Distributed optimal operation of integrated energy systems in weak communication environments considering rural energy consumption characteristics

XU Mingjian; LI Binxian; LI Jiayong; ZHOU Ke; ZHANG Cong; ZHU Lipeng

doi:10.19783/j.cnki.pspc.260018

English Version Journal Login

您当前的位置：

首页 >

文章列表页 >

Distributed optimal operation of integrated energy systems in weak communication environments considering rural energy consumption characteristics

更新时间：2026-10-16

- Distributed optimal operation of integrated energy systems in weak communication environments considering rural energy consumption characteristics
- Power System Protection and Control Vol. 54, Issue 17, (2026)
- 作者机构：
  
  湖南大学电气与信息工程学院,湖南,长沙,410082
- 作者简介：
- 基金信息：
- DOI：10.19783/j.cnki.pspc.260018
  CLC：
- Published：2026
- 稿件说明：
移动端阅览
XU Mingjian, LI Binxian, LI Jiayong, et al. Distributed optimal operation of integrated energy systems in weak communication environments considering rural energy consumption characteristics[J]. Power System Protection and Control, 2026, 54(17).
DOI：

XU Mingjian, LI Binxian, LI Jiayong, et al. Distributed optimal operation of integrated energy systems in weak communication environments considering rural energy consumption characteristics[J]. Power System Protection and Control, 2026, 54(17). DOI： 10.19783/j.cnki.pspc.260018.

摘要

针对乡村综合能源系统负荷机理复杂、通信基础设施薄弱及隐私保护需求迫切的挑战，提出一种计及乡村用能特性的弱通信环境下分布式优化运行方法。首先，剖析乡村典型场景物理机理，构建物理驱动的精细化负荷模型与互联微能网协同调度架构。其次，提出融合事件触发机制与混合动量补偿的鲁棒差分隐私交替方向乘子法 (alternating direction method of multipliers

ADMM)，通过事件触发减少数据传输，利用动量外推进行丢包补偿，并引入动态衰减噪声机制平衡隐私安全与求解精度。算例分析表明，所提方法能够有效挖掘区域间的互济潜力，在保障算法收敛精度与隐私安全的同时降低通信开销，实现了弱通信环境下系统的经济高效运行。

Abstract

To address the challenges of complex load characteristics

weak communication infrastructure

and urgent privacy protection requirements in rural integrated energy systems

this paper proposes a distributed optimal operation method under weak communication environments that accounts for rural energy consumption characteristics. First

the physical mechanisms of typical rural scenarios are analyzed to construct physics‑driven refined load models and a cooperative dispatch architecture for interconnected micro‑energy networks. Second

a robust differential privacy alternating direction method of multipliers (ADMM) integrating an event‑triggered mechanism and hybrid momentum compensation is proposed. This method reduces data transmission through event‑triggering

utilizes momentum extrapolation for packet loss compensation

and introduces a dynamic decaying noise mechanism to balance privacy security with solution precision. Case studies demonstrate that the proposed method effectively exploits the mutual assistance potential between regions

reduces communication overhead while ensuring convergence accuracy and privacy security

and achieves economic and efficient system operation under weak communication environments.

关键词

Keywords

references

中共中央, 国务院. 关于全面推进乡村振兴加快农业农村现代化的意见[N]. 人民日报, 2021-02-22(001).

WANG Qiujie, XIAO Yifeng, TAN Hong, et al. Day‑ahead scheduling of rural integrated energy systems based on distributionally robust optimization theory[J]. Applied Thermal Engineering, 2024, 246.

XIA Shiwei, CAI Liuyang, TONG Mingze, et al. Regulation flexibility assessment and optimal aggregation strategy of greenhouse loads in modern agricultural parks[J]. Protection and Control of Modern Power Systems, 2024, 9(3): 98‑111.

ZHOU Xu, MA Zhongjing, ZOU Suli, et al. Distributed energy management of double‑side multienergy systems via sub‑gradient averaging consensus[J]. IEEE Transactions on Smart Grid, 2023, 14(2): 979‑995.

IMRAN M A, ZENNARO M, POPOOLA O R, et al. Exploring the boundaries of connected systems: communications for hard‑to‑reach areas and extreme conditions[J]. Proceedings of the IEEE, 2024, 112(7): 912‑945.

YUAN Y, HE W, DU W, et al. Distributed gradient tracking for differentially private multi‑agent optimization with a dynamic event‑triggered mechanism[J]. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2024, 54(5): 3044‑3055.

WU Y, YU T, PAN Z, et al. Best response learning assisted asynchronous ADMM for real‑time energy sharing under communication delay[J]. IEEE Transactions on Smart Grid, 2025.

LIANG X, LI Z, HUANG W, et al. Relaxed alternating direction method of multipliers for hedging communication packet loss in integrated electrical and heating system[J]. Journal of Modern Power Systems and Clean Energy, 2020, 8(5): 874‑883.

YANG Q, CHEN G, WANG T. ADMM‑based distributed algorithm for economic dispatch in power systems with both packet drops and communication delays[J]. IEEE/CAA Journal of Automatica Sinica, 2020, 7(3): 842‑852.

CAO Y, CHEN Y. A differentially private energy trading mechanism approaching social optimum[J]. IEEE Transactions on Smart Grid, 2026, 17(2): 1444‑1456.

CHEN J, LI K, ZHAO D, et al. Differential privacy‑enabled distributed optimization dispatch algorithm with multi‑channel communication for integrated energy system[J]. IEEE Transactions on Smart Grid, 2026, 17(2): 1081‑1092.

FAN Ke, BAI Hao, ZHANG Song, et al. Optimal operation of rural integrated energy system containing cold, heat, electricity and hydrogen[C] // 2025 IEEE 8th International Electrical and Energy Conference (CIEEC), May 16‑18, 2025, Changsha, China: 3478‑3483.

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Distributed collaborative optimal operation for electricity-hydrogen coupled active distribution networks based on federated ADMM for data privacy protection

Research on a federated learning ADMM-based hierarchical distributed demand response strategy for industrial parks

基于多主体博弈的配电网-多综合能源系统分布式优化调度

光储式5G通信基站集群灵活性聚合与协同调度策略

基于负荷均衡加载的电力系统分布式经济调度策略

Related Author

CHEN Kena

HUANG Xiaoqing

LU Ming

KANG Bing

DENG Fangming

TIAN Yunpeng

CUI Mingjian

GU Liting

Related Institution

CHENG Ying(1. Hubei Engineering Research Center of New Energy Microgrid (China Three Gorges University)

State Grid Changshou Power Supply Company

DOU Qing(1. College of Electrical and Information Engineering, Hunan University

Shanxi Transportation Technology Research & Development Co., Ltd.

AI问答

⁰