@inproceedings{c5184029da8741d49182edd29775404c,
title = "An Ergodic CuSum Algorithm for False Data Injection Attacks Detection in DC Microgrids",
abstract = "DC microgrids have widely adopted hierarchical control architecture through distributed generation units (DGUs) to enhance reliability and scalability. However, this makes the system vulnerable to false data injection attacks (FDIAs), which can disrupt system stability or shift the operating point. While observers are commonly used to detect FDIAs, some FDIAs can be stealthy, or observers lack sufficient sensitivity for reliable identification. To address this, we propose a quickest change detection (QCD) method based on an unknown input observer (UIO) estimation error model to detect the FDIAs that are stealthy to the UIOs. The Ergodic CuSum algorithm is designed and can be efficiently updated using estimation error observations. The approach is validated through Simulink and real-time simulations.",
keywords = "Attack, CuSum, Detection, Microgrid, Observer",
author = "Ge Yang and Zhongchang Sun and Shaofeng Zou and Xiu Yao and Luis Herrera",
note = "Publisher Copyright: {\textcopyright} 2025 IEEE.; 17th Annual IEEE Energy Conversion Conference Congress and Exposition, ECCE 2025 ; Conference date: 19-10-2025 Through 23-10-2025",
year = "2025",
doi = "10.1109/ECCE58356.2025.11260430",
language = "English",
series = "2025 IEEE Energy Conversion Conference Congress and Exposition, ECCE 2025",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2025 IEEE Energy Conversion Conference Congress and Exposition, ECCE 2025",
address = "United States",
}