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Volume 15
Issue 3
10.3390/electronics15030550
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This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

Topology Robustness of State Estimation Against False Data Injection and Network Parameter Attacks on Power Monitoring and Control Systems

by
Yunhao Yu
1,
Yu Wang
2,
Fuhua Luo
1,
Meiling Dicha
1,
Song Li
3 and
Zhenyong Zhang
4,*
1
Electric Power Dispatching and Control Center, Guizhou Power Grid Co., Ltd., Guiyang 550002, China
2
School of Electrical Engineering, Chongqing University, Chongqing 401331, China
3
China Association for Science and Technology, Beijing 100863, China
4
State Key Laboratory of Public Big Data, College of Computer Science and Technology, Guizhou University, Guiyang 550025, China
*
Author to whom correspondence should be addressed.
Electronics 2026, 15(3), 550; https://doi.org/10.3390/electronics15030550
Submission received: 12 December 2025 / Revised: 21 January 2026 / Accepted: 26 January 2026 / Published: 27 January 2026
(This article belongs to the Section Systems & Control Engineering)
Versions Notes

Abstract

With the integration of information and communication systems, cyberattacks threaten the normal operation of the power grid. As a critical function, state estimation in the power monitoring and control system is an attractive target for attackers. There are two typical cyberattacks—false data injection attack (FDIA) and network parameter attack (NPA)—that produce incorrect state estimation results, threatening the control and operation of the power system. This paper introduces the first theoretical framework for analyzing the topology robustness of state estimation against FDIA, NPA, and coordinated FDIA+NPA, quantifying the inherent tolerance to injected errors under the DC model. Novel contributions include the following: (1) derivation of analytical bounds on relative state errors for FDIA and similar expressions for NPA and coordinated attacks; (2) proof that sensor measurements, network topology, and branch parameters are key factors influencing robustness, with larger robustness factor amplifying errors in dense or partially measured systems; and (3) validation through extensive MATPOWER simulations on IEEE 14-, 30-, 57-, 118-, and 300-bus systems, confirming bound tightness across scales. These insights enable preventive grid design to enhance resilience against cyber-physical threats.
Keywords: power system state estimation; topology robustness; false data injection attack; network parameter attack power system state estimation; topology robustness; false data injection attack; network parameter attack

Share and Cite

MDPI and ACS Style

Yu, Y.; Wang, Y.; Luo, F.; Dicha, M.; Li, S.; Zhang, Z. Topology Robustness of State Estimation Against False Data Injection and Network Parameter Attacks on Power Monitoring and Control Systems. Electronics 2026, 15, 550. https://doi.org/10.3390/electronics15030550

AMA Style

Yu Y, Wang Y, Luo F, Dicha M, Li S, Zhang Z. Topology Robustness of State Estimation Against False Data Injection and Network Parameter Attacks on Power Monitoring and Control Systems. Electronics. 2026; 15(3):550. https://doi.org/10.3390/electronics15030550

Chicago/Turabian Style

Yu, Yunhao, Yu Wang, Fuhua Luo, Meiling Dicha, Song Li, and Zhenyong Zhang. 2026. "Topology Robustness of State Estimation Against False Data Injection and Network Parameter Attacks on Power Monitoring and Control Systems" Electronics 15, no. 3: 550. https://doi.org/10.3390/electronics15030550

APA Style

Yu, Y., Wang, Y., Luo, F., Dicha, M., Li, S., & Zhang, Z. (2026). Topology Robustness of State Estimation Against False Data Injection and Network Parameter Attacks on Power Monitoring and Control Systems. Electronics, 15(3), 550. https://doi.org/10.3390/electronics15030550

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