EN边缘协作与中继辅助联合架构的分布式能源系统信息传输优化方法
Information Transmission Optimization for Distributed Energy Systems via Edge Collaboration and Relay Assistance Joint Architecture
- 中国电力 2025年58卷第11期 页码：135-145
- 作者机构：
东北大学 信息科学与工程学院,辽宁,沈阳,110819
- 作者简介：
- 基金信息：国家自然科学基金资助项目（62303103）;国家自然科学基金资助项目（62373089）;中央高校基本科研业务费专项资金资助项目（N25ZJL020）;辽宁省自然科学基金资助项目（2023-BSBA-140）;辽宁省教育厅科研项目（JYTQN2023161）。
DOI：10.11930/j.issn.1004-9649.202505024
中图分类号：-
网络出版：2025-12-01，
纸质出版：2025-12-01
- 稿件说明：
移动端阅览
张洺瑞, 胡旭光, 王晶宇, 潘慧琳, 杜杭远. 边缘协作与中继辅助联合架构的分布式能源系统信息传输优化方法[J]. 中国电力, 2025, 58(11): 135-145.
ZHANG Mingrui, HU Xuguang, WANG Jingyu, et al. Information Transmission Optimization for Distributed Energy Systems via Edge Collaboration and Relay Assistance Joint Architecture[J]. 2025, 58(11): 135-145.
张洺瑞, 胡旭光, 王晶宇, 潘慧琳, 杜杭远. 边缘协作与中继辅助联合架构的分布式能源系统信息传输优化方法[J]. 中国电力, 2025, 58(11): 135-145. DOI： 10.11930/j.issn.1004-9649.202505024.
ZHANG Mingrui, HU Xuguang, WANG Jingyu, et al. Information Transmission Optimization for Distributed Energy Systems via Edge Collaboration and Relay Assistance Joint Architecture[J]. 2025, 58(11): 135-145. DOI： 10.11930/j.issn.1004-9649.202505024.
摘要
随着分布式能源系统中能源设备逐渐增加，数据传输量激增等问题对能源系统通信网络数据传输的准确性与任务分配的合理性提出了挑战。为此，提出边缘协作与中继辅助联合架构的分布式能源系统信息传输优化方法。首先提出边缘协作与中继辅助联合的分布式能源系统通信网络架构，通过中继辅助承担任务及相邻能源体之间的任务协作，解决通信资源分配不均等问题；其次提出面向非正交多址技术的五隙信息传输框架及能耗成本表示方法，通过对五隙信息整体传输过程建模，解决考虑能耗与偏差的能耗成本量化问题；然后提出协作辅助计算与资源分配算法，通过优化中继功率、执行时间、任务分配，解决五隙传输能耗成本趋优问题。最后对中国某地区分布式能源系统进行测试，结果表明该通信网络架构与传输框架可以有效促进通信资源的合理分配且优化后的通信资源分配策略能显著降低系统的能耗成本。
Abstract
With the surge in data transmission volume from physical terminals in distributed energy systems
the accuracy of data transmission and the rationality of communication task allocation face significant challenges. To address these issues
this paper proposes an optimization method for information transmission in distributed energy systems based on joint edge collaboration and relay assistance architecture. Firstly
a joint edge collaboration and relay-assistance communication network architecture for distributed energy systems is proposed
mitigating communication resource location imbalance by having relay assistance undertake tasks and enabling task collaboration between adjacent energy bodies. Secondly
a five-slot information transmission architecture based on non-orthogonal multiple access (NOMA) technology and an energy consumption cost representation method are proposed to solve the quantification problem of communication costs by modeling the overall transmission process of the five-slot information. Thirdly
a collaboration assistance computing and resource allocation algorithm is proposed to minimize communication costs by optimizing relay power
execution time
and task allocation. Finally
the proposed communication framework and optimization strategy are tested on a distributed energy system in China. The results demonstrate that the proposed approach can effectively promote the reasonable allocation of communication resource and can significantly reduce communication costs.
关键词
Keywords
references
1谭青博, 潘伟, 王竹宁, 等. 新型电力系统下综合能源系统的投资决策模型[J]. 智慧电力, 2023, 51 (8): 46- 52. DOI
TAN Qingbo, PAN Wei, WANG Zhuning, et al. Investment decision model for comprehensive energy system under new power system[J]. Smart Power, 2023, 51 (8): 46- 52. DOI
2张程, 曾崟琳, 匡宇. 考虑需求响应和碳捕集电厂灵活运行方式的综合能源系统调度[J]. 智慧电力, 2024, 52 (9): 88- 95. DOI
ZHANG Cheng, ZENG Yinlin, KUANG Yu. Integrated energy system scheduling considering demand response and flexible operation of carbon capture power plant[J]. Smart Power, 2024, 52 (9): 88- 95. DOI
3康渭滨, 寇明鑫, 张文文, 等. 光伏储能电站不同储能形式经济性对比分析[J]. 电力科技与环保, 2024, 40 (3): 276- 285.
KANG Weibin, KOU Mingxin, ZHANG Wenwen, et al. Economic comparison analysis of different energy storage forms for photovoltaic energy storage power stations[J]. Electric Power Technology and Environmental Protection, 2024, 40 (3): 276- 285.
4吕昊, 何益鸣, 田浩, 等. 基于物联网的园区综合能源系统快速通信网络建模与仿真[J]. 中国电力, 2022, 55 (5): 166- 173.
LV Hao, HE Yiming, TIAN Hao, et al. Modeling and simulation of fast communication network for park integrated energy system based on IoT[J]. Electric Power, 2022, 55 (5): 166- 173.
5孙秋野, 刘广亮, 王一帆. 能源互联网中能源终端的研究综述及展望[J]. 电网技术, 2025, 49 (5): 1792- 1805.
SUN Qiuye, LIU Guangliang, WANG Yifan. Review and prospect of energy terminal in energy Internet[J]. Power System Technology, 2025, 49 (5): 1792- 1805.
6王杰, 郑飞, 张鹏城, 等. 基于数据驱动的高比例新能源配电网规划模型[J]. 中国电力, 2025, 58 (3): 175- 182.
WANG Jie, ZHENG Fei, ZHANG Pengcheng, et al. Model of high-proportion new energy distribution network planning based on data-driven approach[J]. Electric Power, 2025, 58 (3): 175- 182.
7孙秋野, 于潇寒, 王靖傲. “双高”配电系统的挑战与应对措施探讨[J]. 中国电机工程学报, 2024, 44 (18): 7115- 7136.
SUN Qiuye, YU Xiaohan, WANG Jing'ao. Discussion on challenges and countermeasures of "double high" power distribution system[J]. Proceedings of the CSEE, 2024, 44 (18): 7115- 7136.
8陈智雄, 刘宗山, 金鑫, 等. 基于协作通信的电力线通信关键技术研究综述[J]. 电网技术, 2025, 49 (4): 1668- 1680.
CHEN Zhixiong, LIU Zongshan, JIN Xin, et al. Research review and prospect of power line communication technology based on collaborative communication[J]. Power System Technology, 2025, 49 (4): 1668- 1680.
9仝杰, 齐子豪, 蒲天骄, 等. 电力物联网边缘智能: 概念、架构、技术及应用[J]. 中国电机工程学报, 2024, 44 (14): 5473- 5496.
TONG Jie, QI Zihao, PU Tianjiao, et al. Edge intelligence to power Internet of Things: concept, architecture, technology and application[J]. Proceedings of the CSEE, 2024, 44 (14): 5473- 5496.
10王睿, 孙秋野, 张化光, 等. 基于信-能复合调制的多母线直流微电网电流边缘控制策略[J]. 控制与决策, 2023, 38 (10): 2783- 2794.
WANG Rui, SUN Qiuye, ZHANG Huaguang, et al. Current edge-control strategy of multi-bus DC microgrids based on information-energy dual modulation[J]. Control and Decision, 2023, 38 (10): 2783- 2794.
11WANG R, LI J D, SUN Q Y, et al. Current edge-control strategy for multiple energy routers based on cyber-energy dual modulations[J]. IEEE Transactions on Industrial Electronics, 2024, 71 (4): 4079- 4088. DOI
12聂涌泉, 彭超逸, 胡亚平, 等. 基于边缘计算的高渗透率微电网并行分布式优化经济调度[J]. 南方电网技术, 2023, 17 (1): 114- 124.
NIE Yongquan, PENG Chaoyi, HU Yaping, et al. Parallel distributed optimal economic dispatch of high penetration microgrid based on edge computing[J]. Southern Power System Technology, 2023, 17 (1): 114- 124.
13陆旭, 陈影, 许中平, 等. 面向5G边缘计算网络的联合需求响应与任务卸载策略[J]. 中国电力, 2022, 55 (10): 209- 218.
LU Xu, CHEN Ying, XU Zhongping, et al. Joint demand response and task offloading strategy for 5G edge computing network[J]. Electric Power, 2022, 55 (10): 209- 218.
14CHEN X J, WEN H F, NI W, et al. Distributed online optimization of edge computing with mixed power supply of renewable energy and smart grid[J]. IEEE Transactions on Communications, 2022, 70 (1): 389- 403. DOI
15PERVEZ F, SULTANA A, YANG C G, et al. Energy and latency efficient joint communication and computation optimization in a multi-UAV-assisted MEC network[J]. IEEE Transactions on Wireless Communications, 2024, 23 (3): 1728- 1741. DOI
16CONSUL P, BUDHIRAJA I, GARG D, et al. A hybrid task offloading and resource allocation approach for digital twin-empowered UAV-assisted MEC network using federated reinforcement learning for future wireless network[J]. IEEE Transactions on Consumer Electronics, 2024, 70 (1): 3120- 3130. DOI
17ZHANG Z R, WANG N F, WU H M, et al. MR-DRO: a fast and efficient task offloading algorithm in heterogeneous edge/cloud computing environments[J]. IEEE Internet of Things Journal, 2023, 10 (4): 3165- 3178. DOI
18YIN F F, ZENG M Y, ZHANG Z L, et al. Coded caching for smart grid enabled HetNets with resource allocation and energy cooperation[J]. IEEE Transactions on Vehicular Technology, 2020, 69 (10): 12058- 12071. DOI
19司羽飞, 谭阳红, 汪沨, 等. 面向电力物联网的云边协同结构模型[J]. 中国电机工程学报, 2020, 40 (24): 7973- 7979, 8234.
SI Yufei, TAN Yanghong, WANG Feng, et al. Cloud-edge collaborative structure model for power Internet of Things[J]. Proceedings of the CSEE, 2020, 40 (24): 7973- 7979, 8234.
20孙毅, 陈恺, 左强, 等. 考虑5G通信负荷协同优化的云边计算网络能量管理模型[J]. 中国电机工程学报, 2023, 43 (23): 9020- 9033.
SUN Yi, CHEN Kai, ZUO Qiang, et al. Energy management model of cloud-edge computing network considering the coordinated optimization of 5G communication load[J]. Proceedings of the CSEE, 2023, 43 (23): 9020- 9033.
23张爱军, 刘紫玉, 邢华栋, 等. 基于GM估计的电-气-热综合能源系统分解协调鲁棒状态估计方法[J]. 智慧电力, 2023, 51 (10): 9- 14, 53.
ZHANG Aijun, LIU Ziyu, XING Huadong, et al. Decomposition and coordination robust state estimation method for electric-gas-heat integrated energy system based on GM estimation[J]. Smart Power, 2023, 51 (10): 9- 14, 53.
24曹旺斌, 唐宏凯, 谢志远, 等. 下行NOMA-PLC系统最优功率分配方法研究[J]. 中国电机工程学报, 2025, 45 (3): 834- 846.
CAO Wangbin, TANG Hongkai, XIE Zhiyuan, et al. Research on optimal power allocation method in downlink NOMA-PLC system[J]. Proceedings of the CSEE, 2025, 45 (3): 834- 846.
25蒲红红, 刘晓胜, 徐殿国. 基于深度强化学习的协作非正交多址接入网络鲁棒安全传输[J]. 中国电机工程学报, 2022, 42 (13): 4760- 4775.
PU Honghong, LIU Xiaosheng, XU Dianguo. Deep reinforcement learning based robust secure transmission for cooperative non-orthogonal multiple access networks[J]. Proceedings of the CSEE, 2022, 42 (13): 4760- 4775.
26佘蕊, 张宁池, 王艳茹, 等. 面向电力物联网的5G通信认知无线电NOMA系统研究[J]. 中国电力, 2021, 54 (5): 35- 45.
SHE Rui, ZHANG Ningchi, WANG Yanru, et al. Research on cognitive radio non-orthogonal multiple access system in 5G communications oriented to ubiquitous power Internet of Things[J]. Electric Power, 2021, 54 (5): 35- 45.
27LI X W, ZHANG J Y, HAN C Z, et al. Reliability and security of CR-STAR-RIS-NOMA-assisted IoT networks[J]. IEEE Internet of Things Journal, 2024, 11 (17): 27969- 27980. DOI
28CHEN Y, ZHAO J, HU J T, et al. Distributed task offloading and resource purchasing in NOMA-enabled mobile edge computing: hierarchical game theoretical approaches[J]. ACM Transactions on Embedded Computing Systems, 2024, 23 (1): 1- 28.
29CHEN G J, WU Q Q, CHEN W, et al. IRS-aided wireless powered MEC systems: TDMA or NOMA for computation offloading?[J]. IEEE Transactions on Wireless Communications, 2023, 22 (2): 1201- 1218. DOI
30MOHAJER A, SAM DALIRI M, MIRZAEI A, et al. Heterogeneous computational resource allocation for NOMA: toward green mobile edge-computing systems[J]. IEEE Transactions on Services Computing, 2023, 16 (2): 1225- 1238. DOI
31LIU P, MA K, YANG J, et al. Optimization of relay power and load control period based on cost-sharing contract in smart grid communications[J]. IEEE Internet of Things Journal, 2021, 8 (22): 16559- 16570. DOI
32CHUNG H M, MAHARJAN S, ZHANG Y, et al. Optimal energy trading with demand responses in cloud computing enabled virtual power plant in smart grids[J]. IEEE Transactions on Cloud Computing, 2022, 10 (1): 17- 30. DOI
33LIU P, WANG J X, MA K, et al. Joint cooperative computation and communication for demand-side NOMA-MEC systems with relay assistance in smart grid communications[J]. IEEE Internet of Things Journal, 2024, 11 (19): 30594- 30606. DOI
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