Review on scheduling, clustering, and forecasting strategies for controlling electric vehicle charging: Challenges and recommendations

AS Al-Ogaili, TJT Hashim, NA Rahmat… - Ieee …, 2019 - ieeexplore.ieee.org
The usage and adoption of electric vehicles (EVs) have increased rapidly in the 21st century
due to the shifting of the global energy demand away from fossil fuels. The market …

Electric vehicle charging service operations: A review of machine learning applications for infrastructure planning, control, pricing and routing

N Fescioglu-Unver, MY Aktaş - Renewable and Sustainable Energy …, 2023 - Elsevier
The majority of global road transportation emissions come from passenger and freight
vehicles. Electric vehicles (EV) provide a sustainable transportation way, but customers' …

Charging demand forecasting model for electric vehicles based on online ride-hailing trip data

Q Xing, Z Chen, Z Zhang, X Huang, Z Leng, K Sun… - Ieee …, 2019 - ieeexplore.ieee.org
Electric vehicle (EV) has been popularized and promoted on a large scale because of its
clean and efficient features. Charging this increasing number of EVs is expected to have an …

Multi-agent deep reinforcement learning approach for EV charging scheduling in a smart grid

K Park, I Moon - Applied energy, 2022 - Elsevier
As the competitive advantages of electric vehicles, both in terms of operating costs and eco-
friendly characteristics have gained attention, the demand for electric vehicles has …

A novel LSTM based deep learning approach for multi-time scale electric vehicles charging load prediction

J Zhu, Z Yang, Y Chang, Y Guo, K Zhu… - 2019 IEEE Innovative …, 2019 - ieeexplore.ieee.org
Short-term load forecasting is an important issue in energy management system and a key
measure to maintain the stable and effective operation of power systems, providing …

Constrained EV charging scheduling based on safe deep reinforcement learning

H Li, Z Wan, H He - IEEE Transactions on Smart Grid, 2019 - ieeexplore.ieee.org
Electric vehicles (EVs) have been popularly adopted and deployed over the past few years
because they are environment-friendly. When integrated into smart grids, EVs can operate …

Electric vehicle optimum charging-discharging scheduling with dynamic pricing employing multi agent deep neural network

B Aljafari, PR Jeyaraj, AC Kathiresan… - Computers and Electrical …, 2023 - Elsevier
Abstract Electric Vehicles (EVs) are environmentally friendly. Extensive progress makes EVs
popularly deployed and adopted. Once EVs are connected to the smart grid, EVs can act as …

Electric vehicle charging management based on deep reinforcement learning

S Li, W Hu, D Cao, T Dragičević… - Journal of Modern …, 2021 - ieeexplore.ieee.org
A time-variable time-of-use electricity price can be used to reduce the charging costs for
electric vehicle (EV) owners. Considering the uncertainty of price fluctuation and the …

A deep generative model for non-intrusive identification of EV charging profiles

S Wang, L Du, J Ye, D Zhao - IEEE Transactions on Smart Grid, 2020 - ieeexplore.ieee.org
The proliferation of electric vehicles (EVs) brings environmental benefits and technical
challenges to power grids. An identification algorithm which can accurately extract individual …

Data-driven framework for large-scale prediction of charging energy in electric vehicles

Y Zhao, Z Wang, ZJM Shen, F Sun - Applied Energy, 2021 - Elsevier
Large-scale and high-precision predictions of the charging energy required for electric
vehicles (EVs) are essential to ensure the safety of EVs and provide reliable inputs for grid …