上海交通大学学报 ›› 2026, Vol. 60 ›› Issue (4): 652-663.doi: 10.16183/j.cnki.jsjtu.2024.231

• 新型电力系统与综合能源 • 上一篇    下一篇

基于云原生的新型电力系统数字能源终端模型与方法

蔡田田1, 蔡泽祥2(), 李俊业1, 屈径2, 李晓华2, 郑竣杰2   

  1. 1 南方电网数字电网研究院股份有限公司, 广州 510700
    2 华南理工大学 电力学院, 广州 510640
  • 收稿日期:2024-06-17 修回日期:2024-07-19 接受日期:2024-09-30 出版日期:2026-04-28 发布日期:2026-04-29
  • 通讯作者: 蔡泽祥 E-mail:epzxcai@scut.edu.cn
  • 作者简介:蔡田田(1982—),硕士,教授级高工,从事电网数字化、智能化研究.
  • 基金资助:
    南方电网公司科技项目(670000KK52220001)

Models and Methods of Cloud-Native Based New Digital Energy Terminal for Power Systems

CAI Tiantian1, CAI Zexiang2(), LI Junye1, QU Jing2, LI Xiaohua2, ZHENG Junjie2   

  1. 1 China Southern Power Grid Digital Grid Research Institute Co., Ltd., Guangzhou 510700, China
    2 School of Electric Power Engineering, South China University of Technology, Guangzhou 510640, China
  • Received:2024-06-17 Revised:2024-07-19 Accepted:2024-09-30 Online:2026-04-28 Published:2026-04-29
  • Contact: CAI Zexiang E-mail:epzxcai@scut.edu.cn

摘要:

在分布式特征日益凸显的背景下,数字化技术正加速向配用电侧延伸,电力终端将逐步演化为“数字能源终端”,在边缘侧提供对象接入和数字化能源电力管理服务,而云原生是支撑这一转型的关键技术基础.本文分析了海量分布式对象驱动的数字能源终端需求,提出基于云原生的数字能源终端要素、架构和业务组织方式.然后,以算力供需平衡为主线,分析数字能源终端相关的业务模型、算力资源模型和算力供需匹配优化方法.最后,对基于云原生的数字能源终端技术生态进行了展望.本文试图将“云原生-能源电力终端”领域内已有工作统一到基于云原生的新型电力系统数字能源终端的框架,指出云原生技术将重塑数字能源终端的架构、功能和运营模式,对支撑能源电力系统数字化转型、培育能源电力行业新生态具有重要意义.

关键词: 数字能源终端, 云原生, 算力负荷, 算力资源, 算力供需平衡

Abstract:

With the increasing prominence of distributed characteristics driven by digital technologies extending to the distribution and utilization side, power terminals are evolving into “digital energy terminals” that provide object access and digital energy services at the edge. Cloud-native technology is the key technical foundation supporting this transformation. This paper analyzes the demand for digital energy terminals driven by a massive number of distributed objects and proposes the elements, architecture, and business organization of cloud-native digital energy terminals. Next, with the balance of computing supply and demand as the main thread, it analyzes related business models, computing resource models, and optimization methods for computing supply-demand matching of digital energy terminals. Finally, it envisions the technological ecosystem of cloud-native digital energy terminals. This paper attempts to unify existing work in the “cloud-native-energy and power terminals” domain under the framework of cloud-native digital energy terminals for next-generation power systems, highlighting that cloud-native technology will reshape the architecture, functionality, and operational model of digital energy terminals. This has significant implications for supporting the digital transformation of energy power systems and fostering a new ecosystem in the energy power industry.

Key words: digital energy terminal (DET), cloud-native, computing load, computing resources, computing power supply-demand balance

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