PI parameter tuning of converters for sub-synchronous interactions existing in grid-connected DFIG wind turbines

Aikang Chen, Da Xie, Daming Zhang, Chenghong Gu, Keyou Wang

Research output: Contribution to journalArticle

4 Citations (Scopus)
16 Downloads (Pure)

Abstract

As a clean energy, wind power has been extensively exploited in the past few years. However, oscillations in wind turbines, particularly those from controllers, could severely affect the stability of power systems. Therefore, oscillation suppression is a recent research focus. Based on the small-signal model eigenvalues and participation factors, this paper detects the sub-synchronous interactions (SSI) mainly determined by converters' PI parameters in a grid-connected doubly fed induction generator (DFIG). With the aim of oscillation restraint, a novel optimization model with the reference-point based non-dominated sorting genetic algorithm (NSGA-III) and the t-distributed stochastic neighbour embedding (t-SNE) is developed to explore and visualize optimal ranges of PI parameters, facilitating the selection of the appropriate PI parameters to augment the damping. Additionally, to study the adaptability of the optimal PI parameters, interactions performance of the system that uses optimal parameters is studied with different output levels of the wind turbine. Finally, a time domain simulation and a practical experiment are conducted to demonstrate the effectiveness of the proposed approach. Results illustrate that the SSI of a grid-connected DFIG is suppressed by the optimization model. This study is highly beneficial to power system operators in integrating wind power and maintaining system stability.

Original languageEnglish
Article number8488561
Pages (from-to)6345-6355
Number of pages11
JournalIEEE Transactions on Power Electronics
Volume34
Issue number7
Early online date10 Oct 2018
DOIs
Publication statusPublished - 31 Jul 2019

Keywords

  • Converters
  • optimization methods
  • power system stability
  • wind power generation

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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