In recent years, machine learning has proven to be a powerful tool for deriving insights from
data. In this review, we describe ways in which machine learning has been leveraged to …

Despite the advances in solar forecasting methods, and their ever-increasing accuracy, little
is known about their value for real applications, eg, bidding in the electricity market, power …

Using Artificial Intelligence to Improve Real-Time Decision-Making for High-Impact Weather
in: Bulletin of the American Meteorological Society Volume 98 Issue 10 (2017) Jump to …

Solar energy is one of the most promising new energy sources, and making full use of it is
the main way to reduce carbon emissions. The prediction of short-term solar radiation is of …

Entrainment and detrainment rates (ε and δ) constitute the most critical free parameters in
mass flux schemes commonly employed for cumulus parameterizations. Recently, Zhu et …

To blend growing amounts of power from renewable resources into utility operations
requires accurate forecasts. For both day ahead planning and real-time operations, the …

This study presents a high-resolution spatial and temporal assessment of the solar energy
resources over the Arabian Peninsula (AP) from 38 years (1980–2017) reanalysis data …

The growing integration level of wind and solar energy resources introduces new regulating
and operating challenges in the electric grid. Ramp-rate limits of conventional power plants …

A key issue in integrating solar power into the grid is short-term forecasting. Up to now, most
solar forecasting has been run in the time domain. But since the data are dominated by the …

Different entrainment–mixing processes can occur in clouds; however, a homogeneous
mixing mechanism is often implicitly assumed in most commonly used microphysics …