scholarly journals Extreme wind speed prediction in mountainous area with mixed wind climates

2022 ◽  
Author(s):  
Teng Ma ◽  
Wei Cui ◽  
Lin Zhao ◽  
Yejun Ding ◽  
Genshen Fang ◽  
...  
Keyword(s):  
Wind Speed ◽  
Mountainous Area ◽  
Construction Site ◽  
Wind System ◽  
Mountainous Areas ◽  
Wind Speeds ◽  
Extreme Wind ◽  
Synoptic Wind ◽  
Extreme Wind Speed ◽  
Extreme Wind Speeds

Abstract In addition to common synoptic wind system, the mountainous terrain forms a local thermally driven wind system, which makes the mountain wind system have strong terrain dependence. Therefore, in order to estimate the reliable design wind speeds for structural safety, the samples for extreme wind speeds for certain return periods at mountainous areas can only come from field measurements at construction site. However, wind speeds measuring duration is usually short in real practice. This work proposes a novel method for calculating extreme wind speeds in mountainous areas by using short-term field measurement data and long-term nearby meteorological observatory data. Extreme wind speeds in mountainous area are affected by mixed climates composed by local-scale wind and large scale synoptic wind. The local winds can be recorded at construction site with short observatory time, while the extreme wind speeds samples from synoptic wind climate from nearby meteorological station with long observatory time is extracted for data augmentation. The bridge construction site at Hengduan Mountains in southwestern China is taken as an example in this study. A 10-month dataset of field measurement wind speeds is recorded at this location. This study firstly provides a new method to extract wind speed time series of windstorms. Based on the different windstorm features, the local and synoptic winds are separated. Next, the synoptic wind speeds from nearby meteorological stations are converted and combined with local winds to derive the extreme wind speeds probability distribution function. The calculation results shows that the extreme wind speed in the short return period is controlled by the local wind system, and the long-period extreme wind speed is determined by the synoptic wind system in the mountain area.

Extreme wind speed climatology over Greece

2021 ◽  
Author(s):  
Georgios Blougouras ◽  
Chris G. Tzanis ◽  
Kostas Philippopoulos
Keyword(s):  
Wind Speed ◽  
Confidence Intervals ◽  
Wind Turbines ◽  
Economic Losses ◽  
Return Periods ◽  
Wind Speeds ◽  
Return Levels ◽  
Extreme Wind ◽  
Extreme Wind Speed ◽  
Extreme Wind Speeds

<p>Extreme wind speeds are a multifaceted environmental risk. They may cause considerable damage to infrastructure (e.g., bridges, private property), they can jeopardize maritime and aviation activities, and sometimes even human safety. Furthermore, the design of wind turbines for on and off-shore wind farms requires a study of the return periods of extreme wind speeds in combination with the lifespan of the wind turbines. Windstorms also result in major economic losses and cause up to 80 % of the natural hazards' long term insurance loss in Europe. The scope of this work is to identify location-specific extreme wind speed thresholds and obtain accurate estimates of exceedances for multiple future horizons. In this context, the Extreme Value Analysis framework is used for providing the return periods and the respective return levels of extreme wind speeds. The Peaks Over Threshold method is utilized for the 10 m wind speed for a domain centered over Greece, in Southeastern Mediterranean. Wind speed data at 10 m are extracted from the ERA5 reanalysis dataset that provides hourly estimates of surface wind speed with a horizontal resolution of 0.25°x0.25°, from 1979/01/01 up to 2019/12/31 (i.e., 41 years). The thresholds are selected using the Mean Residual Life plots, which is the most reliable method for identifying accurate threshold values. The seasonal analysis of the exceedances is discussed in terms of the physical mechanisms in the region. The exceedances are modelled using the Generalized Pareto Distribution, whose shape and scale parameters (<em>ξ</em> and <em>σ</em>, respectively) are estimated using the Maximum Likelihood Estimation method. The return levels and their confidence intervals are estimated for return periods up to 100 years. Geographic Information Systems are used for mapping future projections of extreme wind speeds and the corresponding confidence intervals. The results are discussed in terms of identifying high-risk areas and the findings could assist in informed decision-making in the wind energy industry. The proposed methodological framework could be extended to other areas characterized by particularly high wind speeds and the results can contribute towards sustainable investments and support adaptation mechanisms.</p>

scholarly journals The Compound Inverse Rayleigh as an Extreme Wind Speed Distribution and its Bayes Estimation

2021 ◽  
Author(s):  
Elio Chiodo ◽  
Maurizio Fantauzzi ◽  
Giovanni Mazzanti
Keyword(s):  
Wind Speed ◽  
Prior Information ◽  
Extreme Values ◽  
Rayleigh Distribution ◽  
Bayes Estimation ◽  
Large Set ◽  
Wind Speeds ◽  
Extreme Wind ◽  
Extreme Wind Speed ◽  
Extreme Wind Speeds

The paper deals with the Compound Inverse Rayleigh distribution, shown to constitute a proper model for the characterization of the probability distribution of extreme values of wind-speed, a topic which is gaining growing interest in the field of renewable generation assessment, both in view of wind power production evaluation and the wind-tower mechanical reliability and safety. The first part of the paper illustrates such model starting from its origin as a generalization of the Inverse Rayleigh model - already proven to be a valid model for extreme wind-speeds - by means of a continuous mixture generated by a Gamma distribution on the scale parameter, which gives rise to its name. Moreover, its validity to interpret different field data is illustrated, also by means of numerous numerical examples based upon real wind speed measurements. Then, a novel Bayes approach for the estimation of such extreme wind-speed model is proposed. The method relies upon the assessment of prior information in a practical way, that should be easily available to system engineers. In practice, the method allows to express one’s prior beliefs both in terms of parameters, as customary, and/or in terms of probabilities. The results of a large set of numerical simulations – using typical values of wind-speed parameters - are reported to illustrate the efficiency and the accuracy of the proposed method. The validity of the approach is also verified in terms of its robustness with respect to significant differences compared to the assumed prior information.

scholarly journals An Improved Typhoon Simulation Method Based On Latin Hypercube Sampling Method

2021 ◽  
Author(s):  
Jianpeng Sun ◽  
Guanjun Lv ◽  
Wenfeng Huang ◽  
Rong Wang ◽  
Xiaogang Ma
Keyword(s):  
Sampling Method ◽  
Correlation Coefficients ◽  
Latin Hypercube Sampling ◽  
Simulation Method ◽  
Return Periods ◽  
Latin Hypercube ◽  
Wind Speeds ◽  
Extreme Wind ◽  
Extreme Wind Speed ◽  
Extreme Wind Speeds

Abstract In order to further improve the prediction accuracy of typhoon simulation method for extreme wind speed in typhoon prone areas, an improved typhoon simulation method is proposed by introducing the Latin hypercube sampling method into the traditional typhoon simulation method. In this paper, the improved typhoon simulation method is first given a detailed introduction. Then, this method is applied to the prediction of extreme wind speeds under various return periods in Hong Kong. To validate this method, two aspects of analysis is carried out, including correlation analysis among typhoon key parameters and prediction of extreme wind speeds under various return periods. The results show that the correlation coefficients among typhoon key parameters can be maintained satisfactorily with this improved typhoon simulation method. Compared with the traditional typhoon simulation method, extreme wind speeds under various return periods obtained with this improved typhoon simulation method are much closer to the results obtained with historical typhoon wind data.

scholarly journals Wavelet Scale Variance Analysis of Wind Extremes in Mountainous Terrains

Energies ◽  
2019 ◽  
Vol 12 (16) ◽  
pp. 3048 ◽  
Author(s):  
Telesca ◽  
Guignard ◽  
Helbig ◽  
Kanevski
Keyword(s):  
Wind Speed ◽  
Average Wind Speed ◽  
Wind Speeds ◽  
Speed Distribution ◽  
Average Wind ◽  
Wind Speed Distribution ◽  
Extreme Wind ◽  
Wavelet Variance ◽  
Extreme Wind Speeds ◽  
Wind Extremes

The 10-min average wind speed series recorded at 130 stations distributed rather homogeneously in the territory of Switzerland are investigated. Fixing a percentile-based threshold of the wind speed distribution, a wind extreme is defined as the duration of the sequence of consecutive wind values above the threshold. This definition allows to analyze the sequence of extremes as a temporal point process marked by their duration. Representing the sequence of wind extremes by the inter-extreme interval series, the wavelet variance, a useful tool to investigate the variance of a time series across scales, was applied in order to find a link between the wavelet scales and several topographic parameters. Our findings suggest that the mean duration of wind extremes and mean inter-extreme time are positively correlated and that such relationship depends on the threshold of the wind speed. Furthermore, the threshold of the wind speed distribution correlates best with a terrain parameter related to the Laplacian of terrain elevations; and, in particular, for wavelet scales less than 3, the terrain exposure may explain the formation of extreme wind speeds.

scholarly journals Non-stationary statistical estimation of wind speeds of rare recurrence in the Azov and Black Sea region

2021 ◽  
pp. 15-22
Author(s):  
V.P. Evstigneev ◽  
◽  
V.A. Naumova ◽  
N.A. Lemeshko ◽  
◽  
...  
Keyword(s):  
Wind Speed ◽  
Black Sea ◽  
Statistical Estimation ◽  
Extreme Values ◽  
Distribution Functions ◽  
Statistical Distribution ◽  
Black Sea Region ◽  
Wind Speeds ◽  
Extreme Wind ◽  
Extreme Wind Speeds

In the paper statistical distribution of the highest wind speed per year in the Azov and Black Sea region was analyzed using the data of 33 meteorological stations for 1958-2013. A statistical estimation of the wind speed extremes was carried out by approximation of the empirical sample with a function of Generalized distribution of Extreme Values (GEV) and by extrapolating it to the low probabilities region. We used two methodologies and applied statistical distribution functions corresponding to them. The first method is based on the assumption of stationarity of parameters of the GEV function. The second one is based on the non-stationary assumption of time dependence of extremum localization parameter μ. It was found, that for 13 out of 33 stations of the region, non-stationary GEV-function turned out to be adequate to describe extreme wind speeds.

scholarly journals Downslope windstorms and associated extreme wind speed statistics evaluation according to the COSMO-CLM Russian Arctic hindcast, ASR reanalysis and observations

2021 ◽  
Author(s):  
Vladimir Platonov ◽  
Anna Shestakova
Keyword(s):  
Wind Speed ◽  
Surface Wind ◽  
Temperature Fields ◽  
The Arctic ◽  
Russian Arctic ◽  
Novaya Zemlya ◽  
Wind Speeds ◽  
Extreme Wind ◽  
Extreme Wind Speed ◽  
Downslope Windstorms

<p>The number of severe weather events at the Arctic region increased significantly. Its formation related generally to the mesoscale processes including downslope windstorms over Novaya Zemlya, Svalbard, Tiksi bay accompanied by strong winds. Therefore, its investigation required detailed hydrometeorological and climatic information with a horizontal resolution of at least several kilometers. This work aims to investigate extreme wind speeds statistics associated with downslope windstorms and evaluate it according to the COSMO-CLM Russian Arctic hindcast, ASR reanalysis, stations and satellite data.</p><p>COSMO-CLM Russian Arctic hindcast created in 2020 covers the 1980–2016 period with grid size ~12 km and 1-hour output step, containing approximately a hundred hydrometeorological characteristics, as well at surface, as on the 50 model levels. The primary assessments of the surface wind speed and temperature fields showed good agreement with ERA-Interim reanalysis in large-scale patterns and many added values in the regional mesoscale features reproduction according to the coastlines, mountains, large lakes, and other surface properties.</p><p>Mean values, absolute and daily maxima of wind speed, high wind speed frequencies were estimated for the COSMO-CLM Russian Arctic hindcast and the well-known Arctic System Reanalysis (ASRv2) for a 2000-2016 period. COSMO-CLM showed higher mean and daily maximal wind speed areas concerned to coastal regions of Svalbard and Scandinavia, over the northern areas of Taymyr peninsula. At the same time, the absolute wind speed maxima are significantly higher according to ASRv2, specially over the Barents Sea, near the Novaya Zemlya coast (differences are up to 15-20 m/s). The same pattern observed by a number of days with wind speed above the 30 m/s threshold. Compared with station data, the ASRv2 reproduced mean wind speeds better at most coastal and inland station, MAE are within 3 m/s. For absolute wind speed maxima differences between two datasets get lower, the COSMO-CLM hindcast is quite better for inland stations.</p><p>Model capability to reproduce strong downslope windstorms evaluated according to the observations timeseries over Novaya Zemlya, Svalbard and Tiksi stations during bora conditions. Generally, the ASRv2 reproduced the wind direction closer to observations and the wind speed worser than COSMO-CLM. The extreme wind speed frequencies during bora cases have less errors according to COSMO-CLM hindcast (up to ~5%) compared to the ASRv2 data (up to 10%). At the same time, moderate wind speed frequencies are reproduced by ASRv2 better.</p><p>Five specific Novaya Zemlya bora cases were evaluated according to SAR satellite wind speed data. Both ASRv2 and COSMO-CLM overestimated mean wind speed (MAE 0.5-6 m/s), maximal wind speed bias has different signs, however, the COSMO-CLM is better in most cases. Extreme percentiles biases (99 and 99.9%), correlation, structure and amplitude (according to the SAL method) are closer to observations by the COSMO-CLM hindcast.</p>

scholarly journals Separated Pitch Control at Tip: Innovative Blade Design Explorations for Large MW Wind Turbine Blades

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Ranjeet Agarwala ◽  
Paul I. Ro
Keyword(s):  
Wind Speed ◽  
Wind Turbine ◽  
Turbine Blades ◽  
Wind Turbine Blades ◽  
Pitch Control ◽  
Wind Speeds ◽  
Extreme Wind ◽  
Blade Tip ◽  
Low Wind Speeds ◽  
Extreme Wind Speeds

This paper focuses on the deployment and evaluation of a separated pitch control at blade tip (SePCaT) control strategy for large megawatt (MW) wind turbine blade and explorations of innovative blade designs as a result of such deployment. SePCaT configurations varied from five to thirty percent of the blade length in 5 percentage increments (SePCaT5, SePCaT10, SePCaT15, SePCaT20, SePCaT25, and SePCaT30) are evaluated by comparing them to aerodynamical responses of the traditional blade. For low, moderate, high, and extreme wind speed variations treated as 10, 20, 30, and 40 percent of reference wind speeds, rotor power abatement in region 3 of the wind speed power curve is realized by feathering full length blade by 6, 9, 12, and 14 degrees, respectively. Feathering SePCaT30, SePCaT25, SePCaT20, and SePCaT15 by 14, 16, 26, and 30 degrees, respectively, achieves the same power abatement results when compared to traditional blade at low wind speeds. Feathering SePCaT30, SePCaT25, and SePCaT20 by 18, 26, and 30 degrees on the other hand has the same effect at high wind speeds. SePCaT30 feathered to 26 and 30 degrees has the same abatement effects when compared to traditional blade at high and extreme wind speeds.

Forecasting of Tornadoes and Downbursts

2020 ◽  
Author(s):  
Djordje Romanic
Keyword(s):  
Chaos Theory ◽  
Prediction Models ◽  
Weather Prediction ◽  
Small Scale ◽  
Weather Forecasts ◽  
Wind Speeds ◽  
The Past ◽  
Extreme Wind ◽  
Extreme Wind Speeds ◽  
Numerical Weather Prediction Models

Tornadoes and downbursts cause extreme wind speeds that often present a threat to human safety, structures, and the environment. While the accuracy of weather forecasts has increased manifold over the past several decades, the current numerical weather prediction models are still not capable of explicitly resolving tornadoes and small-scale downbursts in their operational applications. This chapter describes some of the physical (e.g., tornadogenesis and downburst formation), mathematical (e.g., chaos theory), and computational (e.g., grid resolution) challenges that meteorologists currently face in tornado and downburst forecasting.

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