Predicting failure cascades in large scale power systems via the influence model framework

X Wu, D Wu, E Modiano - IEEE Transactions on Power Systems, 2021 - ieeexplore.ieee.org
Large blackouts in power grids are often the consequence of uncontrolled failure cascades.
The ability to predict the failure cascade process in an efficient and accurate manner is …

Structural analysis of the stochastic influence model for identifiability and reduced-order estimation

L Zhao, Y Wan, C He, FL Lewis - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
The influence model (IM) is a reduced-order stochastic network model that captures the
spatiotemporal dynamics in a network of interactive Markov chains. Identifiability and …

Contingency analysis with warm starter using probabilistic graphical model

S Li, A Pandey, L Pileggi - Electric Power Systems Research, 2024 - Elsevier
Cyberthreats are an increasingly common risk to the power grid and can thwart secure grid
operations. We propose to extend contingency analysis to include cyberthreat evaluations …

Data-integrity aware stochastic model for cascading failures in power grids

RA Shuvro, P Das, JS Jyoti, JM Abreu… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
The reliable operation of power grids during cascading failures is heavily dependent on the
interdependencies between the power grid components and the supporting communications …

Towards Practical Physics-Informed ML Design and Evaluation for Power Grid

S Li, A Pandey, L Pileggi - arXiv preprint arXiv:2205.03673, 2022 - arxiv.org
When applied to a real-world safety critical system like the power grid, general machine
learning methods suffer from expensive training, non-physical solutions, and limited …

Environment, communication and decision for multiagent systems

L Zhao - 2023 - mavmatrix.uta.edu
Multiagent systems (MAS) are ubiquitous in modern systems and have found broad
applications, such as in intelligent transportation systems (ITS). Environment …