Detection of false data injection attacks on power systems based on measurement-eigenvalue residual similarity test

Autor: Yihua Zhu, Ren Liu, Dongxu Chang, Hengdao Guo
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Frontiers in Energy Research, Vol 11 (2023)
Druh dokumentu: article
ISSN: 2296-598X
DOI: 10.3389/fenrg.2023.1285317
Popis: Existing False data injection attack (FDIA) detection methods based on measurement similarity testing have difficulty in distinguishing between actual power grid accidents and FDIAs. Therefore, this paper proposes a detection method called the measurement-eigenvalue residual similarity (MERS) test, which can accurately detect FDIAs in AC state estimationof power system and effectively distinguish them from actual power grid accidents. Simulation results on the IEEE 39-bus system demonstrate that the proposed method achieves higher detection rates and lower false alarm rates than traditional methods under various operation conditions.
Databáze: Directory of Open Access Journals