ANFIS based neuro-fuzzy control of dfig for wind power generation in standalone mode

Ifte K. Amin, M. Nasir Uddin, Marayati Marsadek

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

This paper presents an adaptive neuro-fuzzy controller (NFC)for doubly fed induction generator (DFIG)based wind energy conversion system (WECS)to operate under standalone mode. The NFC is developed based on adaptive-network-based fuzzy inference system (ANFIS)architecture since it has the unique advantage of fast convergence combining the robustness of fuzzy logic and flexibility of neural network algorithm. For the isolated operation of DFIG-WECS, ANFIS is designed for load side converter (LSC)control. The proposed scheme demonstrates improved dynamic performance under variable wind speed and load conditions by maintaining stable output voltage. The supply frequency to the load remains stable by virtue of precise control of LSC while turbine rotation varies with fluctuating wind speed. The flux alignment is ensured by the proportional-integral (PI)control of rotor side converter. The simulation results exhibit the controller's outstanding performance through its robust control over load-voltage and supply frequency under the variation of demand load power and wind speed.

Original languageEnglish
Title of host publication2019 IEEE International Electric Machines and Drives Conference, IEMDC 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2077-2082
Number of pages6
ISBN (Electronic)9781538693490
DOIs
Publication statusPublished - 01 May 2019
Event11th IEEE International Electric Machines and Drives Conference, IEMDC 2019 - San Diego, United States
Duration: 12 May 201915 May 2019

Publication series

Name2019 IEEE International Electric Machines and Drives Conference, IEMDC 2019

Conference

Conference11th IEEE International Electric Machines and Drives Conference, IEMDC 2019
CountryUnited States
CitySan Diego
Period12/05/1915/05/19

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All Science Journal Classification (ASJC) codes

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering
  • Mechanical Engineering

Cite this

Amin, I. K., Nasir Uddin, M., & Marsadek, M. (2019). ANFIS based neuro-fuzzy control of dfig for wind power generation in standalone mode. In 2019 IEEE International Electric Machines and Drives Conference, IEMDC 2019 (pp. 2077-2082). [8785334] (2019 IEEE International Electric Machines and Drives Conference, IEMDC 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IEMDC.2019.8785334