Vulnerability Assessment of Large-scale Power Systems to False Data Injection Attacks

This paper studies the vulnerability of large-scale power systems to false data injection (FDI) attacks through their physical consequences. An attacker-defender bi-level linear program (ADBLP) can be used to determine the worst-case consequences of FDI attacks aiming to maximize the physical power flow on a target line. This ADBLP can be transformed into a single-level mixed-integer linear program (MILP), but it is numerically intractable for power systems with a large number of buses and branches. In this paper, a modified Benders’ decomposition algorithm is proposed to solve the ADBLP on large power systems without converting it to the MILP. Of more general interest, the proposed algorithm can be used to solve any ADBLP. Vulnerability of the IEEE 118-bus system and the Polish system with 2383 buses to FDI attacks is assessed using the proposed algorithm.

[1]  Oliver Kosut,et al.  Vulnerability Analysis and Consequences of False Data Injection Attack on Power System State Estimation , 2015, IEEE Transactions on Power Systems.

[2]  A. M. Geoffrion Generalized Benders decomposition , 1972 .

[3]  Zuyi Li,et al.  Modeling Load Redistribution Attacks in Power Systems , 2011, IEEE Transactions on Smart Grid.

[4]  Zuyi Li,et al.  Quantitative Analysis of Load Redistribution Attacks in Power Systems , 2012, IEEE Transactions on Parallel and Distributed Systems.

[5]  Lalitha Sankar,et al.  Physical System Consequences of Unobservable State-and-Topology Cyber-Physical Attacks , 2016, IEEE Transactions on Smart Grid.

[6]  Bethany L. Nicholson,et al.  Mathematical Programs with Equilibrium Constraints , 2021, Pyomo — Optimization Modeling in Python.

[7]  Lang Tong,et al.  Impact of Data Quality on Real-Time Locational Marginal Price , 2012, IEEE Transactions on Power Systems.

[8]  Stephen P. Boyd,et al.  Convex Optimization , 2004, Algorithms and Theory of Computation Handbook.

[9]  Lang Tong,et al.  Malicious Data Attacks on the Smart Grid , 2011, IEEE Transactions on Smart Grid.

[10]  José Mario Martínez,et al.  On the solution of mathematical programming problems with equilibrium constraints , 2001, Math. Methods Oper. Res..

[11]  Kory W. Hedman,et al.  Computationally Efficient Adjustment of FACTS Set Points in DC Optimal Power Flow With Shift Factor Structure , 2017, IEEE Transactions on Power Systems.

[12]  Kerem Bülbül,et al.  Simultaneous column-and-row generation for large-scale linear programs with column-dependent-rows , 2013, Math. Program..

[13]  Zuyi Li,et al.  False Data Injection Attacks Induced Sequential Outages in Power Systems , 2019, IEEE Transactions on Power Systems.

[14]  L. Mathiesen Computation of economic equilibria by a sequence of linear complementarity problems , 1985 .

[15]  Peng Ning,et al.  False data injection attacks against state estimation in electric power grids , 2011, TSEC.

[16]  K. Arrow,et al.  EXISTENCE OF AN EQUILIBRIUM FOR A COMPETITIVE ECONOMY , 1954 .

[17]  Zhigang Chu,et al.  False data injection attacks on power system state estimation with limited information , 2016, 2016 IEEE Power and Energy Society General Meeting (PESGM).

[18]  J. Salmeron,et al.  Analysis of electric grid security under terrorist threat , 2004, IEEE Transactions on Power Systems.

[19]  George B. Dantzig,et al.  Decomposition Principle for Linear Programs , 1960 .

[20]  M. Lübbecke Column Generation , 2010 .

[21]  I. Grossmann,et al.  Convergence properties of generalized benders decomposition , 1991 .

[22]  Ramin Moslemi,et al.  Design of robust profitable false data injection attacks in multi-settlement electricity markets , 2017 .

[23]  Zhigang Chu,et al.  Evaluating power system vulnerability to false data injection attacks via scalable optimization , 2016, 2016 IEEE International Conference on Smart Grid Communications (SmartGridComm).

[24]  Michael A. Saunders,et al.  SNOPT: An SQP Algorithm for Large-Scale Constrained Optimization , 2002, SIAM J. Optim..

[25]  Oliver Kosut,et al.  Cyber attacks on AC state estimation: Unobservability and physical consequences , 2014, 2014 IEEE PES General Meeting | Conference & Exposition.

[26]  Steven P. Dirkse,et al.  Mathematical Programs with Equilibrium Constraints : Automatic Reformulation and Solution via Constrained Optimization ∗ , 2002 .

[27]  Gabriela Hug,et al.  Vulnerability Assessment of AC State Estimation With Respect to False Data Injection Cyber-Attacks , 2012, IEEE Transactions on Smart Grid.

[28]  Svante Janson,et al.  The Birth of the Giant Component , 1993, Random Struct. Algorithms.

[29]  Deepa Kundur,et al.  Towards a Framework for Cyber Attack Impact Analysis of the Electric Smart Grid , 2010, 2010 First IEEE International Conference on Smart Grid Communications.

[30]  Lang Tong,et al.  On Topology Attack of a Smart Grid: Undetectable Attacks and Countermeasures , 2013, IEEE Journal on Selected Areas in Communications.

[31]  Gerald G. Brown,et al.  Solving Defender-Attacker-Defender Models for Infrastructure Defense , 2011, ICS 2011.

[32]  Zuyi Li,et al.  Local Topology Attacks in Smart Grids , 2017, IEEE Transactions on Smart Grid.

[33]  Bruno Sinopoli,et al.  Integrity Data Attacks in Power Market Operations , 2011, IEEE Transactions on Smart Grid.

[34]  Jacques F. Benders,et al.  Partitioning procedures for solving mixed-variables programming problems , 2005, Comput. Manag. Sci..