Improvement The DFIG Active Power with Variable Speed Wind using Particle Swarm Optimization
Keywords:
Wind, Turbine Generator, Doubly Fed Induction Generator (DFIG), Variable Wind Speed, Particle Swarm Optimization (PSO)Abstract
The Wind Energy Conversion System (WECS) has become very popular and more attractive to study the possibility of replacing the conventional power source by renewable energy. This paper is focusing on the modeling and analysis of (DFIG) in Matlab/Smulink with constant and variable speed wind. Three test systems are considered and implemented. The first system is studied with constant wind speed using sinusoidal pulse width modulation (SPWM) to control the switching of two level three phase back to back converters. The second system is investigated also with constant wind speed but using space vector pulse width modulation (SVPWM). The two systems have been simulated and the results shows the effect of each type of pulse width modulation.
Two fault conditions are subjected to the second system, single line to ground fault at phase A (in 33KV line), programmable fault (three phase voltage drop to 0.5pu) at the Grid bus (132KV bus). Then the system recovery at the steady-state under faults is shown.
For the third system the input was the variable speed wind, the simulation results illustrate that when the input is variable wind speed the generated power will be reduced and the system behavior unstable, therefore, the control circuit is needed for the optimization to reduce the losses of the generated power; this optimization can be made by tuning the controllers gains with new suitable values, so the optimization is made by using Particle Swarm Optimization (PSO).
The new optimal values improved the system behavior, and illustrated the possibility of operation with variable wind speed.
Downloads
References
T. Ackermann, “Wind Power in Power Systems”, Royal Institute of Technology, Stockholm, Sweden, 2005. (Book).
H. T. Rishag, “The effects of sudden changes in wind speed on the design of doubly-fed induction generator (DFIG) controller in wind turbines”, Energy and fuel research center, University of Technology. P. 365-386. December 2011. (Conference).
O. Anaya-Lara, et al., “Wind energy generation modelling and control”, A John Wiley and Sons, Ltd., Publication, 2009. (Book).
A. Khaligh, and O. C. Onar, “Energy harvesting solar, wind, and ocean energy conversion systems”, Taylor and Francis Croup, an informa business, 2010. (Book).
S. Vanukuru, and S. Sukhavasi,“ Active & reactive Power control of a doubly fed induction generator driven by a wind turbine”, International Journal of power system operation and energy management, Volume- 1, Issue-2, 2011, 83-90.
T. M. Prakash & S. S. Ahhamad, “Direct Torque Control for Doubly Fed Induction Machine-Based Wind Turbines Under Voltages Dips and Without Crowbar Protection”, International Journal of Electrical and Electronics Engineering (IJEEE), Vol-1, 2012.
S. Li and S. Sinha, “A simulation analysis of double-fed generator for wind energy conversion using PSpice”, IEEE, 2006, Texas A&M University – Kingsville, USA.
Y. S. Rao and A. J. Laxmi, “Direct torque control of doubly fed induction generator based wind turbine under voltage dips”, International Journal of Advances in Engineering & Technology, Vol. 3, Issue 2, pp. 711-720, 2012.
W. Liu, L. Liu, and D. A. Cartes, “Particle swarm optimization a general design tool in power engineering”, IEEE, October 2011.
B. K. Panigrahi, A. Abraham, and S. Das, “Computational intelligence in power engineering”, Springer-Verlag Berlin Heidelberg, 2010.
C. Du and G. Yu, “Optimal PI Control of a Permanent Magnet Synchronous Motor Using Particle Swarm Optimization”, IEEE, October 31,2011.
H. K. Ahmed, “Enhancement of induction generator in wind energy system", M. Sc. Thesis, University of Technology, Iraq, 2013.
Published
How to Cite
Issue
Section
Copyright (c) 2016 Siraj Manhal Hameed
This work is licensed under a Creative Commons Attribution 4.0 International License.
