新型配电系统运行专用大模型关键技术展望OA

With the large-scale integration of distributed devices and emerging loads,distribution systems face challenges such as structural complexity,dynamic variability,and multi-source risks,overwhelming traditional physics-based modeling and machine learning methods.Large language models(LLM),with their advantages in multi-modal fusion and complex task reasoning,offer a novel approach to revolutionizing operation paradigms.This paper systematically analyzes the technical bottlenecks under the structural evolution and functional transformation of distribution systems,reviews the potential value and current application status of LLMs in power system operation,and highlights their current limitations in grid cognition,functional positioning,and application architecture.In light of this,this paper proposes a technical path for a specialized LLM for distribution system operation,which is founded on building the model's cognitive capabilities for the grid and is characterized by a paradigm of orchestrating various algorithmic tools.Furthermore,it explores the capability system and development directions of this model from three dimensions:situational awareness,task decision-making,and application mode design.Finally,it envisions application prospects for the LLM in risk monitoring,field operation and maintenance,cross-regional generalization,and vehicle network interaction,while emphasizing key technical challenges in data representation,physics-informed mechanism embedding,and reliable deployment,with the aim of providing a reference for the intelligent development of new power distribution systems.