Éditeur(s) : HAL CCSD International Association for Energy Economics
Résumé : International audience
In this paper we propose to determinate and to test a set ofstatistical parameters (20)to estimate the predictability of the global horizontal irradiation time series and thereby propose a new prospective tool indicating the expected error regardlessthe forecasting methodsa modeller can possibly implement. The mean absolute log return, which is a tool usually used in econometry, proves to be a very good estimator. Some examples of the use of this tool are exposed, showing the interest of this statistical parameter in concrete cases of predictions or optimizations.
ISSN: 0195-6574

hal-01180041
https://hal.archives-ouvertes.fr/hal-01180041
https://hal.archives-ouvertes.fr/hal-01180041/document
https://hal.archives-ouvertes.fr/hal-01180041/file/discriminent_param.pdf

Éditeur(s) : HAL CCSD Springer Verlag
Résumé : International audience
ISSN: 0944-1344

hal-01587582
https://hal.archives-ouvertes.fr/hal-01587582
DOI : 10.1007/s11356-016-6993-6

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
Résumé : International audience
Advances in Natural and Technological Hazards Research

hal-01676621
https://hal.univ-antilles.fr/hal-01676621

Éditeur(s) : HAL CCSD
2012 AGU Fall Meeting

hal-00771544
https://hal-mines-paristech.archives-ouvertes.fr/hal-00771544

Éditeur(s) : HAL CCSD
Résumé : The presence of obstacles met in natural environment by the flow, influences the dispersion of air pollutants which it carries. This thesis, based on spatiotemporal micro-meteorological measurements in tropical region, aims at studying the dispersion of compounds emitted by the ecosystem mangrove according to the weather conditions. At a daily scale, the meteorological analysis reveals, besides the presence of Trade Winds, the existence of thermal flows of which nocturnal thermodynamic parameters have been defined. The field observation has shown that the weak intensity of the wind disadvantages the dispersion of compounds emitted during the night. At a finer scale, the existence of a spectral gap separating large scale phenomena of those related to turbulence has been demonstrated. These last ones were treated by spectral and statistical approaches to quantify the turbulent fluxes of momentum and sensible heat during the night, for an averaged duration of 13 minutes. The stratification of the surface layer has been considered and determined by Monin-Obukhov similarity theory. The measurements acquired at night and the application of Kolmogorov theory allowed us to deduct the dissipation rate of energy and the size of the vortices at 5.5 meters in height. This work has also led us, by gas chromatography coupled to mass spectrometry, to identify, in mangrove, sulphurated volatil organic compounds, organohalogen, BTEX, ... All these results will later serve to feed dispersion models related to the studied ecosystem.
La présence d'obstacles rencontrés en milieu naturel par l'écoulement, influence la dispersion des polluants qu'il transporte. Cette thèse, fondée sur des mesures micro-météorologiques spatio-temporelles en région tropicale, vise à étudier la dispersion de composés émis par l'écosystème mangrove en fonction des conditions météorologiques. A l'échelle journalière, l'analyse météorologique révèle, outre la présence des Alizés, l'existence d'écoulements thermiques dont des paramètres thermodynamiques nocturnes ont été définis. L'observation terrain nous a montré que la faible intensité du vent défavorise la dispersion des composés émis durant la nuit. A une échelle plus fine, l'existence d'un trou spectral séparant les phénomènes de grande échelle de ceux liés à la turbulence a été mise en évidence. Ces derniers ont été traités par des approches spectrale et statistique pour quantifier les flux turbulents de quantité de mouvement et de chaleur sensible, pendant la nuit, pour une durée de moyenne de l'ordre de 13 minutes. L'état de stratification de la couche de surface a été pris en compte et déterminé par la théorie de similitude de Monin-Obukhov. Les mesures nocturnes effectuées et l'application de la théorie de Kolmogorov ont permis de déduire les taux de dissipation de l'énergie et la taille des tourbillons à 5,5 m d'altitude. Ce travail a également conduit, par l'analyse chromatographique en phase gazeuse couplée à la spectrométrie de masse, à l'identification, en mangrove, de composés organiques volatils soufrés, des organohalogénés, des BTEX, ... L'ensemble de ces résultats servira ultérieurement à alimenter les modèles de dispersion spécifiques liés aux écosystèmes étudiés.
https://tel.archives-ouvertes.fr/tel-00665882

Droits : info:eu-repo/semantics/OpenAccess
NNT : 11AGUY0438
tel-00665882
https://tel.archives-ouvertes.fr/tel-00665882
https://tel.archives-ouvertes.fr/tel-00665882/document
https://tel.archives-ouvertes.fr/tel-00665882/file/ThA_seCdAlexis.pdf

Éditeur(s) : HAL CCSD
Résumé : International audience
In this work, we have led an analysis of the error of different global solar radiation prediction models according to the global solar radiation variability. Different predictions models where performed such as machine learning techniques (Neural Networks, Gaussian processes and support vector machines) in order to forecast the Global Horizontal solar Irradiance (GHI). We also include in this study a simple linear autoregressive (AR) model as well as two naive models based on persistence of the GHI and persistence of the clear sky index (denoted herein scaled persistence model). The models are calibrated and tested with data from three 3 French islands: Corsica (42.15°N ; 9.08°E), Guadeloupe (16.25°N ; 61.58°W) and Reunion (21.15°S ; 55.5°E). Guadeloupe and Reunion are located in a subtropical climatic zone whereas Corsica is in a tempered climatic zone. Hence the global solar radiation variation differs significantly. The output error of the different models was quantified by the nRSME. In order to quantify the influence of the global solar radiation variability on the forecasting models error we performed a classification of typical days according to different typical days. Each class of typical day is defined by a variation of global solar radiation rate. For each class and for each location, the selected forecasting models where performed and the error was quantified. With this analysis a global solar radiation forecasting models can be selected according to the location, the global solar radiation fluctuations and hence the meteorological conditions. INTRODUCTION Large and frequent variations of solar radiation can be observed in tropical climates with amplitudes reaching 800 W/m² and occurring within a short time interval, from few seconds to few minutes, according to the geographical location. Such fluctuations can be due for example to the dynamic of clouds which can be very complex and depend on cloud type, size, speed and spatial distribution and, more generally, due to some specific local meteorological conditions. Thus, the solar energy forecasting, a process used to predict the amount of solar energy available in the current and near terms, might be a difficult task. Some of the best predictors found in literature are Autoregressive and moving average (ARMA) [5,7,8], Bayesian inferences [9,10], Markov chains [11], k-Nearest-Neighbors predictors [12] or artificial intelligence techniques as the Artificial Neural Network (ANN) [9-11]. Although these methodologies are potentially good in many areas, we observed in our previous studies on global radiation prediction [9,13,14] that the simple model based on the persistence of the clear sky index gives often very good results with acceptable errors [15] for short term forecasting time horizon (<= 1 hour). The goal of this paper is to determinate the influence of solar radiation variability regarding different classes of days on the expected error provided by different forecasting methods that the modeller can possibly implement. The paper is organized as follow: Section 2 describes the data we have used. Section 3 exposes the classification methodology and the results obtained for the three studied locations. In the two following sections, the forecasting methods are exposed and then 3 the errors on the forecasting results for each location and for each class are exposed.
The Third Southern African Solar Energy Conference (SASEC2015)
Kruger National Park, South Africa

Droits : info:eu-repo/semantics/OpenAccess
hal-01099487
https://hal.archives-ouvertes.fr/hal-01099487
https://hal.archives-ouvertes.fr/hal-01099487/document
https://hal.archives-ouvertes.fr/hal-01099487/file/article%20SASEC.pdf

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
Résumé : International audience
Although earthquakes and tsunamis are less frequent in the Dover Straitthan over active subduction zones, a plausible potential exists for intraplate earthquakes of magnitude Mw=6.9 generating a tsunami with damaging consequences. In April 1580, an earthquake shook the region violently and destructions were reported as far as London in the north andRouen in the south. Despite fair weather conditions, a series of abnormal sea waves was reported in several harbours (Calais, Boulogne and Dover) on the same day. A first step was to produce a range of numerical coseismic tsunami simulations and to compare them with historical witness accounts. Results raise the question of whether such earthquakes could also triggerchalk flow-generated tsunamis along cliff lines on both sides of the Strait. Gravity-driven collapses affect thechalk cliffs periodically, but local tsunami waves caused by very large mass movements could reach heights of several meters and, for example, strike Dover.
Proceedings of the 15th World Conference on Earthquake Engineering
Lisbonne, Portugal

halshs-01291496
https://halshs.archives-ouvertes.fr/halshs-01291496

Éditeur(s) : HAL CCSD Elsevier
Résumé : International audience
In this paper, we propose a benchmarking of supervised machine learning techniques (neural networks, Gaussian processes and support vector machines) in order to forecast the Global Horizontal solar Irradiance (GHI). We also include in this benchmark a simple linear autoregressive (AR) model as well as two naive models based on persistence of the GHI and persistence of the clear sky index (denoted herein scaled persistence model). The models are calibrated and validatedwith data from three French islands: Corsica (41.91°N; 8.73°E), Guadeloupe (16.26°N; 61.51°W) and Reunion (21.34°S ; 55.49°E). The main findings of this work are, that for hour ahead solar forecasting,the machine learning techniques slightly improve the performances exhibited by the linear AR and the scaled persistence model. However, the improvement appears to be more pronounced in case of unstable sky conditions.These nonlinear techniques start to outperform their simple counterparts for forecasting horizons greater than one hour.
ISSN: 0038-092X

Droits : info:eu-repo/semantics/OpenAccess
hal-01099211
https://hal.archives-ouvertes.fr/hal-01099211
https://hal.archives-ouvertes.fr/hal-01099211/document
https://hal.archives-ouvertes.fr/hal-01099211/file/Manuscript_Lauretetal_Rev_unmarked.pdf

Éditeur(s) : HAL CCSD Copernicus Publications on behalf of the European Geosciences Union
Résumé : International audience
Natural Hazards and Earth System Science

hal-01676604
https://hal.univ-antilles.fr/hal-01676604

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

Éditeur(s) : HAL CCSD
Résumé : 1 page
The main aim of this study, co-funded by BRGM, Regional Council of Guadeloupe, European Union, ADEME and UAG, was to examine the silica deposition mechanisms and estimate their deposition kinetics at acidic and basic pH conditions, during the cooling from 260 to 25°C of separated waters, discharged from production wells, located in the Bouillante geothermal field. The acquisition of this type of information is very useful not only for the geothermal exploitation but especially, if production fluids are re-injected in the ground, as this is envisaged in the Bouillante geothermal field. The different on site experiments showed that, in these conditions, the silica deposition was always initiated by a silica polymerization mechanism and the formation of a white colloidal gel, which slowed down the silica precipitation. In agreement with the literature data, this polymerization mechanism is characterized by an order 2 kinetic law, strongly dependant on pH. The determination of the specific surface area by specific mercury porosimetry for this gel (250 m2/g) in the UAG laboratories, allowed estimating the corresponding kinetic constant at 25°C. Other experiments at different final temperatures (50, 75 and 100°C) are necessary in order to define this constant as a function of the temperature. The silica precipitation under amorphous silica form was observed much later, after the polymerization stage, and only in particular conditions (long time of atmospheric exposure, water stagnation...). The pH of the Bouillante geothermal fluid is estimated to be close to 5.3±0.3, at 260°C, in the reservoir conditions. If this parameter, very influent on the kinetics of silica deposition, can be preserved at values less than 7 during the re-injection of the production fluids in the ground at relatively high temperatures (150-160°C), it is strongly probable that no chemical treatment is necessary to avoid silica precipitation.
19ème Conférence Géologique de la Caraïbe - 2011
Gosier, Guadeloupe, France

hal-00575943
https://hal-brgm.archives-ouvertes.fr/hal-00575943