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.
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.
The proliferation of distributed energy resources (DERs) and demand-side flexibility has made virtual power plants (VPPs) central to modern grid operation. Yet their end-to-end business pipeline, covering bidding, dispatch, metering, settlement, and archival, forms a tightly coupled cyber-physical-economic system where secure and timely communication is critical. Under the combined stress of sophisticated cyberattacks and extreme weather shocks, conventional cryptography offers limited long-term protection. Quantum key distribution (QKD), with information-theoretic guarantees, is viewed as a gold standard for securing critical infrastructures. However, limited key generation rates, routing capacity, and system overhead render key allocation a pressing challenge: scarce quantum keys must be scheduled across heterogeneous processes to minimize residual risk while maintaining latency guarantees. This paper introduces a quantum-authenticated aggregation and settlement framework for VPPs. We first develop a system-threat model that connects QKD key generation and routing with business-layer security strategies, authentication strength, refresh frequency, and delay constraints. Building on this, we formulate a key-budgeted risk minimization problem that jointly accounts for economic risk, service-level violations, and key-budget feasibility, and reveal a threshold property linking marginal security value to shadow prices. Case studies on a representative VPP system demonstrate that the proposed approach significantly reduces residual risk and SLA violations, enhances key efficiency and robustness, and aligns observed dynamics with the theoretical shadow price mechanism.
This study proposes a lightweight industrial control protocol based on quantum key distribution (QKD) to enhance security and optimize performance in resource-constrained industrial control systems (ICS). Unlike traditional QKD schemes, primarily optimized for long-distance communication in ideal IT environments, this work introduces a resource-aware QKD architecture tailored explicitly for short-range industrial control networks with constrained computing/storage/bandwidth. The protocol constructs a multi-layered stack—integrating the physical layer, quantum key management layer, data link layer, network layer, and application layer—to enable secure quantum key generation, efficient distribution, and dynamic utilization, while avoiding excessive resource overhead on embedded ICS devices. Furthermore, three key optimization strategies are introduced: (1) resource optimization adopts AES-128 with FPGA acceleration, reducing encryption overhead from 15% to 20% CPU utilization to 3%–5% (validated in Sec. V A); (2) real-time assurance implements deficit-round-robin frame scheduling, guaranteeing <2.5 ms latency for safety-critical commands; and (3) stability enhancement utilizes dual-QKD-link redundancy with 5–8 s failover, improving MTBF from 3000 to 10 000+ h. The security real-time trade-off is quantified via coefficient B = Slevel/(Ddelay × δ) (detailed in Sec. V B), where Slevel ∈ [1,10] represents encryption strength, Ddelay is measured latency, and δ is CPU load. Experimental results show that the balance coefficient B improves from 2.1 ± 0.4 (Modbus) to 5.2 ± 0.6, confirming superior balance. This work provides a feasible technical pathway for securing critical infrastructure in the quantum era. Experiments demonstrate a 75% reduction in computational overhead and a real-time-security balance coefficient of 4.5–6.0, which is higher than that of Modbus and PROFINET.
Virtual power plants (VPPs) are becoming a cornerstone of future grids, aggregating distributed PV, wind, storage, and flexible loads for market participation and real-time balancing. As operations move to minute-- and second--level feedback, communication security shifts from a compliance item to an operational constraint: latency, reliability, and confidentiality jointly determine whether dispatch, protection, and settlement signals arrive on time. Conventional PKI and key-rotation schemes struggle with cross-domain, high-frequency messaging and face long-term quantum threats. Quantum key distribution (QKD) offers information-theoretic key freshness, but its key yield is scarce and stochastic, often misaligned with bursty VPP traffic. This paper proposes a key-aware priority and quota framework that treats quantum keys as first-class scheduling resources. The design combines (i) forecast-driven long-term quotas and short-term tokens, (ii) key-aware deficit-round-robin arbitration, (iii) a preemptive emergency key reserve, and (iv) graceful degradation via encryption-mode switching and controlled down-sampling for non-critical traffic. A drift-plus-penalty analysis establishes strong stability under average supply--demand balance with quantifiable bounds on backlog and tail latency, providing interpretable operating guarantees. We build a reproducible testbed on IEEE 33- and 123-bus VPP systems and evaluate normal, degraded, and outage regimes with industry-consistent message classes and TTLs. Against FIFO, fixed-priority, and static-quota baselines, the proposed scheme consistently reduces tail delay and passive timeouts for critical messages, improves per-bit key utility, and enhances power-tracking reliability during key scarcity and regime switches.
The accelerating digitalization and decentralization of modern power systems expose critical communication infrastructures to escalating cyber risks, particularly under emerging quantum computing threats. This paper presents an integrated techno-economic framework to evaluate the feasibility of Quantum Key Distribution (QKD) for secure power-system communications. A stochastic system model is developed to jointly capture time-varying key demand, QKD supply under optical-loss constraints, station-side buffering, and post-quantum cryptography (PQC) fallback mechanisms. Analytical conditions are derived for service-level assurance, including buffer stability, outage probability, and availability bounds. Building on this, two quantitative metrics, including the Levelized Cost of Security (LCoSec) and Cost of Incremental Security (CIS), are formulated to unify capital, operational, and risk-related expenditures within a discounted net-present-value framework. Using IEEE 118-bus, 123-node, and 39-bus test systems, we conduct discrete-event simulations comparing PQC-only, QKD-only, and Hybrid architectures across multiple topologies and service profiles. Results show that Hybrid architectures dominated by QKD significantly reduce key-outage probability and SLA shortfalls, achieving near-unit availability for real-time and confidentiality-critical services. Economic analyses reveal clear breakeven zones where QKD-enhanced deployments become cost-effective, primarily in metropolitan and distribution-level networks under moderate optical loss and buffer sizing. The proposed framework provides a reproducible, risk-aware decision tool for guiding large-scale, economically justified QKD adoption in future resilient power-system infrastructures.
With the development of smart grids, the demand for cybersecurity is increasing rapidly. Quantum Key Distribution (QKD), which can theoretically achieve secure information transmission, has the potential to enhance the security of power communication. To overcome the structural limitations and resource constraints of current QKD-based communication schemes, this paper proposes a multi-resource hybrid QKD-based communication scheme for power grids. This scheme meets the diverse secure communication needs of power systems through the coordinated utilization of multiple QKD resources. First, the advantages and disadvantages of satellite, fiber, and wireless QKD methods, along with their respective application scenarios, are analyzed. Then, considering the synergistic effects of hybrid QKD and the varied demands of power businesses, a quantum resource deployment optimization model is established. This model aims to minimize the system’s information risk index and is reformulated as a solvable mixed-integer linear programming (MILP) problem. Finally, the effectiveness of the proposed scheme is validated using a modified IEEE RTS-79 test system and two real-world power communication systems. By analyzing on sensitivity, adaptability, scalability and IoT applications of various QKD methods, this study provides valuable insights for the large-scale deployment of quantum-secure power communication networks in the future.
The increasing interconnection of smart-grid operational technology, industrial-edge services, and utility information systems creates a critical need for resilient and continuously monitored industrial cyber-physical communication. Although quantum key distribution (QKD) can strengthen session-key establishment for advanced metering infrastructure, distributed energy resources, substation automation, supervisory control, and utility-core services, practical QKD deployments remain vulnerable to implementation-level side-channel attacks that can compromise the cryptographic protection layer without directly targeting conventional network packets. This paper presents a QKD-secured industrial smart-grid cyber-physical system framework for simulating and detecting adaptive side-channel attacks. The proposed 36-node industrial communication architecture integrates AMI devices, DER controllers, PMU and substation automation components, industrial-edge gateways, QKD modules, key-management services, SCADA and utility-core servers, security-operation-center components, and adversarial access points. A 100,000-record cyber-quantum dataset is generated across 12 operating conditions comprising normal communication and 11 adaptive QKD side-channel attacks: detector blinding, time shift, wavelength switching, Trojan-horse probing, photon-number splitting, decoy-state spoofing, RNG bias, calibration manipulation, local-oscillator manipulation, synchronization spoofing, and combined adaptive quantum hacking. Each scenario introduces coupled primary and secondary perturbations across optical, detector, timing, synchronization, randomness, calibration, photon-statistical, leakage, key-generation, encryption, and industrial-network-performance features. To support intelligent industrial security monitoring, the proposed Quantum-aware Mamba–Kolmogorov–Arnold Network (Q-MambaKAN) organizes device, network, QKD, side-channel, encryption, and risk evidence into an ordered cyber-quantum representation processed through selective state-space learning, side-channel attention, nonlinear KAN mapping, adaptive fusion, and multi-task prediction heads. Results show that the QBER increases from 0.071 during normal operation to 0.426 under combined adaptive quantum hacking, while encryption success decreases from 98.1% to 0%. Q-MambaKAN achieves a 99.48% binary detection accuracy, a 99.70% binary F1-score, a 97.60% multiclass macro-F1, and a risk RMSE of 0.021.