Track 1: Foundation Models for Scientific Computing in Power Grid Dispatch

面向电网运行调度的科学计算基础模型研究

English: With the massive integration of high-proportion renewable energy and power electronic equipment, the new power system exhibits strong nonlinearity, uncertainty, and coupling. Traditional physics-based numerical methods struggle to meet the demands of real-time dispatch and security analysis. This forum focuses on the frontier research and engineering applications of foundation models for scientific computing in power grid dispatch. It aims to bring together experts from academia and industry to discuss core issues such as modeling theories of physics-informed data fusion, large model architectures for power grids, and model interpretability, thereby driving the deep integration of AI and power systems and providing technical support for building safe and efficient new power systems.

中文: 随着高比例新能源与电力电子设备大规模接入，新型电力系统呈现强非线性、强不确定性与强耦合特征，传统基于物理机理的数值计算方法已难以满足实时调度与安全分析需求。本论坛聚焦科学计算基础模型在电网运行调度领域的前沿研究与工程应用，旨在汇聚学术界与工业界专家，探讨物理机理与数据融合的建模理论、电网专用大模型架构、模型可解释性等核心问题，推动人工智能与电力系统深度融合，为构建安全高效的新型电力系统提供技术支撑。

• Theoretical Systems of Foundation Models for Scientific Computing in Power Grid Dispatch
  电力系统运行调度的科学计算基础模型理论体系
• Data-Physics Hybrid-Driven Construction of Foundation Models for Grid Computing
  数据-机理混合驱动的电网科学计算基础模型构建
• Explainability and Trustworthiness Assessment of Scientific Computing Foundation Models
  科学计算基础模型的可解释性与可信性评估
• Fast Power Flow Calculation and State Estimation Based on Foundation Models
  基于科学计算基础模型的电网快速潮流计算与状态估计
• Small-Sample Learning and Zero-Shot Inference of Foundation Models for Grid Dispatch
  电网运行调度基础模型的小样本学习与零样本推理