With the rapid advancement of technology in the energy sector and the demand for
sustainable energy practices, the world is aiming at fostering the hydrogen economy and …

In this study, a novel deep solar forecasting approach is proposed based on the complete
ensemble empirical mode decomposition with adaptive noise (CEEMDAN), continuous …

As a kind of clean energy, solar energy occupies a pivotal position in energy applications.
Accurate and reliable solar radiation prediction is critical to the application of solar energy. In …

As the penetration rate of solar energy in the grid continues to enhance, solar power
photovoltaic generation forecasts have become an indispensable aspect of mechanism …

Owing to the continuous increase in the proportion of solar generation accounting for the
total global generation, real-time management of solar power has become indispensable …

As the proportion of photovoltaic (PV) power generation rapidly increases, accurate PV
output power prediction becomes more crucial to energy efficiency and renewable energy …

In recent years, forecasting has received increasing attention since it provides an important
basis for the effective operation of power systems. In this paper, a hybrid method, composed …

A new machine learning approach for forecasting short-termsolar irradiance is presented in
this paper considering different weather conditions and time horizon in a microgrid …

Solar irradiation maps are fundamental geospatial datasets that have been used in a variety
of research fields. However, it is difficult to estimate the continuous distribution of solar …

Surrogate models play a vital role in overcoming the computational challenge in designing
and analyzing nonlinear dynamic systems, especially in the presence of uncertainty. This …