The sustainable energy transition taking place in the 21st century requires a major
revam** of the energy sector. Improvements are required not only in terms of the …

Renewable energy is essential for planet sustainability. Renewable energy output
forecasting has a significant impact on making decisions related to operating and managing …

Climate change is one of the greatest challenges facing humanity, and we, as machine
learning (ML) experts, may wonder how we can help. Here we describe how ML can be a …

The rapid variation of clouds is the main factor that causes the fluctuation of photovoltaic
power. 1 The satellite images contain plenty of information about clouds, applicable for …

The volatile behavior of solar energy is the biggest challenge in its successful integration
with existing grid systems. Accurate global horizontal irradiance (GHI) forecasting can …

The benefits of renewable energy are that it is sustainable and is low in environmental
pollution. Growing load requirement, global warming, and energy crisis need energy …

Renewable energy forecasting is crucial for integrating variable energy sources into the grid.
It allows power systems to address the intermittency of the energy supply at different …

Nowadays, learning-based modeling system is adopted to establish an accurate prediction
model for renewable energy resources. Computational Intelligence (CI) methods have …

This paper designs a hybridized deep learning framework that integrates the Convolutional
Neural Network for pattern recognition with the Long Short-Term Memory Network for half …

With the increase of solar photovoltaic (PV) penetration in power system, the impact of
random fluctuation of PV power on the secure operation of power grid becomes more and …