Image de couverture de livre

Robust Deep Reinforcement Learning for Inverter-based Volt-Var Control in Partially Observable Distribution Networks

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Liu, Qiong, Guo, Ye, Xu, Tong
Format:	Preprint
Publié:	2024
Sujets:	Systems and Control Artificial Intelligence
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Residual Deep Reinforcement Learning for Inverter-based Volt-Var Control
par: Liu, Qiong, et autres
Publié: (2024)

Reinforcement Learning Based Robust Volt/Var Control in Active Distribution Networks With Imprecisely Known Delay
par: Cheng, Hong, et autres
Publié: (2024)

Power Flow Solvability with Volt-Var Controlled Inverter-Based Resources
par: Khan, Taha Saeed, et autres
Publié: (2026)

Incremental Volt/Var Control for Distribution Networks via Chance-Constrained Optimization
par: Colot, Antonin, et autres
Publié: (2024)

Detection and Mitigation of Cyberattacks on Volt-Var Control
par: Beikbabaei, Milad, et autres
Publié: (2024)

Partially Observable Residual Reinforcement Learning for PV-Inverter-Based Voltage Control in Distribution Grids
par: Bouchkati, Sarra, et autres
Publié: (2025)

Learning Provably Stable Local Volt/Var Controllers for Efficient Network Operation
par: Yuan, Zhenyi, et autres
Publié: (2022)

Deep Reinforcement Learning for Wireless Scheduling in Distributed Networked Control
par: Pang, Gaoyang, et autres
Publié: (2021)

Control Synthesis in Partially Observable Environments for Complex Perception-Related Objectives
par: Xuan, Zetong, et autres
Publié: (2025)

Weathering Ongoing Uncertainty: Learning and Planning in a Time-Varying Partially Observable Environment
par: Puthumanaillam, Gokul, et autres
Publié: (2023)

Distributionally Robust Decentralized Volt-Var Control with Network Reconfiguration
par: Byeon, Geunyeong, et autres
Publié: (2023)

RL2: Reinforce Large Language Model to Assist Safe Reinforcement Learning for Energy Management of Active Distribution Networks
par: Yang, Xu, et autres
Publié: (2024)

Action-Conditioned Risk Gating for Safety-Critical Control under Partial Observability
par: Liu, Yushen, et autres
Publié: (2026)

Networked Multiagent Safe Reinforcement Learning for Low-carbon Demand Management in Distribution Network
par: Zhang, Jichen, et autres
Publié: (2023)

Distributed Robust Learning based Formation Control of Mobile Robots based on Bioinspired Neural Dynamics
par: Xu, Zhe, et autres
Publié: (2024)

Safe Deep Reinforcement Learning for Building Heating Control and Demand-side Flexibility
par: Jüni, Colin, et autres
Publié: (2026)

Robust Deep Reinforcement Learning for Volt-VAR Optimization in Active Distribution System under Uncertainty
par: Chen, Zhengrong, et autres
Publié: (2024)

Decision Transformer as a Foundation Model for Partially Observable Continuous Control
par: Zhang, Xiangyuan, et autres
Publié: (2024)

Distributionally Robust Control with End-to-End Statistically Guaranteed Metric Learning
par: Wu, Jingyi, et autres
Publié: (2025)

The Distribution Shift Problem in Transportation Networks using Reinforcement Learning and AI
par: Taschin, Federico, et autres
Publié: (2025)

Fair Reinforcement Learning Algorithm for PV Active Control in LV Distribution Networks
par: Vassallo, Maurizio, et autres
Publié: (2024)

Coordinated Power Smoothing Control for Wind Storage Integrated System with Physics-informed Deep Reinforcement Learning
par: Wang, Shuyi, et autres
Publié: (2024)

Reinforcement Learning for Versatile, Dynamic, and Robust Bipedal Locomotion Control
par: Li, Zhongyu, et autres
Publié: (2024)

Robust Recovery Controller for a Quadrupedal Robot using Deep Reinforcement Learning
par: Lee, Joonho, et autres
Publié: (2019)

Energy-Efficient Thermal Comfort Control in Smart Buildings via Deep Reinforcement Learning
par: Gao, Guanyu, et autres
Publié: (2019)

Safety-Aware Reinforcement Learning for Electric Vehicle Charging Station Management in Distribution Network
par: Fan, Jiarong, et autres
Publié: (2024)

Deep Reinforcement Learning for Power Grid Multi-Stage Cascading Failure Mitigation
par: Meng, Bo, et autres
Publié: (2025)

Deep Reinforcement Learning Optimization for Uncertain Nonlinear Systems via Event-Triggered Robust Adaptive Dynamic Programming
par: Bai, Ningwei, et autres
Publié: (2025)

Model-Free Load Frequency Control of Nonlinear Power Systems Based on Deep Reinforcement Learning
par: Chen, Xiaodi, et autres
Publié: (2024)

Control-Optimized Deep Reinforcement Learning for Artificially Intelligent Autonomous Systems
par: Fivel, Oren, et autres
Publié: (2025)

Transmission Interface Power Flow Adjustment: A Deep Reinforcement Learning Approach based on Multi-task Attribution Map
par: Liu, Shunyu, et autres
Publié: (2024)

Volt/VAR Optimization in Transmission Networks with Discrete-Control Devices
par: Tong, Shuaicheng, et autres
Publié: (2026)

Large Language Model as An Operator: An Experience-Driven Solution for Distribution Network Voltage Control
par: Yang, Xu, et autres
Publié: (2025)

Optimizing Traffic Signal Control using High-Dimensional State Representation and Efficient Deep Reinforcement Learning
par: Francis, Lawrence, et autres
Publié: (2024)

Reinforcement Learning with Partial Parametric Model Knowledge
par: Wang, Shuyuan, et autres
Publié: (2023)

Iterative Learning Control-Informed Reinforcement Learning for Batch Process Control
par: Lin, Runze, et autres
Publié: (2026)

Reinforcement Learning for Robust Ageing-Aware Control of Li-ion Battery Systems with Data-Driven Formal Verification
par: Coppola, Rudi, et autres
Publié: (2025)

Large Artificial Intelligence Model Guided Deep Reinforcement Learning for Resource Allocation in Non Terrestrial Networks
par: Ibrahim, Abdikarim Mohamed, et autres
Publié: (2026)

Optimal Control of Logically Constrained Partially Observable and Multi-Agent Markov Decision Processes
par: Kalagarla, Krishna C., et autres
Publié: (2023)

Reinforcement Learning-based Receding Horizon Control using Adaptive Control Barrier Functions for Safety-Critical Systems
par: Sabouni, Ehsan, et autres
Publié: (2024)