Imagen de Portada

Topology-Aware Graph Neural Network-based State Estimation for PMU-Unobservable Power Systems

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Moshtagh, Shiva, Azimian, Behrouz, Golgol, Mohammad, Pal, Anamitra
Formato:	Preprint
Publicado:	2025
Materias:	Systems and Control
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Time-Synchronized State Estimation Using Graph Neural Networks in Presence of Topology Changes
por: Moshtagh, Shiva, et al.
Publicado: (2022)

Analytical Verification of Performance of Deep Neural Network Based Time-Synchronized Distribution System State Estimation
por: Azimian, Behrouz, et al.
Publicado: (2023)

Data-Driven Flow and Injection Estimation in PMU-Unobservable Transmission Systems
por: Sahoo, Satyaprajna, et al.
Publicado: (2022)

High-Speed Voltage Control in Active Distribution Systems with Smart Inverter Coordination and Deep Reinforcement Learning
por: Golgol, Mohammad, et al.
Publicado: (2023)

Impact of Work Schedule Flexibility on EV Hosting Capacity: Insights from Analyzing Field Data
por: Iorio, Marco, et al.
Publicado: (2026)

System-wide Instrument Transformer Calibration and Line Parameter Estimation Using PMU Data
por: Varghese, Antos Cheeramban, et al.
Publicado: (2025)

Exploring the Influence of Residential Electric Vehicle Charging on Distribution System Hosting Capacity -- A Case-Study in Arizona
por: Golgol, Mohammad, et al.
Publicado: (2024)

A Preventive-Corrective Scheme for Ensuring Power System Security During Active Wildfire Risks
por: Sahoo, Satyaprajna, et al.
Publicado: (2024)

State-Derivative Feedback Control for Damping Low-Frequency Oscillations in Bulk Power Systems
por: Akter, MST Rumi, et al.
Publicado: (2025)

Linear State Estimation in Presence of Bounded Uncertainties: A Comparative Analysis
por: Das, Ayan, et al.
Publicado: (2025)

Cut-set and Stability Constrained Optimal Power Flow for Resilient Operation During Wildfires
por: Sahoo, Satyaprajna, et al.
Publicado: (2023)

Enhancing Power Flow Estimation with Topology-Aware Gated Graph Neural Networks
por: Jadhav, Shrenik, et al.
Publicado: (2025)

Creating Temporally Correlated High-Resolution Profiles of Load Injection Using Constrained Generative Adversarial Networks
por: Shah, Hritik Gopal, et al.
Publicado: (2023)

Analyzing Cross-Phase Effects of Reactive Power Intervention on Distribution Voltage Control
por: Dalal, Dhaval, et al.
Publicado: (2023)

Robust and Interpretable Graph Neural Networks for Power Systems State Estimation
por: Yaniv, Arbel, et al.
Publicado: (2026)

Damping LFOs: Grid Following with Power Oscillation Damping vs. Grid Forming vs. PSS
por: Chakraborty, Tamojit, et al.
Publicado: (2025)

Revisiting the Optimal PMU Placement Problem in Multi-Machine Power Networks
por: Kazma, Mohamad H., et al.
Publicado: (2023)

Wildfire Risk-Informed Preventive-Corrective Decision Making under Renewable Uncertainty
por: Sahoo, Satyaprajna, et al.
Publicado: (2026)

Time-Synchronized Full System State Estimation Considering Practical Implementation Challenges
por: Varghese, Antos Cheeramban, et al.
Publicado: (2022)

A Constrained Formulation for Simultaneous Line Parameter Estimation and Instrument Transformer Calibration
por: Varghese, Antos Cheeramban, et al.
Publicado: (2026)

Optimal PMU Placement for Kalman Filtering of DAE Power System Models
por: Katanic, Milos, et al.
Publicado: (2025)

A Graph Neural Network with Auxiliary Task Learning for Missing PMU Data Reconstruction
por: Li, Bo, et al.
Publicado: (2025)

A Practical Approach Towards Inertia Estimation Using Ambient Synchrophasor Data
por: Sharma, Anushka, et al.
Publicado: (2025)

PowerGNN: A Topology-Aware Graph Neural Network for Electricity Grids
por: Suri, Dhruv, et al.
Publicado: (2025)

Physics-informed Graphical Neural Network for Power System State Estimation
por: Ngo, Quang-Ha, et al.
Publicado: (2023)

Uncertainty Error Modeling for Non-Linear State Estimation With Unsynchronized SCADA and $μ$PMU Measurements
por: Cooper, Austin, et al.
Publicado: (2022)

Physics-Informed Neural Networks for Accelerating Power System State Estimation
por: Falas, Solon, et al.
Publicado: (2023)

Power System Quasi-Steady State Estimation: An Echo State Network Approach
por: Intriago, Gabriel, et al.
Publicado: (2024)

A Learning-Driven Stochastic Hybrid System Framework for Detecting Unobservable Contingencies in Power Systems
por: Varmazyari, Hamid, et al.
Publicado: (2025)

Robust Power System State Estimation using Physics-Informed Neural Networks
por: Falas, Solon, et al.
Publicado: (2025)

Vectorized Gaussian Belief Propagation for Near Real-Time Fully-Distributed PMU-Based State Estimation
por: Cosovic, Mirsad, et al.
Publicado: (2026)

Graph Neural Networks for Fast Contingency Analysis of Power Systems
por: Nakiganda, Agnes M., et al.
Publicado: (2023)

Stiffness-Aware Decentralized Dynamic State Estimation for Inverter-Dominated Power Systems
por: Zhao, Xingyu, et al.
Publicado: (2026)

Topology-Aware Reinforcement Learning over Graphs for Resilient Power Distribution Networks
por: Jacob, Roshni Anna, et al.
Publicado: (2026)

Power System Steady-State Estimation Revisited
por: Rytir, Pavel, et al.
Publicado: (2025)

Physics-Informed Graph Neural Network for Dynamic Reconfiguration of Power Systems
por: Authier, Jules, et al.
Publicado: (2023)

Risk-Aware Planning of Power Distribution Systems Using Scalable Cloud Technologies
por: Poudel, Shiva, et al.
Publicado: (2025)

FaultXformer: A Transformer-Encoder Based Fault Classification and Location Identification model in PMU-Integrated Active Electrical Distribution System
por: Thakur, Kriti, et al.
Publicado: (2026)

Graph-based Simulation Framework for Power Resilience Estimation and Enhancement
por: Wang, Xuesong, et al.
Publicado: (2024)

Graph Neural Networks on Factor Graphs for Robust, Fast, and Scalable Linear State Estimation with PMUs
por: Kundacina, Ognjen, et al.
Publicado: (2023)