M
Mathieu David
Researcher at University of La Réunion
Publications - 69
Citations - 2939
Mathieu David is an academic researcher from University of La Réunion. The author has contributed to research in topics: Solar irradiance & Photovoltaic system. The author has an hindex of 25, co-authored 65 publications receiving 2277 citations.
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Journal ArticleDOI
Review of solar irradiance forecasting methods and a proposition for small-scale insular grids
TL;DR: In this article, the authors present an in-depth review of the current methods used to forecast solar irradiance in order to facilitate selection of the appropriate forecast method according to needs.
ReportDOI
Best Practices Handbook for the Collection and Use of Solar Resource Data for Solar Energy Applications: Second Edition
Alessandro Betti,Philippe Blanc,Mathieu David,Yves-Marie Saint-Drenan,Anton Driesse,Janine Freeman,Rafael Fritz,Christian A. Gueymard,Aron Habte,Jing Huang,Andreas Kazantzidis,Jan Kleissl,Carmen Köhler,Tomas Landelius,V. Lara-Fanego,Philippe Lauret,Elke Lorenz,Luis Cuadrado Martin,Mark Mehos,Richard Meyer,Daryl Meyers,Kristian Pagh Nielsen,Richard Perez,Carlos M. Fernández Peruchena,Jesús Polo,David Renné,Lourdes Ramirez,Jan Remund,J. A. Ruiz Arias,Manajit Sengupta,Manuel Silva,David Spieldenner,Thomas Stoffel,Marcel Suri,Stefan Wilbert,S. Wilcox,Frank Vignola,Ping Wang,Yu Xie,Luis F. Zarzalejo +39 more
TL;DR: In this article, the authors present detailed information about solar resource data and the resulting data products needed for each stage of a solar energy project, from initial site selection to systems operations.
Journal ArticleDOI
A benchmarking of machine learning techniques for solar radiation forecasting in an insular context
TL;DR: It is found 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.
Journal ArticleDOI
Probabilistic forecasting of the solar irradiance with recursive ARMA and GARCH models
TL;DR: This paper assesses the performances of a commonly used combination of two linear models (ARMA and GARCH) in econometrics in order to provide probabilistic forecasts of solar irradiance and the proposed model is able to perform point forecasts as accurately as other methods based on machine learning techniques.
Journal ArticleDOI
Verification of deterministic solar forecasts
Dazhi Yang,Stefano Alessandrini,J. Antonanzas,F. Antonanzas-Torres,Viorel Badescu,Hans Georg Beyer,Robert Blaga,John Boland,Jamie M. Bright,Carlos F.M. Coimbra,Mathieu David,Âzeddine Frimane,Christian A. Gueymard,Tao Hong,Merlinde Kay,Sven Killinger,Jan Kleissl,Philippe Lauret,Elke Lorenz,Dennis van der Meer,Marius Paulescu,Richard Perez,Oscar Perpiñán-Lamigueiro,Ian Marius Peters,David Renné,Yves-Marie Saint-Drenan,Yong Shuai,Ruben Urraca,Hadrien Verbois,Frank Vignola,Cyril Voyant,Jie Zhang +31 more
TL;DR: To analyze and compare solar forecasts, the well-established Murphy–Winkler framework for distribution-oriented forecast verification is recommended as a standard practice and the use of the root mean square error (RMSE) skill score based on the optimal convex combination of climatology and persistence methods is highly recommended.