Test Time Training for AC Power Flow Surrogates via Physics and Operational Constraint Refinement
Fuente:
arXiv
Saved in:
| Main Authors: | Dogoulis, Panteleimon, Alizadeh, Mohammad Iman, Kubler, Sylvain, Cordy, Maxime |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
KCLNet: Physics-Informed Power Flow Prediction via Constraints Projections
by: Dogoulis, Pantelis, et al.
Published: (2025)
by: Dogoulis, Pantelis, et al.
Published: (2025)
Physics Informed Reinforcement Learning with Gibbs Priors for Topology Control in Power Grids
by: Dogoulis, Pantelis, et al.
Published: (2026)
by: Dogoulis, Pantelis, et al.
Published: (2026)
Robustness Analysis of AI Models in Critical Energy Systems
by: Dogoulis, Pantelis, et al.
Published: (2024)
by: Dogoulis, Pantelis, et al.
Published: (2024)
Constraint-Guided Prediction Refinement via Deterministic Diffusion Trajectories
by: Dogoulis, Pantelis, et al.
Published: (2025)
by: Dogoulis, Pantelis, et al.
Published: (2025)
Can Large Language Models Reason and Optimize Under Constraints?
by: Bernier, Fabien, et al.
Published: (2026)
by: Bernier, Fabien, et al.
Published: (2026)
Rebuild AC Power Flow Models with Graph Attention Networks
by: Hu, Yuting, et al.
Published: (2025)
by: Hu, Yuting, et al.
Published: (2025)
Residual Correction Models for AC Optimal Power Flow Using DC Optimal Power Flow Solutions
by: Za'ter, Muhy Eddin, et al.
Published: (2025)
by: Za'ter, Muhy Eddin, et al.
Published: (2025)
Differentiable Optimization for Deep Learning-Enhanced DC Approximation of AC Optimal Power Flow
by: Rosemberg, Andrew, et al.
Published: (2025)
by: Rosemberg, Andrew, et al.
Published: (2025)
Newton's Lantern: A Reinforcement Learning Framework for Finetuning AC Power Flow Warm Start Models
by: Bose, Shourya, et al.
Published: (2026)
by: Bose, Shourya, et al.
Published: (2026)
Inferring Ingrained Remote Information in AC Power Flows Using Neuromorphic Modality Regime
by: Diao, Xiaoguang, et al.
Published: (2024)
by: Diao, Xiaoguang, et al.
Published: (2024)
Self-Tuning PID Control via a Hybrid Actor-Critic-Based Neural Structure for Quadcopter Control
by: Sharifi, Iman, et al.
Published: (2023)
by: Sharifi, Iman, et al.
Published: (2023)
Physics-Constrained Neural Dynamics: A Unified Manifold Framework for Large-Scale Power Flow Computation
by: Liu, Xuezhi
Published: (2025)
by: Liu, Xuezhi
Published: (2025)
Safe Decentralized Operation of EV Virtual Power Plant with Limited Network Visibility via Multi-Agent Reinforcement Learning
by: Huang, Chenghao, et al.
Published: (2026)
by: Huang, Chenghao, et al.
Published: (2026)
SafeFlow: Real-Time Text-Driven Humanoid Whole-Body Control via Physics-Guided Rectified Flow and Selective Safety Gating
by: Cho, Hanbyel, et al.
Published: (2026)
by: Cho, Hanbyel, et al.
Published: (2026)
Formal Control for Uncertain Systems via Contract-Based Probabilistic Surrogates (Extended Version)
by: Schön, Oliver, et al.
Published: (2025)
by: Schön, Oliver, et al.
Published: (2025)
Learning-Augmented Power System Operations: A Unified Optimization View
by: Xu, Wangkun, et al.
Published: (2025)
by: Xu, Wangkun, et al.
Published: (2025)
Machine Learning for Fairness-Aware Load Shedding: A Real-Time Solution via Identifying Binding Constraints
by: Zhou, Yuqi, et al.
Published: (2024)
by: Zhou, Yuqi, et al.
Published: (2024)
Grid-Agent: An LLM-Powered Multi-Agent System for Power Grid Control
by: Zhang, Yan, et al.
Published: (2025)
by: Zhang, Yan, et al.
Published: (2025)
Optimizing Service Operations via LLM-Powered Multi-Agent Simulation
by: Wang, Yanyuan, et al.
Published: (2026)
by: Wang, Yanyuan, et al.
Published: (2026)
PowerModelsGAT-AI: Physics-Informed Graph Attention for Multi-System Power Flow with Continual Learning
by: Ezeakunne, Chidozie, et al.
Published: (2026)
by: Ezeakunne, Chidozie, et al.
Published: (2026)
Optimal Power Grid Operations with Foundation Models
by: Puech, Alban, et al.
Published: (2024)
by: Puech, Alban, et al.
Published: (2024)
SOLIS: Physics-Informed Learning of Interpretable Neural Surrogates for Nonlinear Systems
by: Mansur, Murat Furkan, et al.
Published: (2026)
by: Mansur, Murat Furkan, et al.
Published: (2026)
Interpreting the Value of Flexibility in AC Security-Constrained Transmission Expansion Planning via a Cooperative Game Framework
by: Churkin, Andrey, et al.
Published: (2023)
by: Churkin, Andrey, et al.
Published: (2023)
PowerFlowNet: Power Flow Approximation Using Message Passing Graph Neural Networks
by: Lin, Nan, et al.
Published: (2023)
by: Lin, Nan, et al.
Published: (2023)
gridfm-datakit-v1: A Python Library for Scalable and Realistic Power Flow and Optimal Power Flow Data Generation
by: Puech, Alban, et al.
Published: (2025)
by: Puech, Alban, et al.
Published: (2025)
Automated Validation of Textual Constraints Against AutomationML via LLMs and SHACL
by: Westermann, Tom, et al.
Published: (2025)
by: Westermann, Tom, et al.
Published: (2025)
AC4MPC: Actor-Critic Reinforcement Learning for Nonlinear Model Predictive Control
by: Reiter, Rudolf, et al.
Published: (2024)
by: Reiter, Rudolf, et al.
Published: (2024)
Enhanced Optimal Power Flow Using a Trained Neural Network Surrogate for Distribution Grid Constraints
by: Panagi, Savvas, et al.
Published: (2026)
by: Panagi, Savvas, et al.
Published: (2026)
PGLearn -- An Open-Source Learning Toolkit for Optimal Power Flow
by: Klamkin, Michael, et al.
Published: (2025)
by: Klamkin, Michael, et al.
Published: (2025)
Dispatch-Aware Deep Neural Network for Optimal Transmission Switching: Toward Real-Time and Feasibility Guaranteed Operation
by: Kim, Minsoo, et al.
Published: (2025)
by: Kim, Minsoo, et al.
Published: (2025)
Identification For Control Based on Neural Networks: Approximately Linearizable Models
by: Thieffry, Maxime, et al.
Published: (2024)
by: Thieffry, Maxime, et al.
Published: (2024)
Adaptive Informed Deep Neural Networks for Power Flow Analysis
by: Kaseb, Zeynab, et al.
Published: (2024)
by: Kaseb, Zeynab, et al.
Published: (2024)
Coordinated Power Smoothing Control for Wind Storage Integrated System with Physics-informed Deep Reinforcement Learning
by: Wang, Shuyi, et al.
Published: (2024)
by: Wang, Shuyi, et al.
Published: (2024)
Imitation Learning for Intra-Day Power Grid Operation through Topology Actions
by: de Jong, Matthijs, et al.
Published: (2024)
by: de Jong, Matthijs, et al.
Published: (2024)
Quantifying Cyber-Vulnerability in Power Electronics Systems via an Impedance-Based Attack Reachable Domain
by: Zhen, Hongwei, et al.
Published: (2026)
by: Zhen, Hongwei, et al.
Published: (2026)
A Multi-Scale Attention-Based Attack Diagnosis Mechanism for Parallel Cyber-Physical Attacks in Power Grids
by: Ren, Junhao, et al.
Published: (2025)
by: Ren, Junhao, et al.
Published: (2025)
Refinement of Accelerated Demonstrations via Incremental Iterative Reference Learning Control for Fast Contact-Rich Imitation Learning
by: Yamane, Koki, et al.
Published: (2026)
by: Yamane, Koki, et al.
Published: (2026)
Blackout Mitigation via Physics-guided RL
by: Dwivedi, Anmol, et al.
Published: (2024)
by: Dwivedi, Anmol, et al.
Published: (2024)
Behavioral Generative Agents for Energy Operations
by: Chen, Cong, et al.
Published: (2025)
by: Chen, Cong, et al.
Published: (2025)
Probabilistic Satisfaction of Temporal Logic Constraints in Reinforcement Learning via Adaptive Policy-Switching
by: Lin, Xiaoshan, et al.
Published: (2024)
by: Lin, Xiaoshan, et al.
Published: (2024)
Similar Items
-
KCLNet: Physics-Informed Power Flow Prediction via Constraints Projections
by: Dogoulis, Pantelis, et al.
Published: (2025) -
Physics Informed Reinforcement Learning with Gibbs Priors for Topology Control in Power Grids
by: Dogoulis, Pantelis, et al.
Published: (2026) -
Robustness Analysis of AI Models in Critical Energy Systems
by: Dogoulis, Pantelis, et al.
Published: (2024) -
Constraint-Guided Prediction Refinement via Deterministic Diffusion Trajectories
by: Dogoulis, Pantelis, et al.
Published: (2025) -
Can Large Language Models Reason and Optimize Under Constraints?
by: Bernier, Fabien, et al.
Published: (2026)