量子计算在下一代智能电网运行中的应用：综合评述

中文摘要 AI 辅助

电网边缘分布式能源资源的快速增长显著增加了现代电力系统的运行复杂性。因此，传统计算技术在应对智能电网运行中的大规模优化与控制、不确定性管理、非线性动力学以及组合决策问题时，面临着日益严峻的可扩展性和计算效率挑战。量子计算因此成为一种有前景的计算范式，可在处理选定的计算密集型问题时补充经典方法。在此背景下，本文对量子计算在智能电网运行中的应用进行了全面的结构化评述。遵循基于关键词的透明文献检索，本文对现有研究进行了分类和评估，涵盖监测与估计、系统规划、运行与控制、安全、可靠性与韧性、稳定性评估、数据驱动智能以及数字孪生技术等方面。本文还描述了量子计算的基本概念和关键算法，强调了它们与电力系统应用的相关性。此外，本文回顾了量子硬件、软件框架、模拟器、云服务以及新兴的硬件无关生态系统的当前状态，这些生态系统支持跨平台应用开发和部署。本文从实施环境、基准测试实践、应用规模以及计算优势的证据等方面对评述的研究进行了考察。最后，讨论了实际实施面临的主要挑战，并概述了未来的研究方向。本文为量子计算在下一代智能电网运行中的现状和未来潜力提供了一个综合且基于证据校准的视角。

英文摘要

The rapid proliferation of grid-edge distributed energy resources has significantly increased the operational complexity of modern power systems. Consequently, conventional computational techniques face growing scalability and computational-efficiency challenges in addressing large-scale optimization and control, uncertainty management, nonlinear dynamics, and combinatorial decision-making in smart grid operations. Quantum computing has therefore emerged as a promising computational paradigm that can complement classical methods in addressing selected computationally intensive problems. In this context, this paper presents a comprehensive structured review of quantum computing applications in smart grid operations. Following a transparent keyword-based literature search, the paper classifies and assesses existing studies across monitoring and estimation, system planning, operation and control, security, reliability and resilience, stability assessment, data-driven intelligence, and digital twin technologies. The paper also describes fundamental quantum-computing concepts and key algorithms, highlighting their relevance for power system applications. Furthermore, it reviews the current state of quantum hardware, software frameworks, simulators, cloud services, and emerging hardware-agnostic ecosystems that support cross-platform application development and deployment. The reviewed studies are examined by implementation environment, benchmarking practices, application scale, and evidence of computational advantage. Finally, the principal challenges associated with practical implementation are discussed, and future research directions are outlined. This paper provides a consolidated and evidence-calibrated perspective on the current state and future potential of quantum computing for next-generation smart grid operations.

发表机构

• Penn State Harrisburg（宾夕法尼亚州立大学哈里斯堡分校）

机构由 AI 辅助整理，请以论文原文为准。