Buchumschlag

Safety-Aware Reinforcement Learning for Electric Vehicle Charging Station Management in Distribution Network

Fuente: arXiv

Gespeichert in:

Bibliographische Detailangaben
Hauptverfasser:	Fan, Jiarong, Liebman, Ariel, Wang, Hao
Format:	Preprint
Veröffentlicht:	2024
Schlagworte:	Systems and Control Artificial Intelligence Optimization and Control
Online-Zugang:	Acceder al recurso
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Ähnliche Einträge

Agent-Based Decentralized Energy Management of EV Charging Station with Solar Photovoltaics via Multi-Agent Reinforcement Learning
von: Fan, Jiarong, et al.
Veröffentlicht: (2025)

Safe Decentralized Operation of EV Virtual Power Plant with Limited Network Visibility via Multi-Agent Reinforcement Learning
von: Huang, Chenghao, et al.
Veröffentlicht: (2026)

Large Language Model-Assisted Planning of Electric Vehicle Charging Infrastructure with Real-World Case Study
von: Zheng, Xinda, et al.
Veröffentlicht: (2025)

Dynamic Rolling Horizon Optimization for Network-Constrained V2X Value Stacking of Electric Vehicles Under Uncertainties
von: Jiang, Canchen, et al.
Veröffentlicht: (2025)

Dynamics and Optimization in Spatially Distributed Electrical Vehicle Charging
von: Paganini, Fernando, et al.
Veröffentlicht: (2024)

Controlling Large Electric Vehicle Charging Stations via User Behavior Modeling and Stochastic Programming
von: Puech, Alban, et al.
Veröffentlicht: (2024)

Aero-Promptness: Drag-Aware Aerodynamic Manipulability for Propeller-driven Vehicles
von: Franchi, Antonio
Veröffentlicht: (2026)

Human-in-the-Loop AI for HVAC Management Enhancing Comfort and Energy Efficiency
von: Liang, Xinyu, et al.
Veröffentlicht: (2025)

Distributionally Robust Safety Verification of Neural Networks via Worst-Case CVaR
von: Kishida, Masako
Veröffentlicht: (2025)

Performance-Aware Self-Configurable Multi-Agent Networks: A Distributed Submodular Approach for Simultaneous Coordination and Network Design
von: Xu, Zirui, et al.
Veröffentlicht: (2024)

Distributionally Robust Control with End-to-End Statistically Guaranteed Metric Learning
von: Wu, Jingyi, et al.
Veröffentlicht: (2025)

Approximate Model Predictive Control for Microgrid Energy Management via Imitation Learning
von: Liu, Changrui, et al.
Veröffentlicht: (2025)

Model Predictive Control and Reinforcement Learning: A Unified Framework Based on Dynamic Programming
von: Bertsekas, Dimitri P.
Veröffentlicht: (2024)

Lyapunov Function Consistent Adaptive Network Signal Control with Back Pressure and Reinforcement Learning
von: Ma, Chaolun, et al.
Veröffentlicht: (2022)

Deep Reinforcement Learning Optimization for Uncertain Nonlinear Systems via Event-Triggered Robust Adaptive Dynamic Programming
von: Bai, Ningwei, et al.
Veröffentlicht: (2025)

Hierarchical Deep Reinforcement Learning Framework for Multi-Year Asset Management Under Budget Constraints
von: Fard, Amir, et al.
Veröffentlicht: (2025)

Deep Reinforcement Learning for Multi-Objective Optimization: Enhancing Wind Turbine Energy Generation while Mitigating Noise Emissions
von: de Frutos, Martín, et al.
Veröffentlicht: (2024)

Asynchronous Distributed Reinforcement Learning for LQR Control via Zeroth-Order Block Coordinate Descent
von: Jing, Gangshan, et al.
Veröffentlicht: (2021)

Faster Reinforcement Learning by Freezing Slow States
von: Wang, Yijia, et al.
Veröffentlicht: (2023)

Integrated Optimization of Power Split, Engine Thermal Management, and Cabin Heating for Hybrid Electric Vehicles
von: Gong, Xun, et al.
Veröffentlicht: (2019)

Hierarchical Reinforcement Learning with Low-Level MPC for Multi-Agent Control
von: Studt, Max, et al.
Veröffentlicht: (2025)

Resource-Aware Distributed Submodular Maximization: A Paradigm for Multi-Robot Decision-Making
von: Xu, Zirui, et al.
Veröffentlicht: (2022)

Energy Management for Renewable-Colocated Artificial Intelligence Data Centers
von: Li, Siying, et al.
Veröffentlicht: (2025)

Distributionally Robust Free Energy Principle for Decision-Making
von: Shafiei, Allahkaram, et al.
Veröffentlicht: (2025)

Electric Vehicle Routing Problem for Emergency Power Supply: Towards Telecom Base Station Relief
von: Kikuta, Daisuke, et al.
Veröffentlicht: (2024)

Communication- and Computation-Efficient Distributed Submodular Optimization in Robot Mesh Networks
von: Xu, Zirui, et al.
Veröffentlicht: (2024)

Emission-Aware Reinforcement Learning for Sustainable Electric Vehicle Charging and Carbon Dioxide Reduction Under Varying Renewable Penetration
von: Ou, Ninglin, et al.
Veröffentlicht: (2026)

Temporal Difference Learning with Compressed Updates: Error-Feedback meets Reinforcement Learning
von: Mitra, Aritra, et al.
Veröffentlicht: (2023)

Network-Aware Value Stacking of Community Battery via Asynchronous Distributed Optimization
von: Jiang, Canchen, et al.
Veröffentlicht: (2024)

Action Dependency Graphs for Globally Optimal Coordinated Reinforcement Learning
von: Ding, Jianglin, et al.
Veröffentlicht: (2025)

GLinSAT: The General Linear Satisfiability Neural Network Layer By Accelerated Gradient Descent
von: Zeng, Hongtai, et al.
Veröffentlicht: (2024)

Reinforcement Learning for Distributed Transient Frequency Control with Stability and Safety Guarantees
von: Yuan, Zhenyi, et al.
Veröffentlicht: (2022)

ART for Diffusion Sampling: A Reinforcement Learning Approach to Timestep Schedule
von: Huang, Yilie, et al.
Veröffentlicht: (2026)

CORL: Reinforcement Learning of MILP Policies Solved via Branch and Bound
von: Anand, Akhil S, et al.
Veröffentlicht: (2025)

Koopman Operator-based Detection-Isolation of Cyberattack: A Case Study on Electric Vehicle Charging
von: Ghosh, Sanchita, et al.
Veröffentlicht: (2024)

Safe Control and Learning Using Generalized Action Governor
von: Fang, Peiyuan, et al.
Veröffentlicht: (2022)

Nonlinear Control Allocation: A Learning Based Approach
von: Khan, Hafiz Zeeshan Iqbal, et al.
Veröffentlicht: (2022)

Approximate Information States for Worst-Case Control and Learning in Uncertain Systems
von: Dave, Aditya, et al.
Veröffentlicht: (2023)

Instance-Aware Parameter Configuration in Bilevel Late Acceptance Hill Climbing for the Electric Capacitated Vehicle Routing Problem
von: Qin, Yinghao, et al.
Veröffentlicht: (2026)

Q-Learning for Stochastic Control under General Information Structures and Non-Markovian Environments
von: Kara, Ali Devran, et al.
Veröffentlicht: (2023)