Transportation electrification plays a crucial role in mitigating greenhouse gas (GHG)
emissions and enabling the decarbonization of power systems. However, current research …

The domain of Machine learning has experienced Substantial advancement and
development. Recently, showcasing a Broad spectrum of uses like Computational …

As electric vehicles (EVs) continue to rise in popularity, there has been an intensified focus
on the distribution of power within hybrid renewable energy systems. In this context, the …

The unprecedented proliferation of electric vehicles is envisioned to revolutionize the
Intelligent Transportation System as an energy-efficient and environment-friendly alternative …

Multi-agent deep reinforcement learning (MADRL) approaches are at the forefront of
contemporary research in optimum electric vehicle (EV) charging scheduling challenges …

Compared to traditional building energy systems, the energy systems used in nearly/net
zero energy buildings face more complex challenges due to highly uncertain characteristics …

Due to the recent advancements in the Internet of Things and data science techniques, a
wide range of studies have investigated the use of data mining (DM) and machine learning …

Integrating plug-in electric vehicles (PEVs) into the power and transport sectors can help to
reduce global CO2 emissions. This synergy can be achieved with advances in battery …

Technological developments bring their respective roles in all fields including libraries. One
of the technologies that can be utilized in libraries is artificial intelligence. In this study, the …

Vehicle-to-grid (V2G) systems play a key role in the integration of electric vehicles (EVs) into
smart grids by enabling bidirectional energy flows between EVs and the grid. Optimizing …