Dynamic-Key-Aware Co-Simulation Framework for Next Generation of SCADA Systems Encrypted by Quantum-Key-Distribution Techniques

TL;DR

This work tackles securing power-grid SCADA under quantum-key constraints by developing a unified multi-layer model that links QKD key generation, consumption, and inventory to control latency and reconfiguration. It introduces a chance-constrained, bilevel Stackelberg optimization solved via a novel LD-CP algorithm to fairly allocate scarce keys between TSO and DSO while maintaining grid performance. An end-to-end co-simulation platform integrating OpenQKD-Sim, Q3P/IEC-104, and Grafana enables reproducible evaluation on IEEE benchmark systems, demonstrating improved task success, reduced frequency deviations, and higher key utilization under dynamic link conditions. The results highlight the practical impact of joint quantum-security and control optimization for future quantum-secure grid operations.

Abstract

To address growing cybersecurity challenges in modern power dispatch systems, this paper proposes a multi-layer modeling and optimization framework for SCADA systems enhanced with quantum key distribution (QKD). While most existing applications of QKD in the power sector focus on building secure point-to-point communication tunnels, they rarely consider the system-level coupling between key dynamics and control scheduling. In contrast, our approach integrates quantum key generation, consumption, inventory prediction, and control latency into a unified model, enabling key-aware reconfiguration of SCADA control chains based on task security demands and real-time resource constraints. To resolve conflicts in key resource allocation between transmission system operators (TSOs) and distribution system operators (DSOs), we formulate a bi-level Stackelberg game and transform it into a mathematical program with complementarity constraints (MPCC). We further develop an efficient Level Decomposition-Complementarity Pruning (LD-CP) algorithm to solve the problem. To support reproducible evaluation, we build an end-to-end co-simulation platform that integrates physical-layer disruptions via OpenQKD-Sim, Q3P/IEC-104 protocol stack binding, and real-time control-chain monitoring through Grafana. Experimental results on the IEEE 39- and 118-bus systems show that our method increases task success rate by 25%, reduces peak frequency deviation by 70%, and improves key utilization to 83%. This work lays the foundation for future quantum-secure control systems in power grid operations.

Figures (4)

• Figure 1: Control Recovery Time Distribution
• Figure 2: Violin–Box Plot of Key-Fairness Distribution
• Figure 3: LD-CP Iteration Count versus Achieved Fairness
• Figure 4: Heat-Map of Fairness Variability as a Function of Iteration Budget and Link-Break Frequency