Loading…

Wind Turbine Structural Modeling Consideration for Dynamic Studies of DFIG Based System

This paper presents the dynamic analysis of a grid connected Doubly Fed Induction Generator based wind turbine generator system with the detailed mechanical structural modelling of the wind turbine. The Euler-Lagrangian approach has been used for the structural dynamics of the wind turbine. The driv...

Full description

Saved in:
Bibliographic Details
Published in:IEEE transactions on sustainable energy 2017-10, Vol.8 (4), p.1463-1472
Main Authors: Prajapat, Ganesh P., Senroy, Nilanjan, Kar, Indra Narayan
Format: Article
Language:English
Subjects:
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:This paper presents the dynamic analysis of a grid connected Doubly Fed Induction Generator based wind turbine generator system with the detailed mechanical structural modelling of the wind turbine. The Euler-Lagrangian approach has been used for the structural dynamics of the wind turbine. The driving input mechanical power to the wind turbine has been modelled by the Blade Element Momentum (BEM) method and same has been used to calculate the tangential force on the blades responsible for the edgewise vibration of it. A polynomial regression model and feed-forward back-propagation neural network have been used to replace the BEM algorithm for modal analysis and time-domain simulation, respectively. The different modes of the entire system at different operating points and system parameters have been found and the grid-structure interaction is analyzed. The results offer a deep understanding of the combined electromechanical, aerodynamic, and mechanical structural dynamics of the system and may further be used to design various control schemes. The structural and aerodynamic data from the NREL 5-MW three-bladed Horizontal Axis Wind Turbine were used for the simulation. The model has been validated by NREL's simulation tool, FAST v7.
ISSN:1949-3029
1949-3037
DOI:10.1109/TSTE.2017.2690682