Synchronous Measurement Data-driven Classification Method for Disturbance Sources in Distribution Networks

CHEN Zhilin; LIU Hao; BI Tianshu

doi:10.7500/AEPS20250110002

您当前的位置：

首页 >

文章列表页 >

Synchronous Measurement Data-driven Classification Method for Disturbance Sources in Distribution Networks

Basic Research | 更新时间：2025-09-25

- Synchronous Measurement Data-driven Classification Method for Disturbance Sources in Distribution Networks
- Automation of Electric Power Systems Vol. 49, Issue 18, Pages: 127-135(2025)
- 作者机构：
  
  新能源电力系统国家重点实验室（华北电力大学），北京市 102206
- 作者简介：
- 基金信息：
  
  National Natural Science Foundation of China(52377098)
- DOI：10.7500/AEPS20250110002
  CLC：
- Received：10 January 2025，
  
  Revised：2025-04-16，
  
  Published Online：08 August 2025，
  
  Published：25 September 2025
- 稿件说明：
移动端阅览
陈徵粼,刘灏,毕天姝.同步测量数据驱动的配电网扰动源分类方法[J].电力系统自动化,2025,49(18):127-135.

CHEN Zhilin,LIU Hao,BI Tianshu.Synchronous Measurement Data-driven Classification Method for Disturbance Sources in Distribution Networks[J].Automation of Electric Power Systems,2025,49(18):127-135.
陈徵粼,刘灏,毕天姝.同步测量数据驱动的配电网扰动源分类方法[J].电力系统自动化,2025,49(18):127-135. DOI： 10.7500/AEPS20250110002.

CHEN Zhilin,LIU Hao,BI Tianshu.Synchronous Measurement Data-driven Classification Method for Disturbance Sources in Distribution Networks[J].Automation of Electric Power Systems,2025,49(18):127-135. DOI： 10.7500/AEPS20250110002.

摘要

为应对大量分布式电源接入带来的挑战，同步测量技术被引入配电网，为系统的安全稳定性分析提供了更多维度的数据。为进一步增强对配电网的态势感知，文中提出了一种同步测量数据驱动的配电网扰动源分类方法。首先，提出了一种基于Granger因果分析理论的扰动源快速辨识方法，分辨扰动源位于主网侧还是配网侧。其后，提出了一种基于核支持向量机的算法误判扰动辨识方法，识别由瞬时估计算法误差引起的误判扰动，从而完成对实时配电网扰动数据的快速分类与提取。最后，基于IEEE 123节点系统仿真数据与现场同步测量数据验证了所提方法的有效性。

Abstract

To address the challenges brought by the integration of a large number of distributed generators

the synchronous measurement technology has been introduced into the distribution network to provide more-dimensional data for the safety and stability analysis of the system. To further enhance the situational awareness of the distribution network

a synchronous measurement data-driven classification method for disturbance sources in the distribution network is proposed in this paper. Firstly

a fast identification method for disturbance sources based on Granger causality analysis theory is proposed to identify if the disturbance source is from the main grid side or the distribution network side. Subsequently

a misjudged disturbance identification method based on kernel support vector machine algorithm is proposed to identify misjudged disturbances caused by errors in instantaneous estimation algorithms

thus achieving the rapid classification and extraction of real-time distribution network disturbance data. Finally

the effectiveness of the proposed method is verified based on IEEE 123-bus system simulation data and on-site synchronous measurement data.

关键词

Keywords

references

王伟胜，林伟芳，何国庆，等 . 美国得州2021年大停电事故对我国新能源发展的启示［J］. 中国电机工程学报， 2021 ， 41 （ 12 ）： 4033 - 4043 .

WANG Weisheng ， LIN Weifang ， HE Guoqing ， et al . Enlightenment of 2021 Texas blackout to the renewable energy development in China ［J］. Proceedings of the CSEE ， 2021 ， 41 （ 12 ）： 4033 - 4043 .

钟剑，陈晨，张昊辰，等 . 极端天气下配电网信息物理耦合故障快速恢复策略［J/OL］. 电力系统自动化： 1 - 23 ［ 2025-04-16 ］. https：//link.cnki.net/urlid/32.1180.tp.20241008.1649.004 https://link.cnki.net/urlid/32.1180.tp.20241008.1649.004 .

ZHONG Jian ， CHEN Chen ， ZHANG Haochen ， et al ． Rapid restoration strategy for cyber-physical integrated failures in distribution systems under extreme weather conditions ［J/OL］. Automation of Electric Power Systems ： 1 - 23 ［ 2025-04-16 ］. https：//link.cnki.net/urlid/32.1180.tp.20241008.1649.004 https://link.cnki.net/urlid/32.1180.tp.20241008.1649.004 .

DUAN N ， STEWART E M . Frequency event categorization in power distribution systems using micro PMU measurements ［J］. IEEE Transactions on Smart Grid ， 2020 ， 11 （ 4 ）： 3043 - 3053 .

ARANA A ， BANK J ， GARDNER R ， et al . Estimating speed of frequency disturbance propagation through transmission and distribution systems ［C］// 2006 IEEE PES Power Systems Conference and Exposition ， October 29-November 1 ， 2006 ， Atlanta， USA ： 1286 - 1290 .

王宾，孙华东，张道农 . 配电网信息共享与同步相量测量应用技术评述［J］. 中国电机工程学报， 2015 ， 35 （增刊1 ）： 1 - 7 .

WANG Bin ， SUN Huadong ， ZHANG Daonong . Review on application technology of information sharing and synchronous phasor measurement in distribution network ［J］. Proceedings of the CSEE ， 2015 ， 35 （ S1 ）： 1 - 7 .

VON MEIER A ， STEWART E ， MCEACHERN A ， et al . Precision micro-synchrophasors for distribution systems： a summary of applications ［J］. IEEE Transactions on Smart Grid ， 2017 ， 8 （ 6 ）： 2926 - 2936 .

LIU H ， BI T S ， XU S D ， et al . A full-view synchronized measurement system for the renewables， controls， loads， and waveforms of power-electronics-enabled power distribution grids ［J］. IEEE Transactions on Smart Grid ， 2022 ， 13 （ 5 ）： 3879 - 3890 .

张琳，任双雪，惠子珈，等 . 实现配电网PMU频率测量的数字微分器研究［J］. 中国电机工程学报， 2021 ， 41 （ 22 ）： 7640 - 7648 .

ZHANG Lin ， REN Shuangxue ， HUI Zijia ， et al . Design of digital differentiator for frequency measurement in distribution grid PMU ［J］. Proceedings of the CSEE ， 2021 ， 41 （ 22 ）： 7640 - 7648 .

SHAHSAVARI A ， FARAJOLLAHI M ， STEWART E M ， et al . Situational awareness in distribution grid using micro-PMU data： a machine learning approach ［J］. IEEE Transactions on Smart Grid ， 2019 ， 10 （ 6 ）： 6167 - 6177 .

APPASANI B ， JHA A V ， MISHRA S K ， et al . Communication infrastructure for situational awareness enhancement in WAMS with optimal PMU placement ［J］. Protection and Control of Modern Power Systems ， 2021 ， 6 （ 1 ）： 9 .

SEYEDI Y ， KARIMI H ， GRIJALVA S . Irregularity detection in output power of distributed energy resources using PMU data analytics in smart grids ［J］. IEEE Transactions on Industrial Informatics ， 2018 ， 15 （ 4 ）： 2222 - 2232 .

SHAHSAVARI A ， FARAJOLLAHI M ， STEWART E ， et al . A data-driven analysis of capacitor bank operation at a distribution feeder using micro-PMU data ［C］// 2017 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference （ISGT）， April 23-26 ， 2017 ， Washington， USA ： 1 - 5 .

AKRAMI A ， ASIF M S ， MOHSENIAN-RAD H . Sparse distribution system state estimation： an approximate solution against low observability ［C］// 2020 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference （ISGT）， February 17-20 ， 2020 ， Washington， USA .

SHAHSAVARI A ， FARAJOLLAHI M ， STEWART E ， et al . A machine learning approach to event analysis in distribution feeders using distribution synchrophasors ［C］// 2019 International Conference on Smart Grid Synchronized Measurements and Analytics （SGSMA）， May 21-23 ， 2019 ， College Station， USA ： 1 - 7 .

FARAJOLLAHI M . Locating the source of events in power distribution systems using micro-PMU data ［J］. IEEE Transactions on Power Systems ， 2018 ， 33 （ 6 ）： 6343 - 6354 ．

ZHOU X ， WANG Y H ， SHI Y X ， et al . Deep reinforcement learning-based optimal PMU placement considering the degree of power system observability ［J］. IEEE Transactions on Industrial Informatics ， 2024 ， 20 （ 6 ）： 8949 - 8960 .

CHEN G ， LI Z Y ， ZHAO Z Y . Event-triggered optimal active power control in islanded microgrid with variable demand and time-varying communication topology ［J］. IEEE Transactions on Smart Grid ， 2019 ， 10 （ 4 ）： 4015 - 4025 .

冯双，杨浩，崔昊，等 . 基于Copula传递熵的设备级和网络级宽频振荡传播路径分析及振荡源定位方法［J］. 电工技术学报， 2024 ， 39 （ 16 ）： 4996 - 5010 .

FENG Shuang ， YANG Hao ， CUI Hao ， et al . Propagation path analysis and oscillation source location method of device-level and network-level broadband oscillation based on Copula transfer entropy ［J］. China Industrial Economics ， 2024 ， 39 （ 16 ）： 4996 - 5010 .

穆钢，陈奇，刘洪波，等 . 揭示电力系统运行数据中因果关系的逆信息熵因果推理方法［J］. 中国电机工程学报， 2022 ， 42 （ 15 ）： 5406 - 5417 ．

MU Gang ， CHEN Qi ， LIU Hongbo ， et al . Power system disturbance detection method considering PMU data quality problems ［J］. Proceedings of the CSEE ， 2022 ， 42 （ 15 ）： 5406 - 5417 .

JIANG H G ， DAI X X ， GAO D W ， et al . Spatial-temporal synchrophasor data characterization and analytics in smart grid fault detection， identification， and impact causal analysis ［J］. IEEE Transactions on Smart Grid ， 2016 ， 7 （ 5 ）： 2525 - 2536 .

CHO S H ， JANG G ， KWON S H . Time-frequency analysis of power-quality disturbances via the Gabor-Wigner transform ［J］. IEEE Transactions on Power Delivery ， 2010 ， 25 （ 1 ）： 494 - 499 .

CHASSIN D P ， SCHNEIDER K ， GERKENSMEYER C ． GridLAB-D：an open-source power systems modeling and simulation environment ［C］// Proceedings of the 2008 Power & Energy Society Transmission and Distribution Conference and Exposition ， April 21-24 ， 2008 ， Chicago， USA ： 1 - 5 ．

BAXTER M ， KING R G . Measuring business cycles：approximate band pass filters economic time series ［J］. Review of Economics and Statistics ， 1999 ， 81 （ 4 ）： 575 - 593 ．

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Anti-islanding Protection Method Based on Magnitude Ratio of Inspection Signal to Power Frequency Voltage

Online Reactive Power Optimization Method Based on Data-driven Predictive Control for Distribution Network with Low Situation Awareness

Optimal Control of Power Self-balancing for Distribution Network Based on Decentralized Complex Adaptive System of Systems

Voltage Regulation Strategy for Distribution Network Considering Optimal Adjustment of Automatic Voltage Control System Limits

Related Author

XU Huabo

CHEN Yu

XU Bingyin

ZHAO Ruifeng

LIU Yiming

WANG Pengwei

QIAN Liqun

WEI Qing

Related Institution

School of Electrical and Electronic Engineering, Shandong University of Technology

Electric Power Dispatch and Control Center, Guangdong Power Grid Co., Ltd.

School of Intelligent Manufacturing, Zibo Vocational Institute

School of Electrical Engineering, Zhejiang University

HuaDian Electric Research Institute Co., Ltd.

⁰