信息通信技术与政策

信息通信技术与政策

信息通信技术与政策 ›› 2026, Vol. 52 ›› Issue (7): 22-30.doi: 10.12267/j.issn.2096-5931.2026.07.004

专题:算电协同技术与应用 上一篇    下一篇

人工智能赋能算电协同的关键技术与实践探索

Key technologies and practice exploration of AI-empowered computing-power synergy

严茂胜, 唐诗琦, 李腾达   

  1. 中国移动上海产业研究院, 上海 201206
  • 收稿日期:2026-06-16 出版日期:2026-07-25 发布日期:2026-07-30
  • 通讯作者: 李腾达, 中国移动上海产业研究院产品专家,工程师,长期从事工业互联网、工业大模型、具身智能、数智化转型等方面的研究工作
  • 作者简介:
    严茂胜, 中国移动上海产业研究院副总经理,高级经济师,长期从事车联网与智能交通、工业互联网、5G+北斗高精定位等方面的研究工作
    唐诗琦, 中国移动上海产业研究院工程师,长期从事工业互联网、人工智能、智慧电力等方面的研究工作

YAN Maosheng, TANG Shiqi, LI Tengda   

  1. China Mobile Shanghai Industrial Research Institute, Shanghai 201206, China
  • Received:2026-06-16 Online:2026-07-25 Published:2026-07-30

摘要:

随着数字经济与人工智能(Artificial Intelligence,AI)产业高速发展,算力需求呈爆发式增长,数据中心能耗居高不下与新型电力系统的新能源消纳压力并存的矛盾日益凸显。算电协同作为解决算力与电力时空供需错配、助力实现绿色低碳发展目标的重要路径,受到产业界与学术界的广泛关注。首先,阐述算电协同的核心概念与发展背景,系统梳理国内外算电协同的政策导向、技术进展与应用现状;其次,从多要素时序智能预测、算电联合四维时空调度、异构算力自适应迁移、多维价值量化评估4个维度,深入论述AI赋能算电协同的关键技术;随后,介绍中国移动在算电协同领域的技术布局与实践探索,并结合沪皖疆跨域算力协同案例分析了应用成效;最后,总结了当前算电协同发展面临的挑战,并对未来发展方向进行了展望。

关键词: 算电协同, AI, 算力网络, 新型电力系统, 需求响应

Abstract:

With the rapid development of digital economy and Artificial Intelligence (AI) industry, the demand for computing power shows explosive growth. The contradiction between the high energy consumption of data centers and the pressure of new energy consumption in new power systems is increasingly prominent. As an important path to solve the spatial-temporal supply and demand mismatch between computing power and power and achieve the green and low-carbon development goals, computing-power synergy has attracted extensive attention from industry and academia. Firstly, this paper expounds the core concept and development background of computing-power synergy, and systematically sorts out the policy orientation, technical progress and application situation at home and abroad. Secondly, it discusses in depth the key technologies of AI-empowered computing-power synergy from four dimensions: multi-element time series intelligent prediction, 4D spatial-temporal joint scheduling, adaptive migration of heterogeneous computing power, and quantitative evaluation of multi-dimensional value. Then, it introduces China Mobile’s technical layout and practical exploration in this field, and analyzes the application effects with one typical case: Shanghai-Anhui-Xinjiang cross-domain computing-power synergy. Finally, it summarizes the current challenges and prospects the future development direction.

Key words: computing-power synergy, AI, computing power network, new power system, demand response

中图分类号: