procedure of wind turbine structures at offshore wind farms.