Modeling, Control, and Experimental Verification of a 500 kW DFIG Wind Turbine

Aykut O., Ulu C., Kömürgöz Kırış G.

ADVANCES IN ELECTRICAL AND COMPUTER ENGINEERING, vol.22, no.1, pp.13-20, 2022 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 22 Issue: 1
  • Publication Date: 2022
  • Doi Number: 10.4316/aece.2022.01002
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Aerospace Database, Communication Abstracts, INSPEC, Metadex, Directory of Open Access Journals
  • Page Numbers: pp.13-20
  • Keywords: doubly fed induction generator, modeling control, renewable energy source, wind energy, FED INDUCTION GENERATOR, POWER-CONTROL, FAULT RIDE, CAPABILITY, DESIGN, SYSTEM
  • Yıldız Technical University Affiliated: Yes


In wind turbine applications, an accurate turbine model and effective control algorithms are needed to ensure power flow in accordance with grid standards and design criteria. However, in many studies, only model simulation results are given or the derived models are validated by using only small-scale prototypes. This article presents the modeling, control, and experimental verification of a 500kW doubly fed induction generator (DFIG) wind turbine. The entire model is considered to be a collection of subsystems that are individually modeled and then put together to obtain the whole wind turbine model. The model includes a DFIG, a back-to-back converter, and a control system. In the control system, control of the back-to-back converter, the blade angle control and the maximum power point tracking control are performed to provide effective energy conversion performances for different operation conditions. To validate the derived DFIG turbine model, the results of three experimental tests obtained from a 500kW DFIG wind turbine prototype are used. These test results include both subsynchronous and super synchronous operation conditions. The test results are compared to simulation results obtained by using the derived turbine model. The accuracy of the model is validated by the comparison results.