Artikel

Maximum efficiency of wind energy using novel Dynamic Voltage Restorer for DFIG based Wind Turbine

Fault-tolerable capability of Doubly Fed Induction Generator (DFIG) against disturbance occurrence is recognized as Fault Ride-Through (FRT). With quick and accurate compensation potentiality of Dynamic Voltage Restorer (DVR) to retrieve the nominal PCC voltage, DFIG can safely follow its normal operation in the power system. Multi-Level Inverter (MLI) as the main part of DVR with unique responsibility of synthesizing the staircase sinusoidal voltage ascertains the performance and flexibility of DVR. In this paper a novel asymmetrical MLI structure based on Level Creator and H-bridge inverter is indwelt in DVR in order to providing the high quality voltage. To more augment the efficiency of DVR in dealing with FRT issue, it has been equipped with Brain Emotional Learning Based Intelligent Controller (BELBIC) based on Multi Objective Bees Algorithm (MOBA). So-called AMLI-BELBIC based DVR has been thoroughly appraised under different balanced and unbalanced voltage sags and swells so that FRT capability of DFIG to be appeared. To sum up, the relevant analytical expression along with the simulation results has transparently corroborated the performance of AMLI-BELBIC based DVR aimed to augment the FRT capability of DFIG.

Language
Englisch

Bibliographic citation
Journal: Energy Reports ; ISSN: 2352-4847 ; Volume: 4 ; Year: 2018 ; Pages: 308-322 ; Amsterdam: Elsevier

Classification
Wirtschaft
Subject
Doubly Fed Induction Generator
Dynamic Voltage Restorer
Optimal control
Wind energy
Wind Turbine

Event
Geistige Schöpfung
(who)
Falehi, Ali Darvish
Rafiee, Mansour
Event
Veröffentlichung
(who)
Elsevier
(where)
Amsterdam
(when)
2018

DOI
doi:10.1016/j.egyr.2018.01.006
Handle
Last update
10.03.2025, 11:43 AM CET

Data provider

This object is provided by:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.

Object type

  • Artikel

Associated

  • Falehi, Ali Darvish
  • Rafiee, Mansour
  • Elsevier

Time of origin

  • 2018

Other Objects (12)