QSTAformer: A Quantum-Enhanced Transformer for Robust Short-Term Voltage Stability Assessment against Adversarial Attacks

Abstract--Short-term voltage stability assessment (STVSA) is critical for secure power system operation. While classical machine learning-based methods have demonstrated strong performance, they still face challenges in robustness under adversarial conditions. This paper proposes QST Aformer--a tailored quantum-enhanced Transformer architecture that embeds parameterized quantum circuits (PQCs) into attention mechanisms--for robust and efficient STVSA. A dedicated adversarial training strategy is developed to defend against both white-box and gray-box attacks. Furthermore, diverse PQC architectures are benchmarked to explore trade-offs between expressiveness, convergence, and efficiency. T o the best of our knowledge, this is the first work to systematically investigate the adversarial vulnerability of quantum machine learning-based STVSA. Case studies on the IEEE 39-bus system demonstrate that QST Aformer achieves competitive accuracy, reduced complexity, and stronger robustness, underscoring its potential for secure and scalable STVSA under adversarial conditions. ITH the high penetration of converter-interfaced renewable energy sources and the growing deployment of fast-acting power electronic devices, maintaining short-term voltage stability (STVS) in modern power systems has become a pressing challenge [1]. STVS characterizes a power system's ability to preserve acceptable voltage profiles during the initial seconds following a disturbance [2], and this stability is primarily influenced by the dynamic behavior of fast acting loads, Li is with the School of Electrical Engineering, Northeast Electric Power University, Jilin 132012, China (e-mail: liyang@neepu.edu.cn). C. Ma is with State Grid Shandong Electric Power Company Jiaozhou Power Supply Company, Jiaozhou 266300, China (email:machong58112233@163.com). Z. Li is with the School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan 430074, China (email: Y uanzheng Li@hust.edu.cn). Sen Li is with the Department of Civil and Environmental Engineering, The Hong Kong University of Science and Technology, Hong Kong.