Cover Image

Graph neural networks for power grid operational risk assessment under evolving grid topology

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zhang, Yadong, Karve, Pranav M, Mahadevan, Sankaran
Format:	Preprint
Published:	2024
Subjects:	Systems and Control Machine Learning Methodology
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Operational risk quantification of power grids using graph neural network surrogates of the DC OPF
by: Zhang, Yadong, et al.
Published: (2023)

PowerGraph: A power grid benchmark dataset for graph neural networks
by: Varbella, Anna, et al.
Published: (2024)

Enhanced physics-informed neural networks (PINNs) for high-order power grid dynamics
by: Nair, Vineet Jagadeesan
Published: (2024)

Fault Detection for agents on power grid topology optimization: A Comprehensive analysis
by: Lehna, Malte, et al.
Published: (2024)

A Cyber Manufacturing IoT System for Adaptive Machine Learning Model Deployment by Interactive Causality Enabled Self-Labeling
by: Ren, Yutian, et al.
Published: (2024)

Managing power grids through topology actions: A comparative study between advanced rule-based and reinforcement learning agents
by: Lehna, Malte, et al.
Published: (2023)

Scenario Approach with Post-Design Certification of User-Specified Properties
by: Carè, Algo, et al.
Published: (2026)

A Statistical Decision-Theoretical Perspective on the Two-Stage Approach to Parameter Estimation
by: Lakshminarayanan, Braghadeesh, et al.
Published: (2022)

Deep Adaptive Model-Based Design of Experiments
by: Strouwen, Arno, et al.
Published: (2026)

Assessing Markov Property in Driving Behaviors: Insights from Statistical Tests
by: Li, Zheng, et al.
Published: (2025)

A Metropolis-Adjusted Langevin Algorithm for Sampling Jeffreys Prior
by: Shi, Yibo, et al.
Published: (2025)

Application-Driven Learning: A Closed-Loop Prediction and Optimization Approach Applied to Dynamic Reserves and Demand Forecasting
by: Garcia, Joaquim Dias, et al.
Published: (2021)

Set Invariance with Probability One for Controlled Diffusion: Score-based Approach
by: Wang, Wenqing, et al.
Published: (2025)

Novel application of Relief Algorithm in cascaded artificial neural network to predict wind speed for wind power resource assessment in India
by: Malik, Hasmat, et al.
Published: (2024)

Probabilistic forecasting of power system imbalance using neural network-based ensembles
by: Van Gompel, Jonas, et al.
Published: (2024)

Generating adversarial inputs for a graph neural network model of AC power flow
by: Parker, Robert
Published: (2026)

Online Identification of Stochastic Continuous-Time Wiener Models Using Sampled Data
by: Abdalmoaty, Mohamed, et al.
Published: (2024)

Sample Complexity of the Sign-Perturbed Sums Method
by: Szentpéteri, Szabolcs, et al.
Published: (2024)

On Large-Scale Multiple Testing Over Networks: An Asymptotic Approach
by: Pournaderi, Mehrdad, et al.
Published: (2022)

Causal discovery in deterministic discrete LTI-DAE systems
by: Konkathi, Bala Rajesh, et al.
Published: (2025)

Counterfactual Explanations for Model Ensembles Using Entropic Risk Measures
by: Noorani, Erfaun, et al.
Published: (2025)

Aggregated distribution grid flexibilities in subtransmission grid operational management
by: Majumdar, Neelotpal, et al.
Published: (2024)

Asymmetry underlies stability in power grids
by: Molnar, Ferenc, et al.
Published: (2021)

Online learning for robust voltage control under uncertain grid topology
by: Yeh, Christopher, et al.
Published: (2023)

Modelos Empiricos de Pos-Dupla Selecao por LASSO: Discussoes para Estudos do Transporte Aereo
by: Oliveira, Alessandro V. M.
Published: (2025)

Learning a local trading strategy: deep reinforcement learning for grid-scale renewable energy integration
by: Ju, Caleb, et al.
Published: (2024)

Synchronized states of power grids and oscillator networks by convex optimization
by: Hartmann, Carsten, et al.
Published: (2024)

Control of dynamical systems with neural networks
by: Böttcher, Lucas
Published: (2025)

A Hypergraph-Based Machine Learning Ensemble Network Intrusion Detection System
by: Lin, Zong-Zhi, et al.
Published: (2022)

On zero-shot learning in neural state estimation of power distribution systems
by: Berezin, Aleksandr, et al.
Published: (2024)

Reliably-stabilizing piecewise-affine neural network controllers
by: Fabiani, Filippo, et al.
Published: (2021)

Improving accuracy and convergence of federated learning edge computing methods for generalized DER forecasting applications in power grid
by: Nair, Vineet Jagadeesan, et al.
Published: (2024)

The impact of sensor placement on graph-neural-network-based leakage detection
by: van Gemert, J. J. H., et al.
Published: (2026)

A novel ANROA based control approach for grid-tied multi-functional solar energy conversion system
by: Prasad, Dinanath, et al.
Published: (2024)

Simultaneous estimation of multiple discrete unimodal distributions under stochastic order constraints
by: Yoshida, Yasuhiro, et al.
Published: (2026)

An Interventional Perspective on Identifiability in Gaussian LTI Systems with Independent Component Analysis
by: Rajendran, Goutham, et al.
Published: (2023)

From Data-Driven to Purpose-Driven Artificial Intelligence: Systems Thinking for Data-Analytic Automation of Patient Care
by: Anadria, Daniel, et al.
Published: (2025)

Data driven approach towards more efficient Newton-Raphson power flow calculation for distribution grids
by: Yan, Shengyuan, et al.
Published: (2025)

Improved uncertainty quantification for neural networks with Bayesian last layer
by: Fiedler, Felix, et al.
Published: (2023)

CityLearn v2: Energy-flexible, resilient, occupant-centric, and carbon-aware management of grid-interactive communities
by: Nweye, Kingsley, et al.
Published: (2024)