湖南电力 ›› 2025, Vol. 45 ›› Issue (6): 126-132.doi: 10.3969/j.issn.1008-0198.2025.06.017

• 配电网与用能技术 • 上一篇    下一篇

适应边缘侧动态压缩感知的配电主站算力资源自适应分配方法

赵旷怡1, 李嘉彬1, 李林2, 陆珊珊1, 吴润泽2, 贾泽晗1, 王子桐1   

  1. 1.国网冀北电力有限公司经济技术研究院,北京 100038;
    2.华北电力大学,北京 102206
  • 收稿日期:2025-08-28 修回日期:2025-09-26 出版日期:2025-12-25 发布日期:2026-01-13
  • 通信作者: 吴润泽(1975),女,博士,副教授,主要研究方向为新通信技术及其在智能电网中的应用。
  • 作者简介:赵旷怡(1988),女,硕士,主要研究方向为电力通信系统。李嘉彬(1998),女,硕士,主要研究方向为电力系统规划与仿真等。李林(2001),女,硕士研究生,主要研究方向为无线传感网高能效数据采集。陆珊珊(1998),女,硕士,主要研究方向为电力通信规划技术。贾泽晗(1998),男,硕士,主要研究方向为电力系统通信、智能电网中多模态通信技术。王子桐(1998),女,硕士,主要研究方向为电力系统规划。
  • 基金资助:
    国网冀北电力有限公司科技项目(SGJBJY00SJJS2500013)

Adaptive Allocation Method of Computing Power Resources for Distribution Master Station Adapted to Dynamic Compressed Sensing on Edge Side

ZHAO Kuangyi1, LI Jiabin1, LI Lin2, LU Shanshan1, WU Runze2, JIA Zehan1, WANG Zitong1   

  1. 1. State Grid Jibei Electric Power Co., Ltd., Economic and Technical Research Institute,Beijing 100038, China;
    2. North China Electric Power University, Beijing 102206, China
  • Received:2025-08-28 Revised:2025-09-26 Online:2025-12-25 Published:2026-01-13

摘要: 近年来随着电力电子设备的高比例接入,配电系统边缘侧数据规模骤增,自适应压缩感知逐渐成为缓解云边带宽压力的关键技术之一,对应的配电主站需对其合理解压以满足差异化业务时延要求,为此提出一种适应边缘侧动态压缩感知的配电主站算力资源自适应分配方法。首先,建立基于算力资源驱动的配电主站解压系统模型。然后,考虑差异化业务时延要求设计算力资源分配收益函数,据此设计对应优化问题。最后,将原始优化问题解耦为算力资源分配层和时间断面设置层,采用KKT(Karush-Kuhn-Tucker)条件及变步长重分配机制分别求解各层对应子问题,进而实现对原始优化问题的高效求解。仿真分析表明,所提方法可通过独特的变步长重分配机制充分发掘算力资源分配效用,灵活适应边缘侧动态压缩过程,保障配电主站对边缘侧的状态感知能力。

关键词: 算力资源, 自适应分配, 边缘侧, 压缩感知, 配电系统

Abstract: In recent years, with the high proportion of power electronic equipment access, the data scale on the edge side of the power distribution system has increased sharply. Adaptive compressed sensing has gradually become one of the key technologies to alleviate the bandwidth pressure on the cloud edge. The corresponding distribution master station needs to reasonably decompress it to meet the delay requirements of differentiated business. Therefore, an adaptive allocation method of computing power resources for distribution master station adapted to the dynamic compressed sensing on the edge side is proposed. Firstly, a distribution master station decompression system model driven by computing power resources is established. Then, considering the differentiated business delay requirements, a computing power resource allocation revenue function is designed, and based on this, the corresponding optimization problem is designed. Finally, the original optimization problem is decoupled into the computing power resource allocation layer and the time section setting layer. The KKT(Karush-Kuhn-Tucker) condition and the variable step size reallocation mechanism are adopted to solve the corresponding sub-problems of each layer respectively, thereby achieving efficient solution of the original optimization problem. Simulation analysis shows that the proposed method can fully explore the utility of computing power resource allocation through a unique variable step size reallocation mechanism, flexibly adapt to the dynamic compression process on the edge side, and ensure the state perception ability of the distribution master station on the edge side.

Key words: computing power resources, adaptive allocation, edge side, compressed sensing, power distribution system

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