Using Branch Current Measurements for Parameter Identification in Extended Kalman Filter based Distribution System State Estimation

Dragan Cetenovic, Aleksandar Rankovic, Junbo Zhao, Vladimir Terzija, Can Huang

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

Abstract

Driven by increased penetration from distributed generation, distribution networks require improved operational state awareness tools in the presence of low measurement redundancy. This can be achieved by utilizing Kalman filter based state estimation in case process noise covariance matrix is optimally assessed. This paper aims to investigate the possibility of using readily available conventional branch current flow measurements to assess process noise covariance matrix in extended Kalman filter (EKF) based state estimation for distribution networks. The process noise covariance matrix has a significant impact on EKF's performance. Recently, a method for optimizing the process noise covariance matrix is proposed leveraging the correlation between the estimation error and the cost function via the innovations of branch power flow measurements. This paper extends that to include the innovations of branch current flow measurements in the cost function. Performances of the proposed approach are evaluated on the modified IEEE 13- and IEEE 37-bus distribution test systems. It is demonstrated that the proposed method is robust to different loading conditions and different measurement configurations. Comparison results with the weighted least square estimator show that our method achieves significantly improved estimation accuracy.

Original languageEnglish
Title of host publication2021 IEEE Power and Energy Society General Meeting, PESGM 2021
PublisherIEEE Computer Society
ISBN (Electronic)9781665405072
DOIs
Publication statusPublished - 2021
Event2021 IEEE Power and Energy Society General Meeting, PESGM 2021 - Washington, United States
Duration: 26 Jul 202129 Jul 2021

Publication series

NameIEEE Power and Energy Society General Meeting
Volume2021-July
ISSN (Print)1944-9925
ISSN (Electronic)1944-9933

Conference

Conference2021 IEEE Power and Energy Society General Meeting, PESGM 2021
Country/TerritoryUnited States
CityWashington
Period26/07/2129/07/21

Keywords

  • branch current flow
  • distribution network
  • extended Kalman filter
  • forecasting-aided state estimation
  • measurement innovations

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