Kalman Filter Approach for Line Parameter Estimation for Long Transmission Lines

Yiqi Zhang, Yuan Liao

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

4 Scopus citations

Abstract

Transmission line parameters including series resistance, series reactance, and shunt susceptance are essential inputs to a variety of power system applications. The purpose of the study is to develop new methods to estimate line parameters for long transmission lines with different configurations under the effect of measurement noises by utilizing the Kalman filter techniques. Simulations are performed to demonstrate the effectiveness of the proposed methods. Results evince promising applications of the proposed new method.

Original languageEnglish
Title of host publication2020 IEEE Power and Energy Conference at Illinois, PECI 2020
ISBN (Electronic)9781728152998
DOIs
StatePublished - Feb 2020
Event2020 IEEE Power and Energy Conference at Illinois, PECI 2020 - Champaign, United States
Duration: Feb 27 2020Feb 28 2020

Publication series

Name2020 IEEE Power and Energy Conference at Illinois, PECI 2020

Conference

Conference2020 IEEE Power and Energy Conference at Illinois, PECI 2020
Country/TerritoryUnited States
CityChampaign
Period2/27/202/28/20

Bibliographical note

Publisher Copyright:
© 2020 IEEE.

Keywords

  • Kalman filter
  • PMU
  • noise
  • parameter estimation
  • transmission line

ASJC Scopus subject areas

  • Renewable Energy, Sustainability and the Environment
  • Electrical and Electronic Engineering
  • Control and Optimization
  • Hardware and Architecture
  • Information Systems and Management
  • Energy Engineering and Power Technology

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