Analysis of Self Excited Induction Generator using Particle Swarm Optimization
In this paper, Novel method, Particle Swarm Optimization (PSO) algorithm, based technique is proposed to estimate and analyze the steady state performance of self-excited induction generator (SEIG). In this novel method the tedious job of deriving the complex coefficients of a polynomial equation and solving it, as in previous methods, is not required. By comparing the simulation results obtained by the proposed method with those obtained by the well known mathematical methods, a good agreement between these results is obtained. The comparison validates the effectiveness of the proposed technique.
[1] M. H. Haque, "A Novel Method of Evaluating Performance
Characteristics of a Self-Excited Induction Generator", IEEE
Transactions on Energy Conversion, Vol. 24, No. 2, pp.358-365, June
2009.
[2] Gurung K., Freere P.,"MATLAB symbolic computation for the steady
state modeling of symmetrically loaded self excited induction
generator", Kathmandu university journal of science, engineering and
technology, Vol. I, No. III, pp.1-7, January 2007.
[3] M. H. Haque, "Analysis of a Self-Excited Induction Generator with P-Q
Load Model", IEEE Transaction on Energy Conversion, Vol. 25, No. 1,
pp.265-267, March 2010.
[4] D. Joshi, K. S. Sandhu, and M. K. Soni, "Performance Analysis of Self-
Excited Induction Generator Using Artificial Neural Network", Iranian
Journal of Electrical and Computer Engineering, Vol. 5, No. 1, pp.57-62
Winter-Spring 2006.
[5] Raja Singh Khela, R. K. Bansal, K. S. Sandhu, and A. K. Goel,
"Cascaded ANN for Evaluation of Frequency and Air-gap Voltage of
Self-Excited Induction Generator", World Academy of Science,
Engineering and Technolgy 27, pp.301-307,2007.
[6] A.A.Arkadan,Y.Abou-Samra,Z.H.Ramadan, "Radial Basis Networks for
the Simulation of Stand Alone AC Generators during No-Break Power
Transfer", Marquette University, Milwaukee, WI, pp.237-243, 2007.
[7] S.Mahley, "Steady State Analysis of three phase Self-Excited Induction
Generator, Master Thesis, Department of Power Systems and Electric
Drives, Thapar University, Patiala, 2008.
[8] S Singaravelu Dr. S Velusami, "Generalized Steady State Modeling and
Analysis of Three Phase Self Excited Induction Generators",
International Journal of Emerging Electric Power Systems, Vol. 3, Issue
2, Article 1080, 2005.
[9] H.E.A.Ibrahim, M.M.Metwaly and M.F.Serag, "Analysis of self excited
induction generator (SEIG) using symbolic toolbox and artificial neural
network (ANN)", Ain shams journal of electrical engineering (ASJEE),
Vol.2, pp.17-28, Dec.2010.
[10] Raja Singh Khela , Raj Kumar Bansal , K. S. Sandhu and Ashok Kumar
Goel, "Application of Artificial Neural Network for Analysis of Self-
Excited Induction Generator", JCS and T, Vol. 6, No. 2, pp.73-79,
October 2006.
[11] R.C.Bansal,"Three-Phase Self-Excited Induction Generators:An
Overview", IEEE Transactions on Energy Conversion, Vol. 20, No. 2,
pp.292-299, June 2005.
[1] M. H. Haque, "A Novel Method of Evaluating Performance
Characteristics of a Self-Excited Induction Generator", IEEE
Transactions on Energy Conversion, Vol. 24, No. 2, pp.358-365, June
2009.
[2] Gurung K., Freere P.,"MATLAB symbolic computation for the steady
state modeling of symmetrically loaded self excited induction
generator", Kathmandu university journal of science, engineering and
technology, Vol. I, No. III, pp.1-7, January 2007.
[3] M. H. Haque, "Analysis of a Self-Excited Induction Generator with P-Q
Load Model", IEEE Transaction on Energy Conversion, Vol. 25, No. 1,
pp.265-267, March 2010.
[4] D. Joshi, K. S. Sandhu, and M. K. Soni, "Performance Analysis of Self-
Excited Induction Generator Using Artificial Neural Network", Iranian
Journal of Electrical and Computer Engineering, Vol. 5, No. 1, pp.57-62
Winter-Spring 2006.
[5] Raja Singh Khela, R. K. Bansal, K. S. Sandhu, and A. K. Goel,
"Cascaded ANN for Evaluation of Frequency and Air-gap Voltage of
Self-Excited Induction Generator", World Academy of Science,
Engineering and Technolgy 27, pp.301-307,2007.
[6] A.A.Arkadan,Y.Abou-Samra,Z.H.Ramadan, "Radial Basis Networks for
the Simulation of Stand Alone AC Generators during No-Break Power
Transfer", Marquette University, Milwaukee, WI, pp.237-243, 2007.
[7] S.Mahley, "Steady State Analysis of three phase Self-Excited Induction
Generator, Master Thesis, Department of Power Systems and Electric
Drives, Thapar University, Patiala, 2008.
[8] S Singaravelu Dr. S Velusami, "Generalized Steady State Modeling and
Analysis of Three Phase Self Excited Induction Generators",
International Journal of Emerging Electric Power Systems, Vol. 3, Issue
2, Article 1080, 2005.
[9] H.E.A.Ibrahim, M.M.Metwaly and M.F.Serag, "Analysis of self excited
induction generator (SEIG) using symbolic toolbox and artificial neural
network (ANN)", Ain shams journal of electrical engineering (ASJEE),
Vol.2, pp.17-28, Dec.2010.
[10] Raja Singh Khela , Raj Kumar Bansal , K. S. Sandhu and Ashok Kumar
Goel, "Application of Artificial Neural Network for Analysis of Self-
Excited Induction Generator", JCS and T, Vol. 6, No. 2, pp.73-79,
October 2006.
[11] R.C.Bansal,"Three-Phase Self-Excited Induction Generators:An
Overview", IEEE Transactions on Energy Conversion, Vol. 20, No. 2,
pp.292-299, June 2005.
@article{"International Journal of Electrical, Electronic and Communication Sciences:58340", author = "Hassan E. A. Ibrahim and Mohamed F. Serag", title = "Analysis of Self Excited Induction Generator using Particle Swarm Optimization", abstract = "In this paper, Novel method, Particle Swarm Optimization (PSO) algorithm, based technique is proposed to estimate and analyze the steady state performance of self-excited induction generator (SEIG). In this novel method the tedious job of deriving the complex coefficients of a polynomial equation and solving it, as in previous methods, is not required. By comparing the simulation results obtained by the proposed method with those obtained by the well known mathematical methods, a good agreement between these results is obtained. The comparison validates the effectiveness of the proposed technique.
", keywords = "Evolution theory, MATLAB, optimization, PSO, SEIG.", volume = "5", number = "9", pages = "1217-5", }
