Traffic prediction with high accuracy has significance towards traffic facilities scheduling,
adaptive traffic control logic, even the urban economic development. EV charging station …

This article proposes the operating status prediction model at electric vehicle (EV) charging
stations based on the spatiotemporal graph convolutional network (SGCN). The SGCN …

Electric Vehicle (EV) charging demand and charging station availability forecasting is one of
the challenges in the intelligent transportation system. With accurate EV station availability …

Electric Vehicles (EVs) and corresponding charging stations have been widely popularized,
increasing the power grid's operational risk and pressure, especially for the distribution …

The charging patterns of plug-in electric vehicle (PEV) owners have a substantial impact on
the distribution network's reliability. Uncertainty over arrival and departure dates makes …

Short-term prediction of the Electric Vehicle (EV) charging demand is of great importance to
the operation of EV fleets and charging stations. This paper develops a Long Short-Term …

Short-term load forecasting is a key task to maintain the stable and effective operation of
power systems, providing reasonable future load curve feeding to the unit commitment and …

With an increasing number of electric vehicles, the accurate forecasting of charging station
occupation is crucial to enable reliable vehicle charging. This paper introduces a novel …

Electric vehicles (EVs) have long been recognized as a solution to the shortage of fossil
fuels and the environmental problems associated with increasing CO2 emissions. However …

Abstract Short-term Electric Vehicle (EV) charging demand prediction is an essential task in
the fields of smart grid and intelligent transportation systems, as understanding the …