Attentive primal-dual policy optimization for grid-constrained charging guidance of heterogeneous electric vehicle fleets

Optimal and efficient planning of charging stations for electric vehicles in urban areas: formulation, complexity and solutions

10.1016/j.eswa.2023.120442 · doi-reference

Effective charging planning based on deep reinforcement learning for electric vehicles

10.1109/tits.2020.3002271 · doi-reference

Real-time fast charging station recommendation for electric vehicles in coupled power-transportation networks: a graph reinforcement learning method

10.1016/j.ijepes.2022.108030 · doi-reference

A graph reinforcement learning-based decision-making platform for real-time charging navigation of urban electric vehicles

10.1109/tii.2022.3210264 · doi-reference

User cost minimization and load balancing for multiple electric vehicle charging stations based on deep reinforcement learning

10.3390/wevj16030184 · doi-reference

Development and evaluation of a smart charging strategy for an electric vehicle fleet based on reinforcement learning

10.1016/j.apenergy.2020.116382 · doi-reference

Global drive toward net-zero emissions and sustainability via electric vehicles: an integrative critical review

10.1007/s40974-024-00351-7 · doi-reference

Pandapower—an open-source python tool for convenient modeling, analysis, and optimization of electric power systems

10.1109/tpwrs.2018.2829021 · doi-reference

Learning to predict by the methods of temporal differences

10.1023/a:1022633531479 · doi-reference

Robust scheduling of electric vehicle charging in LV distribution networks under uncertainty

10.1109/tia.2020.2983906 · doi-reference

Electric vehicle charging guidance strategy considering “traffic network-charging station-driver” modeling: a multiagent deep reinforcement learning-based approach

10.1109/tte.2023.3322685 · doi-reference

A distributed EV navigation strategy considering the interaction between power system and traffic network

10.1109/tsg.2020.2965568 · doi-reference

Learning representations by back-propagating errors

10.1038/323533a0 · doi-reference

Deep reinforcement learning for EV charging navigation by coordinating smart grid and intelligent transportation system

10.1109/tsg.2019.2942593 · doi-reference

An efficient method for computing traffic equilibria in networks with asymmetric transportation costs

10.1287/trsc.18.2.185 · doi-reference

A decision-making framework for the smart charging of electric vehicles considering the priorities of the driver

10.3390/en13226120 · doi-reference

Toward multiple-phase MDP model for charging station recommendation

10.1109/tits.2021.3094926 · doi-reference

Online prediction-assisted safe reinforcement learning for electric vehicle charging station recommendation in dynamically coupled transportation-power systems

10.1016/j.trc.2025.105155 · doi-reference

Multi-agent graph reinforcement learning method for electric vehicle on-route charging guidance in coupled transportation electrification

10.1109/tste.2023.3330842 · doi-reference

Deep reinforcement learning based optimal route and charging station selection

10.3390/en13236255 · doi-reference

On-demand valet charging for electric vehicles: economic equilibrium, infrastructure planning and regulatory incentives

10.1016/j.trc.2022.103669 · doi-reference

New paradigm of sustainable urban mobility: electric and autonomous vehicles—a review and bibliometric analysis

10.3390/su14159525 · doi-reference

Deep reinforcement learning-based strategy for charging station participating in demand response

10.1016/j.apenergy.2022.120140 · doi-reference

Voltage-based droop control of electric vehicles in distribution grids under different charging power levels

10.3390/en14133905 · doi-reference

Electric vehicle entire-trip navigation and charging reservation method based on a high-speed communication network

10.1016/j.ijepes.2023.109070 · doi-reference

Long short-term memory

10.1162/neco.1997.9.8.1735 · doi-reference

A data driven typology of electric vehicle user types and charging sessions

10.1016/j.trc.2020.102637 · doi-reference

A user-preference-based charging station recommendation for electric vehicles

10.1109/tits.2024.3379469 · doi-reference

Impact of optimal electric vehicle charging station placement on distribution network performance: a comparative study

10.1109/access.2026.3696427 · doi-reference

Combining market-based control with distribution grid constraints when coordinating electric vehicle charging

10.15302/j-eng-2015095 · doi-reference

Flexible economic energy management including environmental indices in heat and electrical microgrids considering heat pump with renewable and storage systems

10.1038/s41598-025-19416-6 · doi-reference

Multi-agent DDPG based electric vehicles charging station recommendation

10.3390/en16166067 · doi-reference

A new approach for optimum simultaneous multi-DG distributed generation units placement and sizing based on maximization of system loadability using HPSO (hybrid particle swarm optimization) algorithm

10.1016/j.energy.2013.12.037 · doi-reference

A fuzzy-multi attribute decision making scheme for efficient user-centric EV charging station selection

10.1109/access.2024.3487839 · doi-reference

Optimal charging/discharging management strategy for electric vehicles

10.1016/j.apenergy.2024.123187 · doi-reference

Smart city charging station allocation for electric vehicles using analytic hierarchy process and multiobjective goal-programming

10.1016/j.apenergy.2024.123775 · doi-reference