Research on detection and defense methods for false data injection attacks in power systems based on state-space decomposition
Abstract With increasing renewable energy integration, load frequency control (LFC) faces security risks from false data injection attacks (FDIAs). Existing detection methods struggle to distinguish control input attacks from measurement attacks, affecting system stability. This paper formulates a n...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Springer
2025-07-01
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| Series: | Discover Applied Sciences |
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| Online Access: | https://doi.org/10.1007/s42452-025-07251-3 |
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| _version_ | 1849761474024570880 |
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| author | Chao Hong Zhihong Liang Yiwei Yang Pandeng Li Lin Chen Leyi Bi Yunan Zhang |
| author_facet | Chao Hong Zhihong Liang Yiwei Yang Pandeng Li Lin Chen Leyi Bi Yunan Zhang |
| author_sort | Chao Hong |
| collection | DOAJ |
| description | Abstract With increasing renewable energy integration, load frequency control (LFC) faces security risks from false data injection attacks (FDIAs). Existing detection methods struggle to distinguish control input attacks from measurement attacks, affecting system stability. This paper formulates a novel state-space decomposition strategy for decoupling control input and measurement attacks in the context of LFC systems with high renewable penetration; introduces a sliding mode observer (SMO) tailored for real-time attack estimation; and integrates an attack-resilient control (ARC) scheme based on $$H_\infty$$ H ∞ control theory to actively suppress attack impacts. Simulations show that the proposed method reduces AE mean squared error by nearly 30% and improves frequency response stability. These results confirm its effectiveness in detecting FDIAs and enhancing power system security. |
| format | Article |
| id | doaj-art-81d6aa3cf06d4a17b4192c218d05c4fc |
| institution | DOAJ |
| issn | 3004-9261 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Springer |
| record_format | Article |
| series | Discover Applied Sciences |
| spelling | doaj-art-81d6aa3cf06d4a17b4192c218d05c4fc2025-08-20T03:06:01ZengSpringerDiscover Applied Sciences3004-92612025-07-017711810.1007/s42452-025-07251-3Research on detection and defense methods for false data injection attacks in power systems based on state-space decompositionChao Hong0Zhihong Liang1Yiwei Yang2Pandeng Li3Lin Chen4Leyi Bi5Yunan Zhang6Electric Power Research Institute, China Southern Power GridElectric Power Research Institute, China Southern Power GridElectric Power Research Institute, China Southern Power GridElectric Power Research Institute, China Southern Power GridElectric Power Research Institute, China Southern Power GridElectric Power Research Institute, China Southern Power GridElectric Power Research Institute, China Southern Power GridAbstract With increasing renewable energy integration, load frequency control (LFC) faces security risks from false data injection attacks (FDIAs). Existing detection methods struggle to distinguish control input attacks from measurement attacks, affecting system stability. This paper formulates a novel state-space decomposition strategy for decoupling control input and measurement attacks in the context of LFC systems with high renewable penetration; introduces a sliding mode observer (SMO) tailored for real-time attack estimation; and integrates an attack-resilient control (ARC) scheme based on $$H_\infty$$ H ∞ control theory to actively suppress attack impacts. Simulations show that the proposed method reduces AE mean squared error by nearly 30% and improves frequency response stability. These results confirm its effectiveness in detecting FDIAs and enhancing power system security.https://doi.org/10.1007/s42452-025-07251-3Load frequency control (LFC)False data injection attack (FDIA)State-space decompositionSliding mode observer (SMO)Anti-attack control |
| spellingShingle | Chao Hong Zhihong Liang Yiwei Yang Pandeng Li Lin Chen Leyi Bi Yunan Zhang Research on detection and defense methods for false data injection attacks in power systems based on state-space decomposition Discover Applied Sciences Load frequency control (LFC) False data injection attack (FDIA) State-space decomposition Sliding mode observer (SMO) Anti-attack control |
| title | Research on detection and defense methods for false data injection attacks in power systems based on state-space decomposition |
| title_full | Research on detection and defense methods for false data injection attacks in power systems based on state-space decomposition |
| title_fullStr | Research on detection and defense methods for false data injection attacks in power systems based on state-space decomposition |
| title_full_unstemmed | Research on detection and defense methods for false data injection attacks in power systems based on state-space decomposition |
| title_short | Research on detection and defense methods for false data injection attacks in power systems based on state-space decomposition |
| title_sort | research on detection and defense methods for false data injection attacks in power systems based on state space decomposition |
| topic | Load frequency control (LFC) False data injection attack (FDIA) State-space decomposition Sliding mode observer (SMO) Anti-attack control |
| url | https://doi.org/10.1007/s42452-025-07251-3 |
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