AI4S范式下新型电力系统中长期电力供需协同:内涵与架构OA

With the rapid expansion of renewable energy installations and the widespread integration of heterogeneous energy sources,the medium-and long-term mechanisms of power-energy balance in new power systems are undergoing profound transformation.Traditional power supply-demand coordination technologies have become increasingly inadequate.In the context of the 5th paradigm of scientific research,marked by the emergence of"AI for science(AI4S)",AI technologies,particularly large language models,offer new pathways for an intelligent redesign of power supply-demand coordination architectures.This paper explores the key characteristics of mid-to-long-term power and energy balance in new power systems and identifies the limitations of conventional architectures.It also elucidates the connotation of AI4S-driven supply-demand coordination and proposes a novel architecture framework anchored in three core components:the Power Knowledge Base,Transformation Interface,and Decision Plugin..Furthermore,it promotes the transition from human-centric decision loops toward machine-autonomous reasoning,realizing a technical roadmap toward a full-process"AI+"pattern.Finally,this paper discusses future research directions to provide insights into achieving reliable power supply and efficient renewable energy utilization under AI empowerment.