可解释的灾后电网可观测性恢复：基于人工监督的智能体大语言模型
Explainable Post-Disaster Grid Observability Recovery Using Human-Oversight Agentic LLMs
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中文总结 AI 辅助
针对灾后PMU故障导致电网可观测性下降的问题，提出由LLM编排的智能体工具调用框架，协调后端工具实现可解释、可追溯的恢复，并在IEEE 30/57节点系统上达到与MILP相当的恢复效果。
中文摘要 AI 辅助
灾后相量测量单元（PMU）故障会降低电力系统的可观测性，削弱运行人员的态势感知能力，需要在有限资源下进行顺序恢复。现有的基于优化或启发式的PMU恢复方法能够生成恢复计划，但通常在解释性、可追溯性和运行人员交互方面支持有限。本文提出了一种由大语言模型（LLM）编排的智能体工具调用框架，用于灾后PMU恢复和电网可观测性恢复。在该框架中，LLM不直接求解恢复优化问题，而是协调灾后恢复所需的经过验证的后端工具，包括可观测性评估、恢复规划、状态更新和运行人员验证。该框架还维护结构化的工具调用历史和执行上下文，使恢复决策具有可追溯性和可解释性，同时在恢复过程中支持上下文感知的运行人员问答。在IEEE 30节点和IEEE 57节点系统上的仿真结果表明，所提出的框架实现了与混合整数线性规划（MILP）解决方案相当的可观测性恢复，同时提供了基于工具的解释、交互式运行人员支持和人工监督执行。
英文摘要
Post-disaster phasor measurement unit (PMU) outages reduce power-system observability and degrade operator situational awareness, requiring sequential restoration under limited resources. Existing PMU restoration methods based on optimization or heuristics can generate restoration schedules, but they often provide limited support for explanation, traceability, and operator interaction. This paper proposes an agentic tool-calling framework orchestrated by a large language model (LLM) for post-disaster PMU restoration and grid observability recovery. In this framework, the LLM does not directly solve the restoration optimization problem; instead, it coordinates validated backend tools required for post-disaster restoration, including observability assessment, restoration planning, state updates, and operator verification. The framework also maintains a structured tool-call history and execution context that keep restoration decisions traceable and explainable, while enabling context-aware operator question answering during the restoration process. Simulation results on IEEE 30-bus and IEEE 57-bus systems show that the proposed framework achieves observability recovery comparable to a mixed-integer linear programming (MILP) solution, while providing tool-grounded explanations, interactive operator support, and human-overseen execution.
发表机构
- Southern Illinois University Carbondale（南伊利诺伊大学卡本代尔分校）
- Montana State University（蒙大拿州立大学）
机构由 AI 辅助整理，请以论文原文为准。
