Bivariate estimation of extreme wind speeds

Escalante-Sandoval, Carlos

doi:10.1016/j.strusafe.2007.09.005

Cited by 8 publications

(5 citation statements)

References 15 publications

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“…In spite of this obvious fact, efforts to characterize homogeneous or mixed wind series continue prevailing in the technical literature. For instance, in recent contributions to the statistical characterization of extreme winds, Escalante-Sandoval [3], Cook and Harris [4] and Simiu et al [5] propose new schemes to fit probability distributions to available data, but express no restriction to the processing of mixed series.…”

Section: Overview Of Probability Distributions Of Extreme Annual Ts Wmentioning

confidence: 99%

“…The alternative scheme described herein constitutes a departure from the usual approach adopted in the literature, that is, finding the probability density functions that best fit wind velocity series recorded at given meteorological stations [3][4][5]. However, both approaches should not be viewed as competing, but rather as complementary procedures.…”

Section: Introductionmentioning

confidence: 99%

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Simulation of extreme wind series caused by thunderstorms in temperate latitudes

Ponte

Riera

2010

Structural Safety

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Section: Overview Of Probability Distributions Of Extreme Annual Ts Wmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Simulation of extreme wind series caused by thunderstorms in temperate latitudes

Ponte

Riera

2010

Structural Safety

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“…For each pair of random variables a bivariate probability distribution of extreme values is fitted. Escalante-Sandoval (1998) considers that all analysed components occur concurrently with the same probability, i.e. F (Q p …”

Section: Methods Of Escalantementioning

confidence: 99%

“…The general equation for bivariate distributions of extreme values (the logistic model, also named the Gumbel-Hougaard copula, Shiau et al 2006), according to Gumbel (Raynal and Salas 1987, Escalante-Sandoval 1998, Ramírez and Aldama 2000, Escalante-Sandoval and Reyes-Chávez 2002, Escalante-Sandoval 2007, is given by:…”

Section: Bivariate Distribution Function Of Extreme Valuesmentioning

confidence: 99%

Validation of methods to estimate design discharge flow rates for dam spillways with large regulating capacity

2012

Hydrological Sciences Journal

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The estimation and review of discharge flow rates in hydraulic works is a fundamental problem in water management. In the case of dams with large regulating capacity, in order to estimate return periods of discharge flow rates from the spillways, it becomes necessary to consider both peak flow and volume of the incoming floods. In this paper, the results of the validation for several methods of assessing design floods for spillways of dams with a large flood control capacity are presented; the validation is performed by comparing the maximum outflows (or the maximum levels reached in the reservoir) obtained from the routing of the design floods with those obtained from the routing of the historical annual maximum floods. The basin of Malpaso Dam, Mexico, is used as the case study.Key words design events; flood routing; return period; Malpaso Dam, Chiapas, Mexico Validation des méthodes d'estimation des crues de projet pour les déversoirs de barrages de grande capacité de régularisationRésumé L'estimation et la révision des valeurs des crues de projet des ouvrages hydrauliques sont des problémes fondamentaux de la gestion de l'eau. Dans le cas des barrages avec une grande capacité de régularisation, afin d'estimer la période de retour des crues de projet, il est nécessaire de considérer le pic et le volume des crues à l'entrée du déversoir. Dans cette étude on présente les résultats de la validation du calcul des crues de projet par plusieurs méthodes pour des déversoirs de barrages avec une grande capacité de régularisation ; la validation est effectuée en comparant les débits sortants maximaux (ou les niveaux maximaux atteints dans le réservoir) obtenus en utilisant soit les crues de projet, soit les maximums annuels de crues historiques. Le bassin du barrage Malpaso est employé comme cas d'étude.

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“…When dealing with the selection of the optimal wind turbine for a specific site, often the wind database is too short for the application of standard methods, so the accurate estimation of the occurrence of extreme wind speed can be very difficult, and the error of the estimated return level can be very large and inefficient for design purposes . A parametric approach can be very useful when such methods need to be applied to shorter datasets.…”

Section: Introductionmentioning

confidence: 99%

Applied statistics for extreme wind estimate

Castellani

Garinei

Terzi³

et al. 2014

Wind Energy

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The assessment of extreme wind speeds is a crucial issue for securing structural safety of wind turbines and inquiring largest loads to which turbines must be prepared to undergo.International standards suggest applying the Gumbel method of fitting the annual maxima to their theoretic probability distribution. Yet, often, wind databases are too short to apply such methods with statistical significance, and other procedures are commonly adopted [such as peaks over threshold (POT) and independent storms], which involve dependency on arbitrary thresholds for filtering data and issues of sub-asymptocity, i.e. how well the selected dataset fits to density functions describing the distribution of peaks or extreme values.The present paper aims at contributing to such currently ongoing debate, providing a statistical analysis of the application of POT and independent storms methods on wind time series of various lengths from different geographical areas.The CERN data analysis framework ROOT has been employed for guaranteeing excellent standards of computational precision and wealth of statistical information. Analysis of uncertainties in the wind speeds estimates and tests of the goodness of fit of the datasets to the proper distributions have been carried on. An algorithm for choosing the optimum thresholds was developed, which encapsules and compromises the statistical complexity of the methods. A declustering procedure has been carried on for discriminating proper peaks in the POT method: it has been tested that such declustering provides a dramatic improvement of the statistical quality of the method.

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Bivariate estimation of extreme wind speeds

Cited by 8 publications

References 15 publications

Simulation of extreme wind series caused by thunderstorms in temperate latitudes

Simulation of extreme wind series caused by thunderstorms in temperate latitudes

Validation of methods to estimate design discharge flow rates for dam spillways with large regulating capacity

Applied statistics for extreme wind estimate

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