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Techno-Economic Feasibility Analysis of Quantum Key Distribution for Power-System Communications

Published: October 17, 2025 | arXiv ID: 2510.15248v1

By: Ziqing Zhu

Potential Business Impact:

Secures power grids from hackers using quantum.

Business Areas:
Quantum Computing Science and Engineering

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.

Page Count
10 pages

Category
Electrical Engineering and Systems Science:
Systems and Control