智能配电网不平衡问题的主动定位与调控恢复

李一泓; 潘宜城; 马萌; 王平

doi:10.11959/j.issn.2096-3750.2025.00482

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智能配电网不平衡问题的主动定位与调控恢复

能源物联网 | 更新时间：2025-07-29

- 智能配电网不平衡问题的主动定位与调控恢复
- Active location and recovery of unbalance problems in smart distribution networks
- 物联网学报 2025年9卷第2期页码：70-81
- 作者机构：
  
  1.北京大学软件与微电子学院，北京 102600
  2.北京大学计算机学院，北京 100871
  3.北京大学软件工程国家工程研究中心，北京 100871
  4.高可信软件技术教育部重点实验室（北京大学），北京 100871
- 作者简介：
  
  [ "李一泓（1999‒ ），男，北京大学软件与微电子学院硕士生，主要研究方向为微服务、配电网等复杂网络系统中的故障模拟和数据驱动的异常诊断方法等。" ]
  [ "潘宜城（1997‒ ），男，北京大学计算机学院博士生，主要研究方向为网络服务系统故障分析诊断、复杂系统动态因果分析等。" ]
  [ "马萌（1986‒ ），男，北京大学副研究员，主要研究方向为态势表征计算、网络服务系统故障分析诊断、智能交通系统分析等。" ]
  [ "王平（1961‒ ），男，北京大学教授，主要研究方向为信息安全与隐私保护、智能计算与感知、大数据计算与人工智能。" ]
- 基金信息：
  
  国家自然科学基金资助项目(92167104;62072006);启元实验室创新基金资助项目(S20210201079);智能平行技术国家级重点实验室基金资助项目(2024JK15)
- DOI：10.11959/j.issn.2096-3750.2025.00482
  中图分类号： TM76
- 收稿日期：2024-12-31，
  
  修回日期：2025-02-23，
  
  纸质出版日期：2025-06-10
- 稿件说明：
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李一泓,潘宜城,马萌等.智能配电网不平衡问题的主动定位与调控恢复[J].物联网学报,2025,09(02):70-81.

LI Yihong,PAN Yicheng,MA Meng,et al.Active location and recovery of unbalance problems in smart distribution networks[J].Chinese Journal on Internet of Things,2025,09(02):70-81.
李一泓,潘宜城,马萌等.智能配电网不平衡问题的主动定位与调控恢复[J].物联网学报,2025,09(02):70-81. DOI： 10.11959/j.issn.2096-3750.2025.00482.

LI Yihong,PAN Yicheng,MA Meng,et al.Active location and recovery of unbalance problems in smart distribution networks[J].Chinese Journal on Internet of Things,2025,09(02):70-81. DOI： 10.11959/j.issn.2096-3750.2025.00482.

摘要

在新型电力系统快速发展与高比例分布式能源接入的背景下，配电网三相不平衡问题日益凸显，该问题不仅会带来额外损耗，而且会引发设备损毁、供电中断等安全隐患，严重威胁智能配电网的安全稳定运行。为此，提出了智能配电网不平衡问题的主动定位与调控恢复方法——PowerCause。首次将时间序列因果推断引入配电网异常分析领域，构建了“检测-定位-调控”的全流程解决方案。通过融合格兰杰因果检验与自适应区间检测算法，实现了无须预训练、不依赖物理拓扑的不平衡根因定位；基于OpenDSS搭建的主动调控系统集成了异常仿真、多维度指标采集与调控决策，形成“自感知-自诊断-自恢复”的闭环控制体系。仿真结果表明，该方法在根因定位精度和时间效率等各方面具有竞争力，并且对测量噪声、数据丢失误差等环境影响具有较好的鲁棒性。

Abstract

Under the rapid development of new power systems and the high penetration of distributed energy resources

three-phase unbalance issues in distribution networks have become increasingly prominent. This problem not only causes additional losses

but also triggers equipment damage and power supply interruptions

posing significant threats to the secure and stable operation of smart distribution networks. To this end

a method for active location and control recovery of unbalanced problems in smart distribution networks named PowerCause was proposed. The time-series causal inference was introduced into distribution network anomaly analysis

establishing a comprehensive "detection-localization-regulation" solution framework for the first time. By integrating Granger causality tests with adaptive interval detection algorithms

the method achieves unbalanced root cause localization without requiring pre-training or physical topology dependencies. The active regulation system built on OpenDSS incorporates anomaly simulation

multi-dimensional metric collection

and regulation decision-making

forming a closed-loop control system with self-perception

self-diagnosis

and self-recovery capabilities. Simulation results demonstrate the method's competitive performance in root cause localization accuracy and time efficiency

along with strong robustness against environmental disturbances such as measurement noise and data loss errors.

关键词

Keywords

references

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泛在电力物联网形势下考虑多主体投资的配电网运行优化策略