Optimal Deception Strategies in Power System Fortification against Deliberate Attacks

Peng Jiang, Shengjun Huang and Tao Zhang
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Peng Jiang: College of Systems Engineering, National University of Defense Technology, Changsha 410073, China
Shengjun Huang: College of Systems Engineering, National University of Defense Technology, Changsha 410073, China
Tao Zhang: College of Systems Engineering, National University of Defense Technology, Changsha 410073, China

Energies, 2019, vol. 12, issue 3, 1-20

Abstract: As a critical infrastructure, the modern electrical network is faced with various types of threats, such as accidental natural disaster attacks and deliberate artificial attacks, thus the power system fortification has attracted great concerns in the community of academic, industry, and military. Nevertheless, the attacker is commonly assumed to be capable of accessing all information in the literature (e.g., network configuration and defensive plan are explicitly provided to the attacker), which might always be the truth since the grid data access permission is usually restricted. In this paper, the information asymmetry between defender and attacker is investigated, leading to an optimal deception strategy problem for power system fortification. Both the proposed deception and traditional protection strategies are formulated as a tri-level mixed-integer linear programming (MILP) problem and solved via two-stage robust optimization (RO) framework and the column-and-constraint generation (CCG) algorithm. Comprehensive case studies on the 6-bus system and IEEE 57-bus system are implemented to reveal the difference between these two strategies and identify the significance of information deception. Numerical results indicate that deception strategy is superior to protection strategy. In addition, detailed discussions on the performance evaluation and convergence analysis are presented as well.

Keywords: two-stage robust optimization; power system fortification; deception strategies; column-and-constraint generation; information asymmetry (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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