2026

Key Questions on Energy and AI report cover
Report · 2026 Key Questions on Energy and AI

International Energy Agency (IEA)

A follow-up to the IEA's landmark Energy and AI report, examining how the energy–AI nexus has evolved amid surging data centre investment and rapid model capability advances.

2025

An Energy Sector Roadmap to Net Zero Emissions in Colombia report cover
Report · 2025 An Energy Sector Roadmap to Net Zero Emissions in Colombia

International Energy Agency (IEA)

A pathway for Colombia to achieve net zero greenhouse gas emissions by 2050.

World Energy Outlook 2025 report cover
Report · 2025 World Energy Outlook 2025

International Energy Agency (IEA)

The IEA's flagship World Energy Outlook — the most authoritative source of global energy analysis and projections.

Ice sheet elevation reconstruction using implicit neural representations illustration
Preprint · 2025 Implicit Neural Representation for Ice Sheet Surface Elevation Reconstruction to Assess Elevation Change in High-Spatiotemporal Resolution

Peter Naylor, Andreas Stokholm, Natalia Havelund Andersen, Nikolaos Dionelis, Quentin Paletta, Sebastian Bjerregaard Simonsen

A novel Implicit Neural Representation method trained on sparse satellite altimeter data (5% of the domain) to reconstruct missing ice surface elevation for Greenland's Petermann Glacier — an 84% improvement over baselines.

ASIMOV wildfire monitoring downscaling illustration
Preprint · 2025 Deep Learning-Based Downscaling of Seviri Data for High Spatial Resolution Near-Real-Time Wildfire Monitoring

Maria Dekavalla, Quentin Paletta, Chrysovalantis Tsiakos, Angelos Amditis

The ESA-funded ASIMOV project employs multimodal deep learning to enhance SEVIRI satellite data, achieving 1 km resolution for near-real-time wildfire monitoring, comparable to LEO sensors like MODIS.

2024

Sky image-based solar forecasting with multi-location data illustration
Paper · 2024 Sky image-based solar forecasting using deep learning with heterogeneous multi-location data: Dataset fusion versus transfer learning

Alessandro Sebastianelli, Federico Serva, Andrea Ceschini, Quentin Paletta, Massimo Panella, Bertrand Le Saux

Remote Sensing of Environment

Day-ahead surface solar irradiance forecasting using machine learning validated with in situ measurements of the Baseline Surface Radiation Network (BSRN).

Physics-informed transfer learning for solar forecasting illustration
Paper · 2024 Sky image-based solar forecasting using deep learning with heterogeneous multi-location data: Dataset fusion versus transfer learning

Yuhao Nie, Quentin Paletta, Andea Scott, Luis Martin Pomares, Guillaume Arbod, Sgouris Sgouridis, Joan Lasenby, Adam Brandt

Applied Energy

Comparative study between local training, global training, and transfer learning for solar nowcasting based on sky images.

SkyGPT synthetic sky image generation illustration
Paper · 2024 SkyGPT: Probabilistic Ultra-short-term Solar Forecasting Using Synthetic Sky Images from Physics-constrained VideoGPT

Yuhao Nie, Eric Zelikman, Andea Scott, Quentin Paletta, Adam Brandt

Advances in Applied Energy

A physics-informed stochastic video prediction model that generates multiple possible future sky images with diverse cloud motion patterns from past sky image sequences.

Open-source sky image datasets survey illustration
Paper · 2024 Open-source ground-based sky image datasets for very short-term solar forecasting, cloud analysis and modeling: A comprehensive survey

Yuhao Nie, Xiatong Li, Quentin Paletta, Max Aragon, Andea Scott, Adam Brandt

Renewable and Sustainable Energy Reviews

Comprehensive survey of 72 open-source ground-based sky image datasets for very short-term solar forecasting applications.

2023

2022

Paper · 2022 Cloud Flow Centring in Sky and Satellite Images for Deep Solar Forecasting

Quentin Paletta, Guillaume Arbod, Joan Lasenby

8th World Conference on Photovoltaic Energy Conversion

Processing method for cloud cover videos to consistently centre the polar representation on the incoming flow of clouds using an optical flow algorithm.

Paper · 2022 ECLIPSE: Envisioning CLoud Induced Perturbations in Solar Energy

Quentin Paletta, Anthony Hu, Guillaume Arbod, Joan Lasenby

Applied Energy

Novel deep learning architecture for solar irradiance and sky image prediction.

2021

Paper · 2021 Benchmarking of Deep Learning Irradiance Forecasting Models from Sky Images - An in-depth Analysis

Quentin Paletta, Guillaume Arbod, Joan Lasenby

Solar Energy

Benchmarking of standard deep learning models for solar power nowcasting using sky images.

2020

Paper · 2020 A Temporally Consistent Image-based Sun Tracking Algorithm for Solar Energy Forecasting Applications

Quentin Paletta, Joan Lasenby

NeurIPS 2020 - Tackling Climate Change with Machine Learning workshop

Sun tracking algorithm based on sky images only.