新能源电力系统全国重点实验室(华北电力大学), 北京市 昌平区,102206
陈晓梅 (1974),女,副教授,研究方向为无线通信网络与新技术、多媒体信息处理与智能计算技术等,E-mail:chxm@ncepu.edu.cn
邓朝龙 (1997),男,硕士研究生,研究方向为电力物联网资源分配,E-mail:chaolong_deng@163.com
刘昊东 (2000),男,硕士研究生,研究方向为电力物联网资源分配,E-mail:lhd20232024@163.com
汤中卫 (1999),男,硕士研究生,研究方向为电力物联网资源分配,E-mail:zhongwei_tang@ncepu.edu.cn
张孙烜 (1998),男,博士研究生,研究方向为电力物联网资源分配,E-mail:sunxuan_zhang@ncepu.edu.cn
周振宇 (1983),男,博士,教授,通信作者,研究方向为无线通信网络与新技术、物联网与现代传感技术、能源互联网信息通信技术等,E-mail:zhenyu_zhou@ncepu.edu.cn
纸质出版:2026
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陈晓梅, 邓朝龙, 刘昊东, 等. 面向配电网数据断面一致性提升的通感资源分配方法[J]. 现代电力, 2026,43(5):897-905.
CHEN Xiaomei, DENG Chaolong, LIU Haodong, et al. A Communication-sensing Resource Allocation Method for Distribution Network Data-section Consistency Improvement[J]. 2026, 43(5): 897-905.
陈晓梅, 邓朝龙, 刘昊东, 等. 面向配电网数据断面一致性提升的通感资源分配方法[J]. 现代电力, 2026,43(5):897-905. DOI: 10.19725/j.cnki.1007-2322.2024.0179.
CHEN Xiaomei, DENG Chaolong, LIU Haodong, et al. A Communication-sensing Resource Allocation Method for Distribution Network Data-section Consistency Improvement[J]. 2026, 43(5): 897-905. DOI: 10.19725/j.cnki.1007-2322.2024.0179.
针对大规模分布式资源参与配电网协同调控场景下有限通感资源难以满足海量终端数据低时延传输和处理需求的问题,构建面向配电网数据断面一致性提升的通感资源一体化分配架构。其次,以最小化网络平均端到端排队时延与时延断面偏差为优化目标,并基于李雅普诺夫理论将优化问题分解为压缩感知模式选择、终端调度优化子问题和时间分配优化子问题。最后,提出基于改进交换匹配的两阶段通感资源分配方法。在第一阶段,引入时延断面偏差和排队时延赤字改进匹配效益函数,通过迭代交换匹配求解最优压缩感知模式选择和终端调度策略;在第二阶段,基于凸优化求解最优时间分配策略。仿真结果表明,所提算法在降低端到端排队时延、提高数据断面一致性等方面具有优异性能。
In the context of large-scale distributed resources participating in cooperative regulation of distribution grids
the limited communication and sensing resources pose great challenges in satisfying the demands of low-latency transmission and processing of massive device data. An integrated communication-sensing resource allocation architecture is constructed to improve the distribution grid data-section consistency. Secondly
aiming to minimize the network average end-to-end queuing delay and delay-section deviation
the optimization problem is decomposed into compressed sensing mode selection
device scheduling optimization subproblem
and time allocation optimization subproblem based on Lyapunov optimization theory. Finally
a two-stage communication-sensing resource allocation method based on enhanced swap matching is proposed. In the first stage
the delay-section deviation and queuing delay deficit are introduced to improve the matching benefit function. Subsequently
the optimal compressed sensing mode selection and device scheduling strategy are solved through iterative swap matching. In the second stage
the optimal time allocation strategy is solved based on convex optimization. Simulation results demonstrate that the proposed algorithm exhibits excellent performance in reducing end-to-end queuing delay and improving the consistency of the data-section.
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