Cette proposition fait suite à un stage dont les objectifs étaient d'effectuer une étude complète sur le thème de la prévision de la qualité de l'air, et d'initier un projet de construction d'un modèle statistique de prévision. Ainsi l'association agréée Qualitair Corse en collaboration avec l'université de Corse/UMR CNRS UMR 6134 propose de poursuivre cette étude réalisée de juin 2009 à septembre 2009. Les techniques d'Intelligence Artificielle ont été utilisées avec succès dans le cadre du projet EnR pour la prédiction de l'ensoleillement. Nous souhaitons ainsi les étendre à la problématique de la prédiction de pics de pollution atmosphérique.

Un descriptif complet est disponible en bas cette note.

Sources :
http://www.qualitaircorse.org
http://spe.univ-corse.fr

Un papier, auquel j'ai collaboré, avait été accepté lors de la "24th European Photovoltaic Solar Energy Conference and Exhibition", à Hamburg. Nous venons d'apprendre que notre poster a reçu le prix du "Poster Award" lors de la session 5 intitulée « PV SYSTEMS ». Le poster est téléchargeable en bas de page.

>>> Lire le résumé de notre papier

Source :
http://www.photovoltaic-conference.com
http://spe.univ-corse.fr

Ce workshop se tiendra à Brest, du 17 au 18 septembre 2009. Il nous sera donné l'occasion de présenter les travaux suivants.

Title of the paper: Use of the XMCDA format to describe a multicriteria evaluation process to localize a wind park in Corsica: feedback.

Authors: Marie-Laure Nivet, Christophe Paoli, Pascal Oberti.

Abstract: The proposed presentation will be organized as follow. First, we will describe a multicriteria evaluation process to localize a wind park in Corsica. Then, we will present its translation into the XMCDA format. Finally we will present the encountered difficulties and we will discuss some perspectives.

Sources:
http://conferences.telecom-bretagne.eu/ddws5
http://www.decision-deck.org
http://ernst-schroeder.uni.lu/d3

Cette conférence se tiendra à Bonn, du 05 au 08 juillet 2009. Il me sera donné l'occasion de présenter des travaux sur l'aide à la décision participative et de co-présider une session "TF-11: Multicriteria evaluation, information
systems and agents in stream Multiple Criteria Decision Analysis".

Title of the paper: Actors roles and software interface users in a multicriteria evaluation process : state of the art and proposals

Authors: Christophe Paoli, Pascal Oberti.

Abstract: The participation of actors in multicriteria evaluation processes of alternatives is a challenge for the analyst. Various contributions exist [Roy, 1996][Froger, Oberti, 2002][Oberti, 2004][Munda, 2004][Jabeur, Martel, 2005]. First we will present how is studied the structure of evaluation process. In a second time, we will propose an implementation through MECADEPPE software [Oberti et al., 2008], translating the actor roles into user rights in order to represent a real process. Finally we will present an illustration of a participatory evaluation for energy projects.

Source
http://www.euro-2009.de

Un nouveau papier vient d'être accepté au sein d'une conférence dans le domaine de l'intelligence artificielle. Il s'agit de la ICIC'09 : "2009 International Conference on Intelligent Computing", co-sponsorisé par "IEEE Computational Intelligence Society" et "International Neural Network Society". Notre papier (cf ci-dessous : titre, auteurs et résumé) apparaitra dans les "proceedings" (Collection de communications scientifiques) de la conférence qui seront publiés au sein de Springer Verlag, incluant Lecture Notes in Computer Sciences (LNCS)/Lecture Notes in Artificial Intelligence (LNAI)/Lecture Notes in Bioinformatics (LNBI)/ Communications in Computer and Information Science (CCIS).

Title of the paper: Solar radiation forecasting using ad-hoc time series preprocessing and neural networks.

Authors : Christophe Paoli, Cyril Voyant, Marc Muselli, Marie-Laure Nivet.

Abstract: In this paper, we present an application of neural networks in the renewable energy domain. We have developed a methodology for the daily prediction of global solar radiation on a horizontal surface. We use an ad-hoc time series preprocessing and a Multi-Layer Perceptron (MLP) in order to predict solar radiation at daily horizon. First results are promising with nRMSE < 21% and RMSE < 998 Wh/m². Our optimized MLP presents prediction similar to or even better than conventional methods such as ARIMA techniques, Bayesian inference, Markov chains and k-Nearest-Neighbors approximators. Moreover we found that our data preprocessing approach can reduce significantly forecasting errors.

Source
http://www.ic-ic.org

Un papier, auquel j'ai collaboré, vient d'être accepté au congrès suivant "24th European Photovoltaic Solar Energy Conference and Exhibition", à Hamburg, Germany. Près de 1500 articles ont été soumis pour cette rencontre européenne très reconnue dans la communauté des énergéticiens. Le fait d'être accepté pour une session orale est une reconnaissance de notre travail, les programmes oraux devant être établis bien à l'avance. Notre papier (cf ci-dessous : titre, auteurs et résumé) apparaitra dans les "proceedings" (Collection de communications scientifiques) de la conférence.

Title of the paper : Predictability of PV power grid performance on insular sites without weather stations: use of artificial neural networks

Authors : Cyril Voyant, Marc Muselli, Christophe Paoli, Marie-Laure Nivet and Philippe Poggi

Abstract : The official meteorological network is poor on the island of Corsica: only three sites being about 50 km apart are equipped with pyranometers which enable measurements by hourly and daily step. These sites are Ajaccio (41°55'N and 8°48'E, seaside), Bastia (42°33'N, 9°29'E, seaside) and Corte (42°30'N, 9°15'E average altitude of 486 meters). This lack of weather station makes difficult the predictability of PV power grid performance. This work intends to study a methodology which can predict global solar irradiation using data available from another location for daily and hourly horizon. In order to achieve this prediction, we have used Artificial Neural Network which is a popular artificial intelligence technique in the forecasting domain. A simulator has been obtained using data available for the station of Ajaccio that is the only station for which we have a lot of data: 16 years from 1972 to 1987. Then we have tested the efficiency of this simulator in two places with different geographical features: Corte, a mountainous region and Bastia, a coastal region. On daily horizon, the relocation has implied fewer errors than a “naïve” prediction method based on the persistence (RMSE=1468 Vs 1383Wh/m² to Bastia and 1325 Vs 1213Wh/m² to Corte). On hourly case, the results were still satisfactory, and widely better than persistence (RMSE=138.8 Vs 109.3 Wh/m² to Bastia and 135.1 Vs 114.7 Wh/m² to Corte). The last experiment was to evaluate the accuracy of our simulator on a PV power grid localized at 10 km from the station of Ajaccio. We got errors very suitable (nRMSE=27.9%, RMSE=99.0 W.h) compared to those obtained with the persistence (nRMSE=42.2%, RMSE=149.7 W.h).

Source :
http://www.photovoltaic-conference.com

The Developpers' Days meetings aims at gathering developpers from the Decision Deck community to coordinate developpment and implementation of the sofware platform.

We had presented our projet : "Development of applications to assist multi-participatory decision process: the MECADEPPE project". Our aim is to propose the development of software tools for aiding the location of wind farms and photovoltaic projects (GIS, 3D visualization, multicriteria comparator of scenarios) and for assisting the energy policy monitoring (effectiveness, efficiency).

More information
2nd Decision Deck Developers Days
Decision Deck
École Centrale