Impact analysis of false data injection attacks on power system static security assessment

Chen, Jiongcong; Liang, Gaoqi; Cai, Zexiang; Hu, Chunchao; Xu, Yan; Luo, Fengji; Zhao, Junhua

doi:10.1007/s40565-016-0223-6

Cited by 60 publications

(21 citation statements)

References 29 publications

(31 reference statements)

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“…A typical example of attacks compromising data integrity is False Data Injection (FDI) cyber-attacks [12,56]. The FDI attack is one of the most challenging threats for microgrids, and the impacts of FDI on modern power grids can be unacceptable [57][58][59][60]. In such attacks, hackers can penetrate in communication network without changing the system observability, and system operators may be unaware of any attacks [8,9,52].…”

Section: Attacks On Data Integritymentioning

confidence: 99%

Cyber-Security of Smart Microgrids: A Survey

Nejabatkhah¹,

Liang

et al. 2020

Energies

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In this paper, the cyber-security of smart microgrids is thoroughly discussed. In smart grids, the cyber system and physical process are tightly coupled. Due to the cyber system’s vulnerabilities, any cyber incidents can have economic and physical impacts on their operations. In power electronics-intensive smart microgrids, cyber-attacks can have much more harmful and devastating effects on their operation and stability due to low inertia, especially in islanded operation. In this paper, the cyber–physical systems in smart microgrids are briefly studied. Then, the cyber-attacks on data availability, integrity, and confidentiality are discussed. Since a false data injection (FDI) attack that compromises the data integrity in the cyber/communication network is one of the most challenging threats for smart microgrids, it is investigated in detail in this paper. Such FDI attacks can target state estimation, voltage and frequency control, and smart microgrids’ protection systems. The economic and physical/technical impacts of the FDI attacks on smart microgrids are also reviewed in this paper. The defensive strategies against FDI attacks are classified into protection strategies, in which selected meter measurements are protected, and detection/mitigation strategies, based on either static or dynamic detection. In this paper, implementation examples of FDI attacks’ construction and detection/mitigation in smart microgrids are provided. Samples of recent cyber-security projects in the world, and critical cyber-security standards of smart grids, are presented. Finally, future trends of cyber-security in smart microgrids are discussed.

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Section: Attacks On Data Integritymentioning

confidence: 99%

Cyber-Security of Smart Microgrids: A Survey

Nejabatkhah¹,

Liang

et al. 2020

Energies

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“…As shown in Reference 86, cyber‐attack is a potential danger for secure operations of the networks. The influences of false data injection attack (FDIA) on the SSS of the grid are studied in Reference 86. FDIA is a kind of cyber‐attacks which leads to malfunction of meters, and inaccurate state estimation process.…”

Section: Special Casesmentioning

confidence: 99%

Static security assessment of power systems: A review

Gholami

Sanjari

Safari

et al. 2020

Int Trans Electr Energ Syst

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Summary The security assessment, based on which determinant decisions should be made for power system design, control and operation, is a challenging issue for utility engineers and network designers, especially in large‐scale power systems. Numerous methods have been proposed and implemented for this purpose, and a variety of indices have been suggested to address the static security condition of power networks. Large‐scale datasets of measurements in continually expanding power systems necessitate advanced knowledge in big data analytics. In this review paper, numerical techniques and machine learning‐based methods are reviewed as two main categories for static security assessment in power systems based on principal features of static security status classification such as type of classifier, the static security index, and feature selection and extraction methods. This paper can be used as a useful reference for static security assessment of power systems.

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“…Bad measurement detection is one of the most important topics in power system estimation [30], [31]. In a large sensor network, the hardware malfunction or cyber-attack may cause the sensors to provide incorrect readings.…”

Section: F Bad Measurement Detectionmentioning

confidence: 99%

Fully Distributed State Estimation for Power System with Information Propagation Algorithm

Cheng

Gao

et al. 2020

Journal of Modern Power Systems and Clean Energy

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In this paper, a new fully distributed state estimation (DSE) based on weighted least square (WLS) method and graph theory is proposed for power system. The proposed method is fully distributed so that the centralized facilities, e.g., supervisory control and data acquisition (SCADA) and centralized estimators, are not required. Also, different from the existing DSE methods, the proposed method is a bus-level DSE method, in which the power system is not required to be partitioned into several areas. In order to realize the proposed fully distributed DSE method, a novel information propagation algorithm is developed in this paper. This algorithm has great potential in future applications since it is useful to broadcast the local information of the nodes to the entire system in a fully distributed network. The proposed DSE method is compared with the conventional centralized state estimation method and existing multi-area DSE method in different models in this paper. The results show that the proposed method has better performance than the traditional methods.

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Impact analysis of false data injection attacks on power system static security assessment

Cited by 60 publications

References 29 publications

Cyber-Security of Smart Microgrids: A Survey

Cyber-Security of Smart Microgrids: A Survey

Static security assessment of power systems: A review

Fully Distributed State Estimation for Power System with Information Propagation Algorithm

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