面向网络-物理认知：用于实时自主电网运行的统一本体驱动知识图谱
Towards Cyber-Physical Cognition: A Unified Ontology-Driven Knowledge Graph for Real-Time Autonomous Grid Operations
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中文总结 AI 辅助
本文针对电力系统数据碎片化问题，提出基于IEC标准的统一本体驱动知识图谱框架，整合多仿真环境，在基准测试中实现次线性扩展与毫秒级查询，为自主电网运行提供可靠信息支撑。
中文摘要 AI 辅助
现代电力系统与智能电网通常由碎片化且异构的数据孤岛构成，缺乏开展有效跨域分析所需的内聚力。针对这一问题，本文提出一种通用本体框架，用于通过统一知识图谱与具备跨域推理能力的本体，对智能网络-物理电力系统的运行状态进行表征。本研究聚焦于搭建网络-物理仿真器，作为实现上述愿景的过渡步骤。通过建立基于IEC 61970（CIM）与IEC 62351/61850标准的统一语义中间件，该框架将OMNeT++与PowerWorld等不同的网络、物理仿真环境整合为单一知识图谱。对三个标准电力系统基准的评估显示，该框架在知识图谱规模与构建时间上均呈现次线性扩展特性。我们进一步验证了该框架在实时决策支持方面的效能，在知识图谱经历六次累积结构突变的情况下，仍能在两个领域实现毫秒级查询性能。由此生成的统一知识图谱为自主智能电网运行提供了可靠、可扩展的信息库，支持对实际电力系统的复杂分析。
英文摘要
Modern power systems and smart grids are often composed of fragmented and heterogeneous data silos, which lack the cohesion needed for effective cross-domain analysis. For this, this paper introduces a universal ontology framework for the operational representation of intelligent cyber-physical power systems via a unified knowledge graph and an ontology capable of cross-domain reasoning. This work focuses on bridging cyber-physical simulators as a stepping stone towards that vision. By establishing a unified semantic middleware grounded in IEC 61970 (CIM) and IEC 62351/61850 standards, this framework integrates disparate cyber and physical simulation environments, illustrated via OMNeT++ and PowerWorld, into a single knowledge graph. Evaluation across three standard power system benchmarks demonstrates sub-linear scaling in both knowledge graph size and construction time. We further validate the framework's efficacy for real-time decision support, achieving millisecond-level query performance across both domains, maintained across six cumulative structural mutations to the knowledge graph. The resulting unified knowledge graph provides a robust, scalable information corpus for autonomous smart grid operations, enabling complex analysis of real-world power systems.
