Éditeur(s) : HAL CCSD
Résumé : International audience
In this work, we present an analysis of a one-year period measured wind speed in the atmospheric boundary layer from a wind energy production site. We employ a Hilbert-based methodology, namely arbitrary-order Hilbert spectral analysis, to characterize the intermittent property of the wind speed in a joint amplitude-frequency space. The measured scaling exponents implies intermittent nature of the wind on mesoscales.
Wind Energy-Impact of turbulence

hal-01528079
https://hal.archives-ouvertes.fr/hal-01528079
DOI : 10.1007/978-3-642-54696-9

Éditeur(s) : HAL CCSD Elsevier
Résumé : International audience
In order to qualify the fluctuating nature of solar radiation under tropical climate, we classify daily distributions of the clearness index kt by estimating a finite mixture of Dirichlet distributions without assuming any parametric hypothesis on these daily distributions. The method is applied to solar radiation measurements performed in Guadeloupe (16°2 N, 61 W) where important fluctuations can be observed even within a short period of a few minutes. The results put in evidence four distinct classes of distributions corresponding to different types of days. The sequence of such classes can be of interest for prediction.
ISSN: 0038-092X

hal-01527878
https://hal.archives-ouvertes.fr/hal-01527878
DOI : 10.1016/j.solener.2009.01.010

Éditeur(s) : HAL CCSD Non-Linéaire Publications
Résumé : Depuis quelques decennies, l'energie eolienne conna^t une croissance considerable. Cependant cette energie est dependante de la vitesse du vent variant en intensite sur des echelles de temps qui incluent l'annee, la journee 'a quelques secondes. L'objectif de ce travail est de caracteriser les uctuations d'une serie temporelle de production eolienne. Dans un premier temps, nous verions l'utilisation de la Loi de Taylor, relation entre l'ecart type 2 P et la moyenne < p > : 2 P = C < p >. Cette relation fut observee en ecologie, en nance, dans les sciences du vivant et pour des donnees de trac internet [1]. De recents travaux fournissent des hypotheses d'explication quant a l'origine de cette loi [2,3]. L'exposant caracterise le type de dynamique du processus considere et varie entre 1=2 et 1. Dans notre cas d'etude, l'estimation de l'exposant est proche de 1. Quand = 1, les processus consideres sont a invariance d'echelle [1]. Pour mettre en evidence les proprietes d'invariance d'echelle de notre serie temporelle, nous eectuons une analyse multifractale pour estimer la fonction exposant d'echelle (h) a l'aide des moments d'ordre h de l'increment temporel des donnees de production eolienne P = P(t + ) P(t), telle que < Pq > (h) [5]. La fonction (h) est concave et non-lineaire : plus elle est concave, plus la serie analysee sera intermittente. Nous montrons que la serie temporelle de la production eolienne consideree est intermittente et possede des proprietes multifractales. De plus le modele de cascades aleatoires log-normal se revele pertinent pour decrire ces fluctuations.
Rencontre du Non-Linéaire

ISBN : 978-2-9538596-1-4
hal-00760932
https://hal.archives-ouvertes.fr/hal-00760932

Éditeur(s) : HAL CCSD European Geosciences Union (EGU)
Résumé : International audience
We consider here wind speed time series and the aggregate output wind power from a wind farm. We study their scaling statistics in the framework of fully developed turbulence and Kolmogorov's theory. We estimate their Fourier power spectra and consider their scaling properties in the physical space. We show that the atmospheric wind speed and the aggregate power output from a wind farm are intermittent and multifractal over a wide range of scales. The coupling between simultaneous data of the wind speed and aggregate power output is investigated through a joint multifractal description using the generalized correlation functions (GCFs). This multiscaling test is compatible with a linear relation between the wind speed and the aggregate power output fluctuations for timescales T > 103 s ' 15min.
ISSN: 1023-5809

hal-00958490
https://hal.archives-ouvertes.fr/hal-00958490
DOI : 10.5194/npg-21-379-2014

Éditeur(s) : HAL CCSD Elsevier
Résumé : International audience
The objectives are to study and model the aggregate wind power fluctuations dynamics in the multifractal framework. We present here the analysis of aggregate power output sampled at 1 Hz during three years. We decompose the data into several Intrinsic Mode Functions (IMFs) using Empirical Mode Decomposition (EMD). We use a new approach, arbitrary order Hilbert spectral analysis, a combination of the EMD approach with Hilbert spectral analysis (or Hilbert-Huang Transform) and the classical structure-function analysis to extract the scaling exponents or multifractal spectrum ζ(q)ζ(q): this function provides a full characterization of a process at all intensities and all scales. The application of both methods, i.e. structure-function and arbitrary-order Hilbert spectral analyses, gives similar results indicating that the aggregate power output from a wind farm, possesses intermittent and multifractal properties. In order to check this result, we generate stochastic simulations of a Multifractal Random Walk (MRW) using a log-normal stochastic equation. We show that the simulation results are fully compatible with the experimental results
Physica A

hal-00846643
https://hal.archives-ouvertes.fr/hal-00846643
DOI : 10.1016/j.physa.2013.04.038

Éditeur(s) : HAL CCSD
Résumé : 32 pages
Wind energy production is very sensitive to instantaneous wind speed fluctuations. Thus rapid variation of wind speed due to changes in the local meteorological conditions can lead to electrical power variations of the order of the nominal power output. In small grids, as they exist for example on some islands in the French West Indies, such fluctuations can cause instabilities in case of intermediate power shortages. To palliate these difficulties, it is essential to identify and characterize the wind speed distributions. This allows to anticipate the eventuality of power shortage or power surge. Therefore, it is of interest to categorize wind speed fluctuations into distinct classes and to estimate the probability of a distribution to belong to a class. This paper presents a method for classifying wind speed histograms by estimating a finite mixture of Dirichlet distributions. The SAEM algorithm that we use provides a fine distinction between wind speed distribution classes. It's a new nonparametric method for wind speed sequences classification. However, we show that the wind speed distributions in each class correspond to specific Gram- Charlier densities.
https://hal.archives-ouvertes.fr/hal-00319608

hal-00319608
https://hal.archives-ouvertes.fr/hal-00319608
https://hal.archives-ouvertes.fr/hal-00319608v2/document
https://hal.archives-ouvertes.fr/hal-00319608/file/Article_dirichlet.pdf
ARXIV : 0810.4422

Éditeur(s) : HAL CCSD Elsevier
Résumé : International audience
A good knowledge of the intermittency of global solar radiation is crucial for selecting the location of a solar power plant and predicting the generation of electricity. This paper presents a multifractal analysis study of 367 daily global solar radiation sequences measured with a sampling rate of 1 Hz over one year at Guadeloupean Archipelago (French West Indies) located at 16°15'N latitude and 60°30'W longitude. The mean power spectrum computed follows a power law behaviour close to the Kolmogorov spectrum. The intermittent and multifractal properties of global solar radiation data are investigated using several methods. Under this basis, a characterization for each day using three multifractal parameters is proposed
ISSN: 0038-092X

hal-01527892
https://hal.archives-ouvertes.fr/hal-01527892
DOI : 10.1016/j.solener.2013.09.018

Éditeur(s) : HAL CCSD Elsevier
Résumé : International audience
In this work we perform a statistical analysis of global solar radiation measured at two sites, Petit Canal and Pointe a Pitre, 38 km distant from, Guadeloupe, French West Indies. We have established a correlation model based on the coefficient of variation assuming a time scale separation. The coefficient of variation is calculated on 10 min interval with data measured at 1 Hz. This analysis highlights the dynamic correlation that can occur between measurements from two different sites with a time step of 1 s. From these results, knowing the coefficient of variation on a site, we have established a new correlation model on this parameter for another site. A diagram linking the standard deviation for the studied sites, for a given coefficient of variation is proposed for correlated and non-correlated cases. Moreover this analysis evidences the existence of a threshold time under which there is no significant correlation. The methodology and the model can be applied to any other sites to establish diagrams of the coefficient of variation.This model can be useful in choosing new sites of PV production in establishing correlation from on site to another
ISSN: 0960-1481

hal-01528078
https://hal.archives-ouvertes.fr/hal-01528078
DOI : 10.1016/j.renene.2015.10.049

Éditeur(s) : HAL CCSD Elsevier
Résumé : International audience
In this paper, we have presented a spectral and a multifractal analysis performed on 412 time series of wind speed data each of duration of 350 s and sampled at 20 Hz. The average spectrum for the wind speed displays a scaling behavior, in the inertial range, over two decades, with β=1.68 close to the Kolmogorov value −5/3. A multifractal analysis has been motivated by the presence of scaling invariance in data set. Then we have considered their scaling properties in the framework of fully developed turbulence and multifractal cascades. The results obtained for wind speed confirm that the exponent scaling function ζV(q) is nonlinear and concave. This exponent characterizes the scaling functions in the inertial range indicating that the wind speed is intermittent and multifractal. Moreover the theoretical quadratic relation for lognormal multifractals is well fitted. We investigate the consequence for wind energy production: we generate stochastic simulations of a multifractal random walk, and using a power curve derived from experimental data, we generate the associated power time series. We show that, due to the saturation of the power curve for large speed values, when the input time series (turbulent wind speed) is multifractal, the output can be almost monofractal.
ISSN: 0167-6105

hal-00779049
https://hal.archives-ouvertes.fr/hal-00779049
DOI : 10.1016/j.jweia.2012.06.002