Accurate prediction of renewable energy output is essential for integrating sustainable
energy sources into the grid, facilitating a transition towards a more resilient energy …

Climate change is recognized as one of the most significant challenge of the 21st century.
Anthropogenic activities have led to a substantial increase in greenhouse gases (GHGs) …

The advancement of sustainable energy sources necessitates the development of robust
forecasting tools for efficient energy management. A prominent player in this domain, solar …

Forecasting solar power production accurately is critical for effectively planning and
managing renewable energy systems. This paper introduces and investigates novel hybrid …

The fourth energy revolution is characterized by the incorporation of renewable energy
supplies into intelligent networks. As the world is shifting towards cleaner energy sources …

This paper reviews the advancements in machine learning techniques for enhanced solar
power generation forecasting. Solar energy, a potent alternative to traditional energy …

Solar energy has emerged as a clean and sustainable alternative to conventional energy
sources, making it a preferred choice for widespread integration into power grids. Despite its …

Renewable energy sources like solar, wind, and hydroelectric power are gaining popularity
as we work towards a more sustainable future. However, their intermittent and often …

Solar and wind energy forecasting is vital for efficient energy management and sustainable
power grid operations. This chapter explores machine learning (ML) algorithms for solar and …

As solar photovoltaic (PV) generation becomes cost-effective, solar power comes into its
own as the alternative energy with the potential to make up a larger share of growing energy …