Power System Dynamic State Estimation: Motivations, Definitions, Methodologies, and Future Work

Junbo Zhao, Antonio Gómez-Expósito, Marcos Netto, Lamine Mili, Ali Abur, Vladimir Terzija, Innocent Kamwa, Bikash Pal, Abhinav Kumar Singh, Junjian Qi, Zhenyu Huang, A. P.Sakis Meliopoulos

Research output: Contribution to journalArticlepeer-review

223 Citations (Scopus)

Abstract

This paper summarizes the technical activities of the Task Force on Power System Dynamic State and Parameter Estimation. This Task Force was established by the IEEE Working Group on State Estimation Algorithms to investigate the added benefits of dynamic state and parameter estimation for the enhancement of the reliability, security, and resilience of electric power systems. The motivations and engineering values of dynamic state estimation (DSE) are discussed in detail. Then, a set of potential applications that will rely on DSE is presented and discussed. Furthermore, a unified framework is proposed to clarify the important concepts related to DSE, forecasting-aided state estimation, tracking state estimation, and static state estimation. An overview of the current progress in DSE and dynamic parameter estimation is provided. The paper also provides future research needs and directions for the power engineering community.

Original languageEnglish
Article number8624411
Pages (from-to)3188-3198
Number of pages11
JournalIEEE Transactions on Power Systems
Volume34
Issue number4
DOIs
Publication statusPublished - Jul 2019
Externally publishedYes

Keywords

  • bad data
  • Dynamic state estimation (DSE)
  • forecasting-aided state estimation (FASE)
  • Kalman filtering
  • parameter estimation
  • power system dynamics
  • power system protection
  • power system stability and control
  • robust estimation
  • static state estimation (SSE)
  • synchrophasor measurements
  • tracking state estimation (TSE)

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