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Neural Computing and Applications
Published in: Neural Computing and Applications 5/2014

01-10-2014 | Original Article

Modeling and simulation of static loads for wind power applications

Authors: M. K. Döşoğlu, A. Basa Arsoy

Published in: Neural Computing and Applications | Issue 5/2014

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Abstract

This study aims to model and simulate static nonlinear loads with wind power generation to evaluate the impact of load models on wind power systems. Nonlinear loads are modeled as exponential load model, ZIP load model and combination of exponential/ZIP with an induction motor. The wind power generator is represented with a reduced-order doubly fed induction generator (DFIG) model. Developed models have been implemented in a grid-integrated wind power plant and simulated in MATLAB/SIMULINK. The effects of nonlinear loads into wind power plant are investigated in terms of bus voltages, angular speed, electrical torque, and d–q stator axes currents. Additional analyses are conducted to compare the behaviors of full- and reduced-order DFIG models under a selected loading condition. The results of this study indicate that the response of a system with DFIG is dependent of the load modeling and reduced-order DFIG model shows more stable trend than full-order DFIG model.
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Metadata
Title
Modeling and simulation of static loads for wind power applications
Authors
M. K. Döşoğlu
A. Basa Arsoy
Publication date
01-10-2014
Publisher
Springer London
Published in
Neural Computing and Applications / Issue 5/2014
Print ISSN: 0941-0643
Electronic ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-014-1583-3

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