The augmentation of renewable energy sources within the global energy portfolio is
imperative for mitigating the impacts of climate change. Nonetheless, the inherent variability …

To mitigate the adverse effects of climate change, the power sector is rapidly transitioning
towards decarbonization through the integration of renewable energy sources, such as wind …

The paper addresses the imperative requirement for precise forecasting of intermittent
renewable energy sources, specifically wind and solar, to facilitate their integration into …

The use of renewable energy sources (RESs) at the distribution level has become
increasingly appealing in terms of costs and technology, expecting a massive diffusion in the …

High penetration of renewable energy such as wind power and photovoltaic (PV) requires
large amounts of flexibility to balance their inherent variability. Making an accurate …

This study introduces a methodology for the Uncertainty Analysis of the Canadian power
system, leveraging ML techniques. Specifically, we seek to uncover nonlinear behaviors and …

The operation and planning of large-scale power systems are becoming more challenging
with the increasing penetration of stochastic renewable generation. In order to minimize the …

The global energy landscape is rapidly shifting towards renewable sources, notably
photovoltaic (PV) installations. However, the PV reliance on meteorological conditions …

The increasing integration of renewable energy sources into smart energy grids presents
significant challenges in maintaining grid stability and optimizing energy distribution …

This paper addresses the challenge of accurately forecasting solar power generation (SPG)
across multiple sites using a single common model. The proposed deep learning-based …