International audienceWe provide probabilistic forecasts of photovoltaic (PV) production, for several PV plants located in France up to 6 days of lead time, with a 30-min timestep. First, we derive multiple forecasts from numerical weather predictions (ECMWF and Météo France), including ensemble forecasts. Second, our parameter-free online learning technique generates a weighted combination of the production forecasts for each PV plant. The weights are computed sequentially before each forecast using only past information. Our strategy is to minimize the Continuous Ranked Probability Score (CRPS). We show that our technique provides forecast improvements for both deterministic and probabilistic evaluation tools
International audienceEnsemble forecasting resorts to multiple individual forecasts to produce a dis...
Uncertainty in the upcoming production of photovoltaic (PV) plants is a challenge for grid operation...
Photovoltaic systems are expected to play a key role in the planning and operation of future distrib...
International audienceWe provide probabilistic forecasts of photovoltaic (PV) production, for severa...
Our main objective is to improve the quality of photovoltaic power forecasts deriving from weather f...
Notre principal objectif est d'améliorer la qualité des prévisions de production d'énergie photovolt...
Photovoltaic power forecasting is nowadays a very active research topic both for industries and acad...
The penetration of nonprogrammable renewable energy sources, namely wind and solar technology, has g...
We provide a learning algorithm combining distributed Extreme Learning Machine and an information fu...
Photovoltaic (PV) generation is potentially uncertain. Probabilistic PV generation forecasting metho...
International audienceThe valorization of photovoltaic (PV) energy generation involves several decis...
International audienceWe provide a learning algorithm combining distributed Extreme Learning Machine...
Probabilistic forecasting accounts for the uncertainty in prediction that arises from inaccurate inp...
Abstract. Probabilistic forecasts account for the uncertainty in the pre-diction helping the decisio...
International audienceEnsemble forecasting resorts to multiple individual forecasts to produce a dis...
Uncertainty in the upcoming production of photovoltaic (PV) plants is a challenge for grid operation...
Photovoltaic systems are expected to play a key role in the planning and operation of future distrib...
International audienceWe provide probabilistic forecasts of photovoltaic (PV) production, for severa...
Our main objective is to improve the quality of photovoltaic power forecasts deriving from weather f...
Notre principal objectif est d'améliorer la qualité des prévisions de production d'énergie photovolt...
Photovoltaic power forecasting is nowadays a very active research topic both for industries and acad...
The penetration of nonprogrammable renewable energy sources, namely wind and solar technology, has g...
We provide a learning algorithm combining distributed Extreme Learning Machine and an information fu...
Photovoltaic (PV) generation is potentially uncertain. Probabilistic PV generation forecasting metho...
International audienceThe valorization of photovoltaic (PV) energy generation involves several decis...
International audienceWe provide a learning algorithm combining distributed Extreme Learning Machine...
Probabilistic forecasting accounts for the uncertainty in prediction that arises from inaccurate inp...
Abstract. Probabilistic forecasts account for the uncertainty in the pre-diction helping the decisio...
International audienceEnsemble forecasting resorts to multiple individual forecasts to produce a dis...
Uncertainty in the upcoming production of photovoltaic (PV) plants is a challenge for grid operation...
Photovoltaic systems are expected to play a key role in the planning and operation of future distrib...