Mixed-Integer Optimization for Bio-Inspired Robust Power Network Design

no code implementations • 30 Oct 2020 • Hao Huang, Varuneswara Panyam, Mohammad Rasoul Narimani, Astrid Layton, Katherine R. Davis

This paper presents an approach to address this challenge through bio-inspired power system network design to improve system reliability and resilience against disturbances.

Toward Efficient Wide-Area Identification of Multiple Element Contingencies in Power Systems

no code implementations • 16 Feb 2021 • Hao Huang, Zeyu Mao, Mohammad Rasoul Narimani, Katherine R. Davis

Based on each selected branch, the approach constructs the subgraph with parameters of distance and search level, while using branches' LODF metrics as the weights.

Graph Neural Networks Based Detection of Stealth False Data Injection Attacks in Smart Grids

no code implementations • 5 Apr 2021 • Osman Boyaci, Amarachi Umunnakwe, Abhijeet Sahu, Mohammad Rasoul Narimani, Muhammad Ismail, Katherine Davis, Erchin Serpedin

False data injection attacks (FDIAs) represent a major class of attacks that aim to break the integrity of measurements by injecting false data into the smart metering devices in power grids.

Joint Detection and Localization of Stealth False Data Injection Attacks in Smart Grids using Graph Neural Networks

no code implementations • 24 Apr 2021 • Osman Boyaci, Mohammad Rasoul Narimani, Katherine Davis, Muhammad Ismail, Thomas J Overbye, Erchin Serpedin

To the best of our knowledge, this is the first work based on GNN that automatically detects and localizes FDIA in power systems.

Cyberattack Detection in Large-Scale Smart Grids using Chebyshev Graph Convolutional Networks

no code implementations • 25 Dec 2021 • Osman Boyaci, Mohammad Rasoul Narimani, Katherine Davis, Erchin Serpedin

As a highly complex and integrated cyber-physical system, modern power grids are exposed to cyberattacks.