Power generation allocation of cyber–physical power systems from a defense–attack–defense perspective
Zhengcheng Dong, Meng Tian, Mian Gang Tang, Jiaqi Liang
Abstract
Cyber–physical power systems have emerged as intelligent devices integrate into traditional power systems. These systems, featuring an integration of the physical and cyber components, are exposed to compounded risks from both realms. This paper explores the optimization of generation node allocation with a defense–attack–defense perspective to bolster the system’s resistance to external deliberate attacks. A trilevel optimization model is introduced, addressing the complications arising from communication line failures. This model encompasses upper-level defenders orchestrating generation allocation, middle-level attackers executing deliberate attacks, and lower-level operators optimizing system performance. The model leverages the Column-and-Constraint Generation (C&CG) approach to derive the optimal generation allocation strategy. Empirical validation using two IEEE test cases demonstrates the model’s effectiveness. Results highlight a significant escalation in total load loss upon communication line failures, and underscore the critical role of decentralized generation allocation in enhancing system resilience. These findings hold the potential to inform strategies for safeguarding cyber–physical power systems and reinforcing the architecture of resilient smart grids.