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电力人工智能的演变与展望——从专业智能走向通用智能

Retrospect and Prospect of Artificial Intelligence for Electric Power System-From Domain Intelligence to General Intelligence
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摘要 新型电力系统快速发展背景下,海量多源异构信息与多类型业务深度耦合,电力系统运行面临着强复杂性、随机性等挑战。同时,加快构建灵活智能的新型电力系统是能源发展的重要战略,亟须形成具备智慧性、自适应性、安全性的电力人工智能技术体系,推动新型电力系统智能化转型发展。文中对电力人工智能技术的演变过程与研究现状进行回顾总结;分析了以预训练多模态大模型为基础的新一代电力人工智能(AI EPS)的技术框架、原理与关键技术方法;提出了电力大模型技术在电力系统感知预测、调控决策与运行规划等场景的应用方案;阐述了基于电力大模型的电力人工智能面临的技术难点与应用瓶颈。最后,对电力通用人工智能技术应用进行了总结与展望。 In the background of rapid development of new power systems,the deep coupling between massive multi-source heterogeneous information and diverse business brings significant challenges such as strong complexity and randomness in the power system operation.Concurrently,accelerating the construction of a flexible and intelligent new power system is a crucial strategy for energy development.There is an urgent need to establish a technology system of artificial intelligence for electric power system(AI EPS)that is intelligent,self-adaptive,and secure,in order to promote the intelligent transformation and development of the new power system.This paper reviews and summarizes the evolution and current research status of AI EPS technologies.It analyzes the technical framework,principles,and key technical methods for the new generation of AI EPS,which is based on pretrained multimodal large models.The application schemes for power large model technology in the scenarios such as perception prediction,dispatching and control decision-making,and operation planning are proposed.The technical challenges and application bottlenecks faced by electric artificial intelligence based on power large models are discussed.Finally,the application of electric artificial general intelligence technology is summarized and prospected.
作者 李鹏 余涛 李立浧 张孝顺 潘振宁 黄文琦 黄展鸿 LI Peng;YU Tao;LI Licheng;ZHANG Xiaoshun;PAN Zhenning;HUANG Wenqi;HUANG Zhanhong(Novel Electric Power System(Beijing)Research Institute of China Southern Power Grid,Beijing 102209,China;School of Electric Power Engineering,South China University of Technology,Guangzhou 510640,China;China Southern Power Grid Co.,Ltd.,Guangzhou 510623,China;Foshan Graduate School of Innovation,Northeastern University,Foshan 528311,China)
出处 《电力系统自动化》 EI CSCD 北大核心 2024年第16期1-17,共17页 Automation of Electric Power Systems
基金 国家自然科学基金资助项目(52207105)。
关键词 新型电力系统 人工智能 大模型 数据驱动 new power system artificial intelligence large model data-driven
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