A Comprehensive Framework for Robust AC/DC Grid State Estimation Against Measurement and Control Input Errors

Zhi Fang, Yuzhang Lin, Shaojian Song, Chi Li, Xiaofeng Lin, Fei Wang, Yimin Lu

Research output: Contribution to journalArticlepeer-review

Abstract

Thispaper proposes a systematic framework of the AC/DC grid state estimation with high accuracy, computational tractability, and robustness against measurement and control input errors. First, tractable lossy models of bidirectional isolated DC/DC voltage source converters (VSCs), bidirectional DC/AC VSCs, and DC lines for state estimation are developed. Then, the state variables of the DC grid are selected, and measurement equations are derived. Finally, combined with the state estimation model of AC grids, a general framework for the robust AC/DC transmission grid state estimation against both measurement errors and control input errors is presented. Simulation results show that the proposed framework can effectively capture the operating state of the AC/DC grid, and suppress the impact of simultaneous measurement errors and control input errors.

Original languageEnglish (US)
Pages (from-to)1067-1077
Number of pages11
JournalIEEE Transactions on Power Systems
Volume37
Issue number2
DOIs
StatePublished - Mar 1 2022

Keywords

  • AC/DC grid
  • robustness
  • state estimation
  • voltage source converters

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

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