| Review of solar irradiance forecasting methods and a proposition for small-scale insular grids M Diagne, M David, P Lauret, J Boland, N Schmutz Renewable and Sustainable Energy Reviews 27, 65-76, 2013 | 1058 | 2013 |
| Modelling of diffuse solar fraction with multiple predictors B Ridley, J Boland, P Lauret Renewable Energy 35 (2), 478-483, 2010 | 396 | 2010 |
| A benchmarking of machine learning techniques for solar radiation forecasting in an insular context P Lauret, C Voyant, T Soubdhan, M David, P Poggi Solar Energy 112, 446-457, 2015 | 308 | 2015 |
| Probabilistic forecasting of the solar irradiance with recursive ARMA and GARCH models M David, F Ramahatana, PJ Trombe, P Lauret Solar Energy 133, 55-72, 2016 | 293 | 2016 |
| Bayesian neural network approach to short time load forecasting P Lauret, E Fock, RN Randrianarivony, JF Manicom-Ramsamy Energy conversion and management 49 (5), 1156-1166, 2008 | 272 | 2008 |
| Verification of deterministic solar forecasts D Yang, S Alessandrini, J Antonanzas, F Antonanzas-Torres, V Badescu, ... Solar Energy 210, 20-37, 2020 | 262 | 2020 |
| Combining solar irradiance measurements, satellite-derived data and a numerical weather prediction model to improve intra-day solar forecasting LM Aguiar, B Pereira, P Lauret, F Díaz, M David Renewable Energy 97, 599-610, 2016 | 201 | 2016 |
| Spatial and temporal variability of solar energy R Perez, M David, TE Hoff, M Jamaly, S Kivalov, J Kleissl, P Lauret, ... Foundations and Trends® in Renewable Energy 1 (1), 1-44, 2016 | 171 | 2016 |
| Verification of solar irradiance probabilistic forecasts P Lauret, M David, P Pinson Solar Energy 194, 254-271, 2019 | 159 | 2019 |
| Assessment of machine learning techniques for deterministic and probabilistic intra-hour solar forecasts HTC Pedro, CFM Coimbra, M David, P Lauret Renewable Energy 123, 191-203, 2018 | 159 | 2018 |
| Post-processing of solar irradiance forecasts from WRF model at Reunion Island M Diagne, M David, J Boland, N Schmutz, P Lauret Solar Energy 105, 99-108, 2014 | 152 | 2014 |
| A node pruning algorithm based on a Fourier amplitude sensitivity test method P Lauret, E Fock, TA Mara IEEE transactions on neural networks 17 (2), 273-293, 2006 | 146 | 2006 |
| Use of satellite data to improve solar radiation forecasting with Bayesian Artificial Neural Networks LM Aguiar, B Pereira, M David, F Díaz, P Lauret Solar Energy 122, 1309-1324, 2015 | 143 | 2015 |
| Sky temperature modelisation and applications in building simulation L Adelard, F Pignolet-Tardan, T Mara, P Lauret, F Garde, H Boyer Renewable Energy 15 (1-4), 418-430, 1998 | 143 | 1998 |
| Probabilistic solar forecasting using quantile regression models P Lauret, M David, HTC Pedro energies 10 (10), 1591, 2017 | 128 | 2017 |
| Building energy efficiency and thermal comfort in tropical climates: Presentation of a numerical approach for predicting the percentage of well-ventilated living spaces in … A Bastide, P Lauret, F Garde, H Boyer Energy and buildings 38 (9), 1093-1103, 2006 | 127 | 2006 |
| Solar irradiation forecasting: state-of-the-art and proposition for future developments for small-scale insular grids HM Diagne, P Lauret, M David WREF 2012-World Renewable Energy Forum, 2012 | 115 | 2012 |
| Evaluating tilted plane models for solar radiation using comprehensive testing procedures, at a southern hemisphere location M David, P Lauret, J Boland Renewable Energy 51, 124-131, 2013 | 88 | 2013 |
| A Bayesian neural network approach to estimating the energy equivalent speed C Riviere, P Lauret, JFM Ramsamy, Y Page Accident Analysis & Prevention 38 (2), 248-259, 2006 | 88 | 2006 |
| Comparison of intraday probabilistic forecasting of solar irradiance using only endogenous data M David, MA Luis, P Lauret International journal of forecasting 34 (3), 529-547, 2018 | 87 | 2018 |
