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Found 6 papers, 2 papers with code
Power Grid Behavioral Patterns and Risks of Generalization in Applied Machine Learning
Recent years have seen a rich literature of data-driven approaches designed for power grid applications.
Towards Practical Physics-Informed ML Design and Evaluation for Power Grid
This work formalizes a new concept of physical interpretability which assesses how a ML model makes predictions in a physically meaningful way and introduces an evaluation methodology that identifies a set of attributes that a practical method should satisfy.
Circuit-theoretic Line Outage Distribution Factor
This work presents the design of AC line outage distribution factor created from the circuit-theoretic power flow models.
A Convex Method of Generalized State Estimation using Circuit-theoretic Node-breaker Model
An accurate and up-to-date topology is critical for situational awareness of a power grid; however, wrong switch statuses due to physical damage, communication error, or cyber-attack, can often result in topology errors.
Combined Transmission and Distribution State-Estimation for Future Electric Grids
Instead, a more distributed yet coordinated approach for grid operation and control will emerge that models and analyzes the grid with a larger footprint and deeper hierarchy to unify control of disparate T&D grid resources under a common framework.
Dynamic Graph-Based Anomaly Detection in the Electrical Grid
Given sensor readings over time from a power grid, how can we accurately detect when an anomaly occurs?
