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An Estimation Method of Transmission Line Parameters Based on Measurements of Injection Power and Voltage Phasor in Power Grid

  • Xi'an Jiaotong University
  • Tsinghua University
  • Electric Power Research Institute of State Grid Shaanxi Electric Power Company

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Estimation of transmission line parameters is an important problem for state estimation of power grid. In recent years, some studies have shown that the transmission line parameters can be estimated by some specific measurement data of the power grid. However, most of the studies mainly focus on single type of measurement data. In this paper, we propose an estimation method of transmission line parameters based on multi-measurement data of power grid, including measurements of injection power and voltage phasor. And considering the different reliability of the measurements, we make different restrictions on the multi-measurements. In our method, parameters and connection topology of transmission lines are estimated separately, and an ALS optimization model is established to solve the problem. Compared to the previous methods, the objective functions and constraints of our optimization model are improved, with considering different constraints based on phasor measurements, to get better estimation accuracy. The effectiveness and performance of the developed estimation method are demonstrated based on experiments using IEEE 30-bus and 118-bus systems.

Original languageEnglish
Title of host publication2021 IEEE 17th International Conference on Automation Science and Engineering, CASE 2021
PublisherIEEE Computer Society
Pages202-207
Number of pages6
ISBN (Electronic)9781665418737
DOIs
StatePublished - 23 Aug 2021
Event17th IEEE International Conference on Automation Science and Engineering, CASE 2021 - Lyon, France
Duration: 23 Aug 202127 Aug 2021

Publication series

NameIEEE International Conference on Automation Science and Engineering
Volume2021-August
ISSN (Print)2161-8070
ISSN (Electronic)2161-8089

Conference

Conference17th IEEE International Conference on Automation Science and Engineering, CASE 2021
Country/TerritoryFrance
CityLyon
Period23/08/2127/08/21

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