most citedDeep learning-based multi-output quantile forecasting of PV generation

13 citations · 13 across the 2 of their papers we have counts for

collaborators

5 papers

cs.LG202113 cited

Deep learning-based multi-output quantile forecasting of PV generation

Jonathan Dumas, Colin Cointe, Xavier Fettweis +1

This paper develops probabilistic PV forecasters by taking advantage of recent breakthroughs in deep learning. It tailored forecasting tool, named encoder-decoder, is implemented t…

math.OC2021

Probabilistic forecasting for sizing in the capacity firming framework

Jonathan Dumas, Bertrand Cornélusse, Xavier Fettweis +3

This paper proposes a strategy to size a grid-connected photovoltaic plant coupled with a battery energy storage device within the \textit{capacity firming} specifications of the F…

stat.AP2021

A Probabilistic Forecast-Driven Strategy for a Risk-Aware Participation in the Capacity Firming Market: extended version

Jonathan Dumas, Colin Cointe, Antoine Wehenkel +3

This paper addresses the energy management of a grid-connected renewable generation plant coupled with a battery energy storage device in the capacity firming market, designed to p…

physics.soc-ph2018

Critical Time Windows for Renewable Resource Complementarity Assessment

Mathias Berger, David Radu, Raphael Fonteneau +7

This paper proposes a systematic framework to assess the complementarity of renewable resources over arbitrary geographical scopes and temporal scales which is particularly well-su…

physics.ao-ph2018

Complementarity Assessment of South Greenland Katabatic Flows and West Europe Wind Regimes

David Radu, Mathias Berger, Raphaël Fonteneau +6

Current global environmental challenges require vigorous and diverse actions in the energy sector. One solution that has recently attracted interest consists in harnessing high-qua…