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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
作者:
作者单位:

1.南方电网新型电力系统(北京)研究院有限公司, 北京市 102209;2.华南理工大学电力学院, 广东省 广州市 510640;3.中国南方电网有限责任公司, 广东省 广州市 510623;4.东北大学佛山研究生创新学院, 广东省 佛山市 528311

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通用人工智能面临的技术难点与应用瓶颈。最后,对电力通用智能技术应用进行了总结与展望。

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基金项目:

国家自然科学基金资助项目(52207105)。

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作者简介:


Retrospect and Prospect of Artificial Intelligence for Electric Power System —From Domain Intelligence to General Intelligence
Author:
Affiliation:

1.New Power System (Beijing) Research Institute Co., Ltd., China Southern Power Grid, Beijing 102209, China;2.School of Electric Power Engineering, South China University of Technology, Guangzhou 510640, China;3.China Southern Power Grid Co., Ltd., Guangzhou 510623, China;4.Foshan Graduate School of Innovation, Northeastern University, Foshan 528311, China

Abstract:

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 methods for the new generation of AI EPS, which is based on pre-trained multimodal large models. The application schemes for large power model technology in scenarios such as perception prediction, control decision-making, and operation planning are proposed. The technical challenges and application bottlenecks faced by electric artificial general intelligence based on large power models are discussed. Finally, the application of electric general intelligence technology is summarized and prospected.

Keywords:

Foundation:
This work is supported by National Natural Science Foundation of China (No. 52207105).
引用本文
[1]李鹏,余涛,李立浧,等.电力人工智能的演变与展望——从专业智能走向通用智能[J/OL].电力系统自动化,http://doi. org/10.7500/AEPS20231226004.
LI Peng, YU Tao, LI Licheng, et al. Retrospect and Prospect of Artificial Intelligence for Electric Power System —From Domain Intelligence to General Intelligence[J/OL]. Automation of Electric Power Systems, http://doi. org/10.7500/AEPS20231226004.
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  • 收稿日期:2023-12-26
  • 最后修改日期:2024-06-27
  • 录用日期:2024-05-28
  • 在线发布日期: 2024-07-08
  • 出版日期: