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.
Highlights
In order to facilitate the community to achieve stable and reliable power supply, a lot of new technologies and equipment are extensively integrated into the modern power grid, such as advanced metering infrastructure (AMI) and intelligent electronic device (IED)
The main contributions of this paper are as follows: (1) the deception conception is proposed and formulated, providing a general framework for more complicated defensive strategies based on information asymmetry in the future; (2) an robust optimization (RO) solution framework for the optimal deception strategy is developed on the basis of column-and-constraint generation (CCG) constraints, and the convergence property is discussed; and
The reason for the smaller number of iterations with deception strategy might be explained from two aspects: (1) the hidden lines reduced the solution space of the subproblem, resulting in the worst attack plan being easy to be found; (2) the hidden lines changed the configuration of subproblem solution space, leading to the CCG constraints being capable of eliminating more intermediate solutions; and (3) the variation on objectives between defender and attacker makes their decisions be diametrically opposed, resulting in the room for bargaining is limited, the number of iterations is smaller
Summary
In order to facilitate the community to achieve stable and reliable power supply, a lot of new technologies and equipment are extensively integrated into the modern power grid, such as advanced metering infrastructure (AMI) and intelligent electronic device (IED). The CCG method is proposed in [20] and [21], whose performance in RO framework has been extensively verified on different types of power system optimization problems, such as transmission expansion planning [22], economic dispatch [23], unit commitment [24], and distribution network reconfiguration [25], etc. The main contributions of this paper are as follows: (1) the deception conception is proposed and formulated, providing a general framework for more complicated defensive strategies based on information asymmetry in the future; (2) an RO solution framework for the optimal deception strategy is developed on the basis of CCG constraints, and the convergence property is discussed; and (3) comprehensive numerical experiments are implemented to verify the advantageous of deception strategy, including less objective value and faster convergence rate
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