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 …
Review of electric vehicles integration impacts in distribution networks: Placement, charging/discharging strategies, objectives and optimisation models
Vehicles around the world are being converted to electric power in order to combat climate
change and lower pollution levels. Sustaining this process calls for more electric vehicle …
change and lower pollution levels. Sustaining this process calls for more electric vehicle …
Charging and discharging of electric vehicles in power systems: An updated and detailed review of methods, control structures, objectives, and optimization …
As a result of fossil fuel prices and the associated environmental issues, electric vehicles
(EVs) have become a substitute for fossil-fueled vehicles. Their use is expected to grow …
(EVs) have become a substitute for fossil-fueled vehicles. Their use is expected to grow …
A survey of battery swap** stations for electric vehicles: Operation modes and decision scenarios
H Wu - IEEE Transactions on Intelligent Transportation …, 2021 - ieeexplore.ieee.org
The population of electric vehicles (EVs) has grown rapidly over the past decade due to the
development of EV technologies, battery materials, charger facilities, and public charging …
development of EV technologies, battery materials, charger facilities, and public charging …
A systematic survey on demand response management schemes for electric vehicles
The unprecedented proliferation of electric vehicles is envisioned to revolutionize the
Intelligent Transportation System as an energy-efficient and environment-friendly alternative …
Intelligent Transportation System as an energy-efficient and environment-friendly alternative …
Vehicle-to-grid aggregator to support power grid and reduce electric vehicle charging cost
This paper presents an optimised bidirectional Vehicle-to-Grid (V2G) operation, based on a
fleet of Electric Vehicles (EVs) connected to a distributed power system, through a network of …
fleet of Electric Vehicles (EVs) connected to a distributed power system, through a network of …
[HTML][HTML] Smart grid evolution: Predictive control of distributed energy resources—A review
As the smart grid evolves, it requires increasing distributed intelligence, optimization and
control. Model predictive control (MPC) facilitates these functionalities for smart grid …
control. Model predictive control (MPC) facilitates these functionalities for smart grid …
Comprehensive review of electric vehicle technology and its impacts: Detailed investigation of charging infrastructure, power management, and control techniques
Electric vehicles (EVs) are universally recognized as an incredibly effective method of
lowering gas emissions and dependence on oil for transportation. Electricity, rather than …
lowering gas emissions and dependence on oil for transportation. Electricity, rather than …
Electric vehicle charging service operations: A review of machine learning applications for infrastructure planning, control, pricing and routing
The majority of global road transportation emissions come from passenger and freight
vehicles. Electric vehicles (EV) provide a sustainable transportation way, but customers' …
vehicles. Electric vehicles (EV) provide a sustainable transportation way, but customers' …
A cooperative hierarchical multi-agent system for EV charging scheduling in presence of multiple charging stations
The increasing penetration of plug-in electric vehicles (EVs) to the electrical grid raises
concerns over secure and economic operation of the system. A coordination mechanism …
concerns over secure and economic operation of the system. A coordination mechanism …