Éditeur(s) : HAL CCSD MDPI
Résumé : International audience
The Taylor power law (or temporal fluctuation scaling), is a scaling relationship of the form σ ~ (P)λ where !! is the standard deviation and hPi the mean value of a sample of a time series has been observed for power output data sampled at 5 min and 1 s and from five wind farms and a single wind turbine, located at different places. Furthermore, an analogy with the turbulence field is performed, consequently allowing the establishment of a scaling relationship between the turbulent production IP and the mean value (P)
ISSN: 2079-9276

hal-01528077
https://hal.archives-ouvertes.fr/hal-01528077
https://hal.archives-ouvertes.fr/hal-01528077/document
https://hal.archives-ouvertes.fr/hal-01528077/file/resources-04-00787.pdf
DOI : 10.3390/resources4040787

Éditeur(s) : HAL CCSD Intech
Résumé : International audience
The massive integration of sustainable energies into electrical grids (non-interconnectedor connected) is a major problem due to their stochastic character revealed by strongfluctuations at all scales. In this paper, the scaling behaviour or power law correlationsand the nature of scaling behaviour of sustainable resource data such as flow velocity,atmospheric wind speed, solar global solar radiation and sustainable energy such as,wind power output, are highlighted. For the first time, Fourier power spectral densitiesare estimated for each dataset. We show that the power spectrum densities obtained areclose to the 5/3 Kolmogorov spectrum. Furthermore, the multifractal and intermittentproperties of sustainable resource and energy data have been revealed by the concavityof the scaling exponent function. The proposed analysis frame allows a full descriptionof fluctuations of processes considered. A good knowledge of the dynamic of fluctua-tions is crucial to management of the integration of sustainable energies into a grid.
Sustainable Energy - Technological Issues, Applications and Case Studies

hal-01528087
https://hal.archives-ouvertes.fr/hal-01528087
DOI : 10.5772/106341

Éditeur(s) : HAL CCSD Institut Henri Poincaré-Nonlinéaire Publications
Résumé : International audience
Depuis quelques décennies, l'énergie éolienne connaît une croissance considérable. Cependant cette énergie est dépendante de la vitesse du vent variant en intensité sur des échelles de temps qui incluent l'année, la journée à quelques secondes. Il est donc fondamental de bien parvenir à comprendre et décrire le caractère non-linéaire et stochastique de ces fluctuations dans la production électrique issue des éoliennes. L'objectif de ce travail est de caract'eriser les fluctuations d'une série temporelle de production éolienne. Dans un premier temps, nous vérifions l'utilisation de la loi de Taylor, relation de puissance entre l'écart-type et la moyenne. Cette relation fut observée en écologie, en finance, dans les sciences du vivant et pour des données de traffic internet. De récents travaux fournissent des hypothèses d'explication quant à l'origine de cette loi cite{Agata2010,Kendall2011}. L'exposant alpha caractérise le type de dynamique du processus considéré et varie entre 1/2 et 1. Dans notre cas d'étude, l'estimation de l'exposant alpha est proche de 1. Quand alpha=1, les processus considérés sont à invariance d'échelle cite{eisler2008}. Pour mettre en évidence les propriétés d'invariance d'échelle de notre série temporelle, nous effectuons une analyse multifractale pour estimer la fonction exposant d' échelle l'aide des moments d'ordre $q$ de l'incrément temporel des données de production éolienne $Delta P=P(t+ au)-P(t)$, telle que $<(Delta P_ au)^q>simeq au^{zeta(q)}$ cite{Schertzer1997}. La fonction $zeta(q)$ est concave et non-linéaire: plus elle est concave, plus la série analysée sera intermittente. Nous montrons que la série temporelle de la production éolienne considérée est intermittente et possède des propriiétés multifractales. De plus le modèle de cascades aléatoires log-normal se révèle pertinent pour décrire ces fluctuations.
Compte-rendus de la 15ème Rencontre du non-linéaire

hal-01527884
https://hal.archives-ouvertes.fr/hal-01527884

Éditeur(s) : HAL CCSD Elsevier
Résumé : International audience
The correlation between the flow turbulence and the performances of a ma- rine current turbine is studied. First, the incoming flow encountered in the flume tank is characterized in the framework of fully developed turbulent cascades in the inertial range. The Reynolds number, the Kolmogorov dissipation scale and the integral scale, are estimated from flow measurements. The intermittency of the turbulence is characterized in the lognormal multifractal framework, and the influence of the turbulent flow on the turbine power is assessed. The rotor speed control unit characteristics used for the turbine regulation induces non-negligible effects on the turbine behavior under fluctuations loads. Even if the power spectrum does not reveal any scale invariance, a multiscale analysis allows us to show the correlations between the turbulence time se- ries and the power produced. The classical Mean Square Coherency function shows that for scales larger than 10 seconds, the upstream velocity and power have large correlations. In the framework of the Empirical Mode Decomposition method, such correlations are studied using the time-dependence intrinsic corre- lation analysis method. This method allows to zoom into time-frequency scales where the flow perturbations induced some modifications in power production
ISSN: 0960-1481

hal-01528296
https://hal.archives-ouvertes.fr/hal-01528296
DOI : 10.1016/j.renene.2017.05.024

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 (IMF) using Empirical Mode Decomposition (EMD). We use a new approach, arbitrary order Hilbert spectral analysis, a combination of EMD approach with Hilbert spectral analysis (or Hilbert Huang Transform) and the classical structure function analysis to extract the scaling exponents or multifractal spectrum $zeta(q)$: 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, give 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-01527887
https://hal.archives-ouvertes.fr/hal-01527887
DOI : 10.1016/j.physa.2013.04.038

Éditeur(s) : HAL CCSD
Résumé : International audience
There is growing efforts for the development of wind energy. Yet, as for other renewable resources, a basic characteristic of wind energy is to deliver intermittent power. In this paper, we consider this topic by analyzing data provided by the wind industry. We discuss first the spectral properties of the data and the corresponding power curve. We estimate the scaling behavior in the inertial scale of wind input and the power output. We also study the rotor revolution scaling fluctuations. Finally the wind/power transfer function is studied, together with the wind/rotation and rotation/power intermediary transfer functions.
Energy Procedia

hal-01273262
https://hal.archives-ouvertes.fr/hal-01273262
DOI : 10.1016/j.egypro.2015.07.897

Éditeur(s) : HAL CCSD
Résumé : International audience
Journal of Applied Nonlinear Dynamics

hal-01528080
https://hal.archives-ouvertes.fr/hal-01528080
DOI : 10.5890/JAND.2016.12.001

Éditeur(s) : HAL CCSD Springer
Résumé : In this work, we present an analysis of 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 amplitudefrequency space. The measured scaling exponents implies intermittent nature of the wind on mesoscales.
Wind Energy: Impact of Turbulence

ISBN : 978-3642546952
hal-00958512
https://hal.archives-ouvertes.fr/hal-00958512

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 ≃ 15 min
ISSN: 1023-5809

hal-01527893
https://hal.archives-ouvertes.fr/hal-01527893
DOI : 10.5194/npg-21-379-2014

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 150N latitude and 60 300W longitude. The mean power spectrum computed follows a power law behavior 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-00903410
https://hal.archives-ouvertes.fr/hal-00903410
DOI : 10.1016/j.solener.2013.09.018

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 b ¼ 1:68 close to the Kolmogorov value À 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 z V ðqÞ 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-01527886
https://hal.archives-ouvertes.fr/hal-01527886
DOI : 10.1016/j.jweia.2012.06.002

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 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 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 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