Open AccessEvent‐triggered detection of cyberattacks on load frequency control
Author(s) -
Patel Aradhna,
Purwar Shubhi
Publication year - 2020
Publication title -
iet cyber‐physical systems: theory and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.308
H-Index - 7
ISSN - 2398-3396
DOI - 10.1049/iet-cps.2019.0067
Subject(s) - electric power system , computer science , vulnerability (computing) , computer security , leverage (statistics) , load shedding , kalman filter , event (particle physics) , real time computing , power (physics) , physics , quantum mechanics , machine learning , artificial intelligence
Modern power systems are extensively interlaced with data communication at various levels leading to increased vulnerability to cyberattacks at individual components as well as integrated controls. An effective cyber protection is, therefore, fast becoming an indispensable requirement for the smart grids. A false data injection (FDI) attack on load frequency control (LFC) is a stealth process, which has devastating consequences while at times may also lead to catastrophic system blackouts. This work comprises detailed analyses of the LFC system vulnerability to FDI attacks. It further develops an efficient event‐triggered detection scheme to leverage the LFC protection against FDI attacks. This developed event‐triggered generalised extended state observer (ET‐GESO) uses Lyapunov stability analysis to derive the event‐triggering condition and thereby reduce the communication burden significantly. The feasibility of the proposed ET‐GESO is further studied by demonstrating its Zeno behaviour exclusion. Extensive simulation studies are performed on a peer‐reported two‐area power transacting system and IEEE 39‐bus New England system. A comparison study between the proposed technique and reported Kalman filter‐based detection scheme is also performed. Different FDI attack formulations and their detection illustrate the effectiveness of the proposed detection method.