Nonparametric Bayesian-based recognition of solar irradiance conditions: Application to the generation of high temporal resolution synthetic solar irradiance data

Autor: Frimane, Âzeddine, Soubdhan, Ted, Bright, Jamie M., Aggour, Mohammed

Publikováno v: In Solar Energy April 2019 182:462-479

Use of BESTEST procedure to improve a building thermal simulation program

Autor: Soubdhan, Ted, Mara, Thierry Alex, Boyer, Harry, Younès, Anis

Publikováno v: World Renewable Energy Congress VI Renewables: The Energy for the 21st Century World Renewable Energy Congress VI 1-7 July 2000 Brighton, UK, Elsevier (Ed.) (2000) 1800-1803

Validation of building energy simulation programs is of major interest to both users and modellers. To achieve such a task, it is essential to apply a methodology based on a priori test and empirical validation. A priori test consists in verifying th

Externí odkaz: http://arxiv.org/abs/1212.5263

Extracting Statistical Properties of Solar and Photovoltaic Power Production for the Scope of Building a Sophisticated Forecasting Framework.

Autor: Ndong, Joseph¹ joseph.ndong@ucad.edu.sn, Soubdhan, Ted²

Publikováno v: Forecasting. Mar2023, Vol. 5 Issue 1, p1-21. 21p.

A robust forecasting framework based on the Kalman filtering approach with a twofold parameter tuning procedure: Application to solar and photovoltaic prediction

Autor: Soubdhan, Ted, Ndong, Joseph, Ould-Baba, Hanany, Do, Minh-Thang

Publikováno v: In Solar Energy June 2016 131:246-259

A benchmarking of machine learning techniques for solar radiation forecasting in an insular context

Autor: Lauret, Philippe, Voyant, Cyril, Soubdhan, Ted, David, Mathieu, Poggi, Philippe

Publikováno v: In Solar Energy February 2015 112:446-457