Neural Networks for AC Optimal Power Flow: Improving Worst-Case Guarantees during Training
Fuente:
arXiv
Saved in:
| Main Authors: | Giraud, Bastien, Nellikath, Rahul, Vorwerk, Johanna, Alowaifeer, Maad, Chatzivasileiadis, Spyros |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Global Performance Guarantees for Neural Network Models of AC Power Flow
by: Chevalier, Samuel, et al.
Published: (2022)
by: Chevalier, Samuel, et al.
Published: (2022)
A Dataset Generation Toolbox for Dynamic Security Assessment: On the Role of the Security Boundary
by: Giraud, Bastien, et al.
Published: (2025)
by: Giraud, Bastien, et al.
Published: (2025)
Neural Operators for Power Systems: A Physics-Informed Framework for Modeling Power System Components
by: Karampinis, Ioannis, et al.
Published: (2025)
by: Karampinis, Ioannis, et al.
Published: (2025)
Correctness Verification of Neural Networks Approximating Differential Equations
by: Ellinas, Petros, et al.
Published: (2024)
by: Ellinas, Petros, et al.
Published: (2024)
Verification and Validation of Physics-Informed Surrogate Component Models for Dynamic Power-System Simulation
by: Ellinas, Petros, et al.
Published: (2026)
by: Ellinas, Petros, et al.
Published: (2026)
Physics-Informed Neural Networks in Power System Dynamics: Improving Simulation Accuracy
by: Nadal, Ignasi Ventura, et al.
Published: (2025)
by: Nadal, Ignasi Ventura, et al.
Published: (2025)
Graph Neural Networks for Fast Contingency Analysis of Power Systems
by: Nakiganda, Agnes M., et al.
Published: (2023)
by: Nakiganda, Agnes M., et al.
Published: (2023)
Toolbox for Developing Physics Informed Neural Networks for Power Systems Components
by: Karampinis, Ioannis, et al.
Published: (2025)
by: Karampinis, Ioannis, et al.
Published: (2025)
Stochastic Quantum Power Flow for Risk Assessment in Power Systems
by: Sævarsson, Brynjar, et al.
Published: (2023)
by: Sævarsson, Brynjar, et al.
Published: (2023)
Physics-Informed Neural Networks: a Plug and Play Integration into Power System Dynamic Simulations
by: Nadal, Ignasi Ventura, et al.
Published: (2024)
by: Nadal, Ignasi Ventura, et al.
Published: (2024)
Trustworthiness Layer for Foundation Models in Power Systems: Application to N-k Contingency Screening
by: Alcántara, Antonio, et al.
Published: (2026)
by: Alcántara, Antonio, et al.
Published: (2026)
Bayesian Physics-informed Neural Networks for System Identification of Inverter-dominated Power Systems
by: Stock, Simon, et al.
Published: (2024)
by: Stock, Simon, et al.
Published: (2024)
PINNSim: A Simulator for Power System Dynamics based on Physics-Informed Neural Networks
by: Stiasny, Jochen, et al.
Published: (2023)
by: Stiasny, Jochen, et al.
Published: (2023)
Learning to Pursue AC Optimal Power Flow Solutions with Feasibility Guarantees
by: Ajeyemi, Damola, et al.
Published: (2025)
by: Ajeyemi, Damola, et al.
Published: (2025)
A hybrid Quantum-Classical Algorithm for Mixed-Integer Optimization in Power Systems
by: Ellinas, Petros, et al.
Published: (2024)
by: Ellinas, Petros, et al.
Published: (2024)
Scalable Physics-Informed Neural Networks for Accelerating Electromagnetic Transient Stability Assessment
by: Nadal, Ignasi Ventura, et al.
Published: (2025)
by: Nadal, Ignasi Ventura, et al.
Published: (2025)
Error estimation for physics-informed neural networks with implicit Runge-Kutta methods
by: Stiasny, Jochen, et al.
Published: (2024)
by: Stiasny, Jochen, et al.
Published: (2024)
Network-Aware Flexibility Requests for Distribution-Level Flexibility Markets
by: Prat, Eléa, et al.
Published: (2021)
by: Prat, Eléa, et al.
Published: (2021)
Improved Physics-Informed Neural Network based AC Power Flow for Distribution Networks
by: Eeckhout, Victor, et al.
Published: (2024)
by: Eeckhout, Victor, et al.
Published: (2024)
Digital Twin for Real-Time Security Assessment and Flexibility Activation in the Bornholm Distribution System
by: Sundhu, Anosh Arshad, et al.
Published: (2026)
by: Sundhu, Anosh Arshad, et al.
Published: (2026)
AC-Network-Informed DC Optimal Power Flow for Electricity Markets
by: Constante-Flores, Gonzalo E., et al.
Published: (2024)
by: Constante-Flores, Gonzalo E., et al.
Published: (2024)
Beyond the Neural Fog: Interpretable Learning for AC Optimal Power Flow
by: Pineda, Salvador, et al.
Published: (2024)
by: Pineda, Salvador, et al.
Published: (2024)
Dual Pricing to Prioritize Renewable Energy and Consumer Preferences in Electricity Markets
by: Jong, Emilie, et al.
Published: (2024)
by: Jong, Emilie, 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)
Distributed AC Optimal Power Flow: A Scalable Solution for Large-Scale Problems
by: Dai, Xinliang, et al.
Published: (2025)
by: Dai, Xinliang, et al.
Published: (2025)
Advancing Distributed AC Optimal Power Flow for Integrated Transmission-Distribution Systems
by: Dai, Xinliang, et al.
Published: (2023)
by: Dai, Xinliang, et al.
Published: (2023)
Data-driven AC Optimal Power Flow with Physics-informed Learning and Calibrations
by: Wang, Junfei, et al.
Published: (2024)
by: Wang, Junfei, et al.
Published: (2024)
A Computationally Efficient Method for Solving Mixed-Integer AC Optimal Power Flow Problems
by: Heid, Johannes, et al.
Published: (2025)
by: Heid, Johannes, et al.
Published: (2025)
A Bezier Curve Based Approach to the Convexification of the AC Optimal Power Flow Problem
by: Saldarriaga-Cortes, Carlos Arturo, et al.
Published: (2025)
by: Saldarriaga-Cortes, Carlos Arturo, 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)
Neural Risk Limiting Dispatch in Power Networks: Formulation and Generalization Guarantees
by: Chen, Ge, et al.
Published: (2024)
by: Chen, Ge, et al.
Published: (2024)
Exploiting Scheduling Flexibility via State-Based Scheduling When Guaranteeing Worst-Case Services
by: Xu, Yike, et al.
Published: (2026)
by: Xu, Yike, et al.
Published: (2026)
Stochastic Security Constrained AC Optimal Power Flow Using General Polynomial Chaos Expansion
by: Mohy-ud-din, Ghulam, et al.
Published: (2025)
by: Mohy-ud-din, Ghulam, et al.
Published: (2025)
A Differentially Private Quantum Neural Network for Probabilistic Optimal Power Flow
by: Cao, Yuji, et al.
Published: (2024)
by: Cao, Yuji, et al.
Published: (2024)
Advancing Hybrid Quantum Neural Network for Alternative Current Optimal Power Flow
by: Hu, Ze, et al.
Published: (2024)
by: Hu, Ze, et al.
Published: (2024)
Graph Neural Network-Accelerated Network-Reconfigured Optimal Power Flow
by: Pham, Thuan, et al.
Published: (2024)
by: Pham, Thuan, et al.
Published: (2024)
Reduced Optimal Power Flow Using Graph Neural Network
by: Pham, Thuan, et al.
Published: (2022)
by: Pham, Thuan, et al.
Published: (2022)
Rebuild AC Power Flow Models with Graph Attention Networks
by: Hu, Yuting, et al.
Published: (2025)
by: Hu, Yuting, et al.
Published: (2025)
Hypergraph-Based Fast Distributed AC Power Flow Optimization
by: Dai, Xinliang, et al.
Published: (2023)
by: Dai, Xinliang, et al.
Published: (2023)
Optimal Design of Volt/VAR Control Rules of Inverters using Deep Learning
by: Gupta, Sarthak, et al.
Published: (2022)
by: Gupta, Sarthak, et al.
Published: (2022)
Similar Items
-
Global Performance Guarantees for Neural Network Models of AC Power Flow
by: Chevalier, Samuel, et al.
Published: (2022) -
A Dataset Generation Toolbox for Dynamic Security Assessment: On the Role of the Security Boundary
by: Giraud, Bastien, et al.
Published: (2025) -
Neural Operators for Power Systems: A Physics-Informed Framework for Modeling Power System Components
by: Karampinis, Ioannis, et al.
Published: (2025) -
Correctness Verification of Neural Networks Approximating Differential Equations
by: Ellinas, Petros, et al.
Published: (2024) -
Verification and Validation of Physics-Informed Surrogate Component Models for Dynamic Power-System Simulation
by: Ellinas, Petros, et al.
Published: (2026)