Detection and Defense Methods for False Data Injection Attack in Power Systems Based on State-Space Decomposition

Zhihong LIANG; Binyuan YAN; Chao HONG; Jiaye TAO; Yiwei YANG; Lin CHEN; Pandeng LI

doi:10.13648/j.cnki.issn1674-0629.2025.06.004

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South Power Sys Technol ›› 2025, Vol. 19 ›› Issue (6) : 39-50. DOI: 10.13648/j.cnki.issn1674-0629.2025.06.004

Network Security and Attack Defense Technologies for Power Systems

Detection and Defense Methods for False Data Injection Attack in Power Systems Based on State-Space Decomposition

Zhihong LIANG ¹^,² ,
Binyuan YAN ³ ,
Chao HONG ¹^,² ,
Jiaye TAO ³ ,
Yiwei YANG ¹^,² ,
Lin CHEN ¹^,² ,
Pandeng LI ¹^,²

Author information +

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Abstract

With the growing integration of renewable energy, load frequency control （LFC） in power systems faces security risks from false data injection attack （FDIA）. Existing detection methods struggle to differentiate control input attacks from measurement attacks, compromising system stability and security. This paper develops a state-space model for LFC incorporating renewable energy and energy storage systems and analyzes the impact of FDIA on system dynamics. A state-space decomposition method is employed to decouple attack signals into control input and measurement attacks, improving detection accuracy. A sliding mode observer-based attack estimation method is proposed for real-time detection. Additionally, an attack-resilient control （ARC） strategy is designed using $H ∞$ control theory to enhance system robustness. Simulations show that the proposed method reduces the attack estimation mean squared error by nearly 30% and significantly improves frequency response stability compared to traditional methods. These results demonstrate the method′s effectiveness in detecting FDIA and enhancing power system security.

Key words

load frequency control / false data injection attack / state-space decomposition / sliding mode observer / anti-attack control

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Zhihong LIANG , Binyuan YAN , Chao HONG , et al . Detection and Defense Methods for False Data Injection Attack in Power Systems Based on State-Space Decomposition[J]. Southern Power System Technology. 2025, 19(6): 39-50 https://doi.org/10.13648/j.cnki.issn1674-0629.2025.06.004

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