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A systematic review and meta-analysis of machine learning, deep learning, and ensemble learning approaches in predicting EV charging behavior
Abstract Machine learning (ML) and deep learning (DL) have enabled algorithms to
autonomously acquire knowledge from data, facilitating predictive and decision-making …
autonomously acquire knowledge from data, facilitating predictive and decision-making …
[HTML][HTML] Electric vehicle hosting capacity analysis: Challenges and solutions
The significant rise of electric vehicles (EVs) and distributed energy resources (DERs) poses
critical challenges to the distribution systems for maintaining statutory limits of technical and …
critical challenges to the distribution systems for maintaining statutory limits of technical and …
Hybrid genetic algorithm-simulated annealing based electric vehicle charging station placement for optimizing distribution network resilience
Rapid placement of electric vehicle charging stations (EVCSs) is essential for the
transportation industry in response to the growing electric vehicle (EV) fleet. The widespread …
transportation industry in response to the growing electric vehicle (EV) fleet. The widespread …
[HTML][HTML] Electric vehicle charging technologies, infrastructure expansion, grid integration strategies, and their role in promoting sustainable e-mobility
The transport sector is experiencing a notable transition towards sustainability, propelled by
technological progress, innovative materials, and a dedication to environmental …
technological progress, innovative materials, and a dedication to environmental …
[HTML][HTML] Exploring potential storage-based flexibility gains of electric vehicles in smart distribution grids
Flexibility is one of the most important solutions for facilitating the variability of renewable
energy sources (RESs) in a distribution network. It is predicted that electric vehicles (EVs) …
energy sources (RESs) in a distribution network. It is predicted that electric vehicles (EVs) …
Placement and capacity of EV charging stations by considering uncertainties with energy management strategies
At the present context, Plug-in electric vehicles (PEVs) are gaining popularity in the
automotive industry due to their low CO2 emissions, simple maintenance, and low operating …
automotive industry due to their low CO2 emissions, simple maintenance, and low operating …
[HTML][HTML] A critical review of the effect of light duty electric vehicle charging on the power grid
Electric vehicles (EVs) have emerged as one of the alternative solutions for reducing carbon
emissions in the road transportation sector. In the near future, more and more EVs will be …
emissions in the road transportation sector. In the near future, more and more EVs will be …
[HTML][HTML] Multi-objective stochastic techno-economic-environmental optimization of distribution networks with G2V and V2G systems
Plug-in electric vehicles (PEVs) are one of the most promising technologies for
decarbonizing the transportation sector towards the global Net-zero target. However …
decarbonizing the transportation sector towards the global Net-zero target. However …
Utilization of EV charging station in demand side management using deep learning method
Conventional energy sources are a major source of pollution. Major efforts are being made
by global organizations to reduce CO2 emissions. Research shows that by 2030, EVs can …
by global organizations to reduce CO2 emissions. Research shows that by 2030, EVs can …
Energy management in microgrids using transactive energy control concept under high penetration of renewables; a survey and case study
Abstract Transactive Energy Control (TEC) paradigm enables involving Microgrids (MGs) in
the energy management procedure to realize the transition of energy systems using market …
the energy management procedure to realize the transition of energy systems using market …