Bearing in mind European Green Deal assumptions regarding a significant reduction of
green house emissions, electricity generation from Renewable Energy Sources (RES) is …

Probabilistic solar forecasts may take the form of predictive probability distributions,
ensembles, quantiles, or interval forecasts. State-of-the-art approaches build on input from …

PV power forecasting models are predominantly based on machine learning algorithms
which do not provide any insight into or explanation about their predictions (black boxes) …

The interest for co-located wind and solar photovoltaic (PV) parks, also known as hybrid
power parks (HPPs), is increasing both in industry and in the scientific community. Co …

This paper presents a first step in the field of probabilistic forecasting of co-located wind and
photovoltaic (PV) parks. The effect of aggregation is analyzed with respect to forecast …

The work explores the opportunities offered by higher temperature heat transfer/heat storage
fluids, and higher temperature power cycles, in higher concentration solar thermal power …

The association of different variable renewable technologies in hybrid power plants and the
benefits of their aggregation for the operation of power systems is an area of recent …

Insular power systems are a special case of infrastructure for power production due to their
particular land morphology with extensive hills and ridges. For a higher renewable energy …

A modern renewable energy forecasting system blends physical models with artificial
intelligence to aid in system operation and grid integration. This paper describes such a …

Wind and solar energy are vital to the global transition toward sustainable energy systems,
driven by the need to reduce fossil fuel dependence, mitigate climate change, and enhance …