配电网重构的大模型动态调用启发式优化方法及求解器
By constructing a heuristic optimization model library and a domain-specific large language model, the distribution network status is perceived in real time, and the optimization model is dynamically invoked and adjusted. This solves the problems of insufficient efficiency, accuracy and reliability in the distribution network reconfiguration process in existing technologies, and realizes the output of efficient and reliable reconfiguration schemes.
CN122047017BActive Publication Date: 2026-07-17ZHEJIANG UNIV +1
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- ZHEJIANG UNIV
- Filing Date
- 2026-04-17
- Publication Date
- 2026-07-17
Smart Images
Figure CN122047017B_ABST
Abstract
本申请提供一种配电网重构的大模型动态调用启发式优化方法及求解器，本申请涉及智能电网技术领域，通过构建一个包含多种不同优化偏好的启发式优化模型库；实时感知配电网状态，由能够理解配电网状态与运行指标间的因果关系的领域大语言模型作为智能调度中枢，动态分析当前情境，并从预构建的模型库中筛选、评估并调用最适配的启发式优化模型进行迭代求解，输出最优的配电网络重构方案。对已执行的配电网重构方案进行评估，得到用于训练领域大语言模型的新的大语言模型进行强化学习训练，优化其未来的模型调度与决策能力；基于此，实现在配电网重构过程中兼顾效率、精度与可靠性的目的。
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