Manuscript Number : CSEIT172371

Performance Analysis of Scig and DFIG-Based Wind Turbines

Authors(2) :-Kishan V Dave, Nimish R Suchak

This paper presents a comparative performance analysis of squirrel cage induction generator (SCIG) and doubly fed induction generator (DFIG) systems driven by wind turbines under different operating conditions. Also, the constant and variable-speed configurations are compared regarding short-term flicker severity, Pst. The constant speed configurations are based on SCIG in addition to SCIG equipped with static synchronous compensator (STATCOM) with the same generation capacity. In this paper, comprehensive models of wind turbine are used to analyze power and voltage fluctuations. The short-time flicker index is used to assess the emitted voltage fluctuation. The effects of grid short circuit capacity and impedance angle on flicker emission are investigated. The influences of site mean-wind-speed and turbulence intensity on voltage fluctuation are also examined. A flickermeter model is implemented according to the guidelines provided by IEC 61000-4-15 to evaluate the severity of voltage fluctuation emission. The models of different system components along with their control schemes are simulated using Matlab/Simulink® package.

Authors and Affiliations

Kishan V Dave
A. V. Parekh Technical Institute, Rajkot, Gujarat, India
Nimish R Suchak
A. V. Parekh Technical Institute, Rajkot, Gujarat, India

Wind Turbine, SCIG, DFIG, Maximum Power Point Tracking (MPPT), Voltage Flicker

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Publication Details

Published in : Volume 2 | Issue 3 | May-June 2017
Date of Publication : 2017-06-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 438-445
Manuscript Number : CSEIT172371
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Kishan V Dave, Nimish R Suchak, "Performance Analysis of Scig and DFIG-Based Wind Turbines", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 2, Issue 3, pp.438-445, May-June-2017.
Journal URL : http://ijsrcseit.com/CSEIT172371

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