Connotation Analysis of Leverage Measurement and Its Identification Method Based on Improved Generalized Potential Indicator

Youzhi LIU; Hui ZI; Jian XIAO; Xi GAO; Chunqi YANG; Jikeng LIN

doi:10.7500/AEPS20200924001

您当前的位置：

首页 >

文章列表页 >

Connotation Analysis of Leverage Measurement and Its Identification Method Based on Improved Generalized Potential Indicator

Basic Research | 更新时间：2025-06-16

- Connotation Analysis of Leverage Measurement and Its Identification Method Based on Improved Generalized Potential Indicator
- Automation of Electric Power Systems Vol. 45, Issue 12, Pages: 92-100(2021)
- 作者机构：
  
  1.广东电网有限责任公司广州供电局电力调度控制中心，广东省广州市 510620
  2.同济大学电子与信息工程学院，上海市 201804
- 作者简介：
- 基金信息：
- DOI：10.7500/AEPS20200924001
  CLC：
- Received：24 September 2020，
  
  Revised：2021-01-24，
  
  Published Online：23 April 2021，
  
  Published：25 June 2021
- 稿件说明：
移动端阅览
刘有志,资慧,肖健等.杠杆量测内涵分析及其改进广义潜能指标辨识方法[J].电力系统自动化,2021,45(12):92-100.

LIU Youzhi,ZI Hui,XIAO Jian,et al.Connotation Analysis of Leverage Measurement and Its Identification Method Based on Improved Generalized Potential Indicator[J].Automation of Electric Power Systems,2021,45(12):92-100.
刘有志,资慧,肖健等.杠杆量测内涵分析及其改进广义潜能指标辨识方法[J].电力系统自动化,2021,45(12):92-100. DOI： 10.7500/AEPS20200924001.

LIU Youzhi,ZI Hui,XIAO Jian,et al.Connotation Analysis of Leverage Measurement and Its Identification Method Based on Improved Generalized Potential Indicator[J].Automation of Electric Power Systems,2021,45(12):92-100. DOI： 10.7500/AEPS20200924001.

摘要

杠杆量测的准确辨识多年来一直是状态估计精度提升的瓶颈。文中针对杠杆量测这一重要的量测类型进行了深入分析和研究。首先，分析了2个关于杠杆量测定义的内涵一致性；进而，分别从代数和几何角度对杠杆量测的特性进行了分析，并以命题形式证明了无限靠近雅可比矩阵列空间的量测只能是杠杆量测；在此基础上，提出了基于潮流解及改进广义潜能指标的杠杆量测辨识新方法。相对于其他方法而言，该方法能够明显提升多个杠杆量测的正确辨识率。算例结果验证了所提方法的可行性和正确性。

Abstract

The accurate identification of leverage measurement (LM) has been the bottleneck of precision improvement of state estimation for many years. This paper deeply analyzes and explores the relevant issues about the important measurement type of LM. Firstly

the connotation consistency of the two definitions on LM is analyzed. Secondly

the characteristics of LM are explored from both algebraic and geometric aspects. The proposition that a measurement infinitely closing to the column space of Jacobi matrix indeed is LM is strictly proven. On this basis

this paper proposes a new identification method of LM using the power flow solution and the improved generalized potential indicator. Compared with other methods

the proposed method can significantly improve the correct identification rate of multiple LMs. The example results verify the feasibility and validity of the proposed method.

关键词

Keywords

references

于尔铿 . 电力系统状态估计［M］. 北京：水利电力出版社， 1985 .

YU Erkeng . Power system state estimation ［M］. Beijing ： Hydraulic and Electric Power Press ， 1985 .

ABUR A ， GOMEZ-EXPOSITO A . Power system state estimation： theory and implementation ［M］. New York ， USA： Marcel Dekker ， 2004 .

COUTTO FILHO M B D ， STACCHINI DE SOUZA J C ， RIBEIRO GUIMARAENS M A . Enhanced bad data processing by phasor-aided state estimation ［J］. IEEE Transactions on Power Systems ， 2014 ， 29 （ 5 ）： 2200 - 2209 .

CLEMENTS K A ， DAVIS P W . Multiple bad data detectability and identifiability： a geometric approach ［J］. IEEE Transactions on Power Delivery ， 1986 ， 1 （ 3 ）： 355 - 360 .

LIN Yuzhang ， ABUR A . A new framework for detection and identification of network parameter errors ［J］. IEEE Transactions on Smart Grid ， 2018 ， 9 （ 3 ）： 1698 - 1706 .

MILI L ， CHENIAE M G ， ROUSSEEUW P J . Robust state estimation of electric power systems ［J］. IEEE Transactions on Circuits and Systems Ⅰ： Fundamental Theory and Applications ， 1994 ， 41 （ 5 ）： 349 - 358 .

ROUSSEEUW P J ， LEROY A M . Robust regression and outlier detection ［M］. Hoboken， USA ： John Wiley&Sons ， 2005 .

MONTICELLI A ， WU F F ， YEN M . Mutiple bad data identification for state estimation by combinatorial optimization ［J］. IEEE Transactions on Power Delivery ， 1986 ， 1 （ 3 ）： 361 - 369 .

ROUSSEEUW P J ， DRIESSEN K V . A fast algorithm for the minimum covariance determinant estimator ［J］. Technometrics ， 1999 ， 41 （ 3 ）： 212 - 223 .

MILI L ， CHENIAE M G ， VICHARE N S ， et al . Robust state estimation based on projection statistics of power systems ［J］. IEEE Transactions on Power Systems ， 1996 ， 11 （ 2 ）： 1118 - 1127 .

HOAGLIN D C ， WELSCH R E . The hat matrix in regression and ANOVA ［J］. The American Statistician ， 1978 ， 32 （ 1 ）： 17 - 22 .

VELLEMAN P F ， WELSCH R E . Efficient computing of regression diagnostics ［J］. The American Statistician ， 1981 ， 35 （ 4 ）： 234 - 242 .

BRETAS N G ， LONDON J B A ， ALBERTO L F C ， et al . Geometrical approach on masked gross errors for power systems state estimation ［C］// IEEE Power & Energy Society General Meeting ， July 26 - 30 ， 2009 ， Calgary， Canada： 7p .

HABSHAH M ， NORAZAN M R . RAHMATULLAH IMON A H M. The performance of diagnostic-robust generalized potentials for the identification of multiple high leverage points in linear regression ［J］. Journal of Applied Statistics ， 2009 ， 36 （ 5 ）： 507 - 520 .

MAJUMDAR A ， PAL B C . Bad data detection in the context of leverage point attacks in modern power networks ［J］. IEEE Transactions on Smart Grid ， 2018 ， 9 （ 3 ）： 2042 - 2054 .

ZHAO J ， MILI L . Vulnerability of the largest normalized residual statistical test to leverage points ［J］. IEEE Transactions on Power Systems ， 2018 ， 33 （ 4 ）： 4643 - 4646 .

WU W ， GUO Y ， ZHANG B ， et al . Robust state estimation method based on maximum exponential square ［J］. IET Generation ， Transmission & Distribution ， 2011 ， 5 （ 11 ）： 1165 - 1172 .

MILI L ， PHANIRAJ V ， ROUSSEEUW P J . Least median of squares estimation in power systems ［J］. IEEE Transactions on Power Systems ， 1991 ， 6 （ 2 ）： 511 - 523 .

管晓宏，赵千川，贾庆山，等 . 信息物理融合能源系统［M］. 北京：科学出版社， 2016 .

GUAN Xiaohong ， ZHAO Qianchuan ， JIA Qingshan ， et al . Information and physical fusion energy system ［M］. Beijing ： Science Press ， 2016 .

TAN S ， SONG W Z ， STEWART M ， et al . LPAttack： leverage point attacks against state estimation in smart grid ［C］// IEEE Global Communications Conference （GLOBECOM）， December 8 - 12 ， 2014 ， Austin， USA： 643 - 648 .

COOK R D ， WEISBERG S . Characterizations of an empirical influence function for detecting influential cases in regression ［J］. Technometrics ， 1980 ， 22 （ 4 ）： 495 - 508 .

HADI A S . A new measure of overall potential influence in linear regression ［J］. Computational Statistics & Data Analysis ， 1992 ， 14 （ 1 ）： 1 - 27 .

IMON A . Identifying multiple high leverage points in linear regression ［J］. Journal of Statistical Studies ， 2002 ， 3 ： 207 - 218 .

CHEN Yanbo ， MA Jin ， ZHANG Pu ， et al . Robust state estimator based on maximum exponential absolute value ［J］. IEEE Transactions on Smart Grid ， 2017 ， 8 （ 4 ）： 1537 - 1544 .

HE Guangyu ， DONG Shufeng ， QI Junjian ， et al . Robust state estimator based on maximum normal measurement rate ［J］. IEEE Transactions on Power Systems ， 2011 ， 26 （ 4 ）： 2058 - 2065 .

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Distribution Network Restoration Decision Considering Risk of State Estimation Error in Restoration Process

Time-varying Virtual Inertia and State Estimation of Grid-following Converter Based on Maximum Correntropy Criterion and Polynomial Chaos Kalman Filter

Related Author

ZHU Kaiyu

LIN Jikeng

HAO Lili

KAN Yizhou

XUE Yusheng

XUE Feng

WANG Yuhong

WANG Xueke

Related Institution

College of Electronics and Information Engineering, Tongji University

College of Electrical Engineering & Control Science, Nanjing Tech University

State Grid Electric Power Research Institute (NARI Group Corporation)

School of Electrical Engineering, Sichuan University

State Grid Urumqi Power Supply Company

⁰