Adaptive Multi-Parameter-Tuning for Online Stabilization Control of Grid-Tied VSC: An Artificial Neural Network-Based Method

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

Voltage Source Converter (VSC) for grid integration of renewable energies are prone to have small-signal stability issues when connected to weak AC grids. Such stability issues largely arise from the lack of VSC control adaptivity to the varying grid condition (e.g., grid impedance). To address this issue, this letter presents an adaptive multi-parameter tuning method using the Artificial Neural Network. Innovative aspect of the proposal lies in that it enables the VSC to simultaneously tune multiple controller parameters online, which brings about a pole-tracking-based stabilization control feature for the VSC. Experimental results demonstrate that the proposed method can effectively and adaptively stabilize the VSC when the grid impedance is varied.
Original languageEnglish
Article number9767572
JournalIEEE Transactions on Power Delivery
Volume37
Issue number4
Pages (from-to)3428-3431
ISSN1937-4208
DOIs
Publication statusPublished - 1 Aug 2022

Keywords

  • Adaptive parameter tuning
  • Phase locked loops
  • Impedance
  • Optimized production technology
  • Power system stability
  • Circuit stability
  • Stability criteria
  • Artificial neural network

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