Statistical postprocessing techniques are nowadays key components of the forecasting
suites in many national meteorological services (NMS), with, for most of them, the objective …

Since the inception of competitive power markets two decades ago, electricity price
forecasting (EPF) has gradually become a fundamental process for energy companies' …

Ensemble weather predictions require statistical postprocessing of systematic errors to
obtain reliable and accurate probabilistic forecasts. Traditionally, this is accomplished with …

The use of renewable energy resources, especially wind power, is receiving strong attention
from governments and private institutions, since it is considered one of the best and most …

Fusing probabilistic information is a fundamental task in signal and data processing with
relevance to many fields of technology and science. In this work, we investigate the fusion of …

Postprocessing ensemble weather predictions to correct systematic errors has become a
standard practice in research and operations. However, only a few recent studies have …

There is rising interest in probabilistic forecasting to mitigate risks from solar power
uncertainty, but the numerical weather prediction (NWP) ensembles readily available to …

Accurate wind forecasts for one day ahead or longer periods have significant impacts on the
safe and efficient dispatch of power grids, where Numerical Weather Prediction (NWP) …

Short-term probabilistic wind power forecasting can provide critical quantified uncertainty
information of wind generation for power system operation and control. It would be difficult to …

The value of ensemble forecasts is well documented. However, postprocessing by statistical
methods is usually required to make forecasts reliable in a probabilistic sense. In this work a …