Artificial Neural Network Based Identification of Multi-Operating-Point Impedance Model

Mengfan Zhang, Xiongfei Wang (Corresponding author), Dongsheng Yang, Mads Græsbøll Christensen

Research output: Contribution to journalArticleAcademicpeer-review

3 Citations (Scopus)

Abstract

The black-box impedance model of voltage source inverters (VSIs) can be measured at their terminals without access to internal control details, which greatly facilitate the analysis of inverter-grid interactions. However, the impedance model of VSI is dependent on its operating point and can have different profiles when the operating point is changed. This letter proposes a method for identifying the impedance model of VSI under a wide range of operating points. The approach is based on the artificial neural network (ANN), where a general framework for applying the ANN to identify the VSI impedance is established. The effectiveness of the ANN-based method is validated with the analytical impedance models.
Original languageEnglish
Article number9151366
Pages (from-to)1231-1235
Number of pages5
JournalIEEE Transactions on Power Electronics
Volume36
Issue number2
DOIs
Publication statusPublished - Feb 2021

Keywords

  • Artificial neural networks
  • impedance measurement
  • multiple operating points
  • voltage source inverter

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