Share This Article:

Genetic Algorithm Based Performance Analysis of Self Excited Induction Generator

Abstract Full-Text HTML Download Download as PDF (Size:684KB) PP. 859-864
DOI: 10.4236/eng.2011.38105    6,561 Downloads   11,114 Views   Citations

ABSTRACT

This paper investigates the effects of various parameters on the terminal voltage and frequency of self excited induction generator using genetic algorithm. The parameters considered are speed, capacitance, leakage reactance, stator and rotor resistances. Simulated results obtained using genetic algorithm facilitates in exploring the performance of self-excited induction generator. The paper henceforth establishes the application of user friendly genetic algorithm for studying the behaviour of self-excited induction.

Conflicts of Interest

The authors declare no conflicts of interest.

Cite this paper

H. Ibrahim and M. Metwaly, "Genetic Algorithm Based Performance Analysis of Self Excited Induction Generator," Engineering, Vol. 3 No. 8, 2011, pp. 859-864. doi: 10.4236/eng.2011.38105.

References

[1] D. Joshi, K. Sandhu and M. Soni, “Voltage Control of Self-Excited Induction Generator Using Genetic Algorithm,” Turkish Journal of Electrical Engineering and Computer Sciences, Vol. 17, No. 1, 2009, pp. 87-97.
[2] S. Vadhera and K. Sandhu, “Genetic Algorithm Toolbox Based Investigation of Terminal Voltage and Frequency of Self Excited Induction Generator,” International Journal of Advanced Engineering & Application, Vol. 1, No. 1, 2010, pp. 243-250.
[3] K. Sandhu and D. Joshi, “A Simple Approach to Estimate the Steady-State Performance of Self-Excited Induction Generator,” Wseas Transactions on Systems and Control, Vol. 3, No. 3, 2008, pp. 208-218.
[4] S. Mahley and Y. Chauhan, “Steady State Analysis of Three-Phase Self-Excited Induction Generator,” Master Thesis, Department of Power Systems & Electric Drives, Thapar University, Patiala, 2008.
[5] Y. Cao and Q. Wu, “Teaching Genetic Algorithm Using Matlab,” International Journal of Electrical Engineering Education, Vol. 36, No. 2, 1999, pp. 139-153.
[6] S. Vadhera and K. Sandhu, “Constant Voltage Operation of Self Excited Induction Generator Using Optimization Tools,” International Journal of Energy and Environment, Vol. 2, No. 4, 2008, pp. 191-198.
[7] A. L. Alolah and M. A. Alkanhal, “Optimization Based Steady State Analysis of Three Phase Self-Excited Induction Generator,” IEEE Transactions on Energy Conversion, Vol. 15, No. 1, 2000, pp. 61-65. doi:10.1109/60.849117
[8] H. E. A. Ibrahim, M. Metwaly and M. Serag, “Analysis of Self Excited Induction Generator Using Symbolic Toolbox and Artificial Neural Network,” Ain Shams Journal of Electrical Engineering, Vol. 3, No. 8, 2010, pp. 17-28.
[9] D. Joshi and K. Sandhu, “Excitation Control of Self Excited Induction Generator Using Genetic Algorithm and Artificial Neural Network,” International Journal of Mathematical Modela and Methods In applied Sciences, Vol. 3, No. 1, 2009, pp. 68-75.
[10] K. Sandhu and D. Joshi, “Steady Sate Analysis of Self Excited Induction Generator Using Phasor Diagram Based Iterative Model,” Wseas Transactions on Power Systems, Vol. 3, No. 12, 2008, pp. 715-724.
[11] A.-F. Attia, H. Soliman and M. Sabry, “Genetic Algorithm Based Control System Design of a Self-Excited Induction Generator,” Czech Technical University in Prague Acta Polytechnica, Vol. 46, No. 2, 2006, pp. 11-22.
[12] D. Joshi, K. Sandhu and M. Soni, “Constant Voltage Constant Frequency Operation for a Self-Excited Induction Generator,” IEEE Transactions on Energy Conversion, Vol. 21, No. 1, 2006, pp. 228-234. doi:10.1109/TEC.2005.858074
[13] H. E. A. Ibrahim, “Design Parameters for Micro Ma- chined Tunneling Accelerometer Using Genetic Optimi- zation,” Ain Shams Journal of Electri-cal Engineering, Vol. 40, No. 4, 2005, pp. 787-806.

  
comments powered by Disqus

Copyright © 2020 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.