Abstract Machine learning (ML) and deep learning (DL) have enabled algorithms to
autonomously acquire knowledge from data, facilitating predictive and decision-making …

The indisputable environmental concerns have forced the imminent proliferation of
renewable energy sources (RES) and electric vehicles (EV). However, the high penetration …

The number of electric vehicles (EVs) is expected to increase significantly in the near future,
which will affect the operation of future power networks. This study investigates the impact of …

The variable natures of renewable power sources and the additional demand from EV
(electric vehicle)-charging present unique challenges to electrical grids. This paper explores …

Integrating water electrolysis and green electricity offers a promising approach towards
sustainable and clean energy. However, such a system demands electrodes that can swiftly …

Electric mobility is a sustainable alternative for mitigating carbon emissions by replacing the
conventional fleet. However, the low availability of data from charging stations makes …

To accommodate high penetration of fluctuating renewable power within the power grid,
thermal power plants often engage in load cycling dynamic processes. When thermal power …

The increasing integration of renewable energy resources in active distribution networks
(ADNs) aggravates voltage deviations. Fluctuations among distributed generators (DGs) and …

This paper addresses the challenges inherent in Microgrids (MGs), Renewable Energy
Sources (RES), and Plug-in Hybrid Electric Vehicles (PHEVs), presenting a pioneering …

The expansion of distributed generation and erratic loads create many challenges for
electricity distribution networks (DN), like grid congestion and load unbalance …