CFP last date
22 April 2024
Call for Paper
May Edition
IJCA solicits high quality original research papers for the upcoming May edition of the journal. The last date of research paper submission is 22 April 2024

Submit your paper
Know more
The week's pick
Responsive image
Enhancing Privacy Preservation: Multi-Attribute Protection with P-Sensitive K-Anonymity

Twinkle Patel Kiran Amin
Random Articles
Reseach Article

Multi-Objective Optimization using Evolutionary Computation Techniques

by Rambabu CH, Dr.Y.P.Obulesh, Dr.CH.Saibabu
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 27 - Number 11
Year of Publication: 2011
Authors: Rambabu CH, Dr.Y.P.Obulesh, Dr.CH.Saibabu
10.5120/3345-4609

Rambabu CH, Dr.Y.P.Obulesh, Dr.CH.Saibabu . Multi-Objective Optimization using Evolutionary Computation Techniques. International Journal of Computer Applications. 27, 11 ( August 2011), 19-25. DOI=10.5120/3345-4609

@article{ 10.5120/3345-4609,
author = { Rambabu CH, Dr.Y.P.Obulesh, Dr.CH.Saibabu },
title = { Multi-Objective Optimization using Evolutionary Computation Techniques },
journal = { International Journal of Computer Applications },
issue_date = { August 2011 },
volume = { 27 },
number = { 11 },
month = { August },
year = { 2011 },
issn = { 0975-8887 },
pages = { 19-25 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume27/number11/3345-4609/ },
doi = { 10.5120/3345-4609 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:13:29.393850+05:30
%A Rambabu CH
%A Dr.Y.P.Obulesh
%A Dr.CH.Saibabu
%T Multi-Objective Optimization using Evolutionary Computation Techniques
%J International Journal of Computer Applications
%@ 0975-8887
%V 27
%N 11
%P 19-25
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper an EP and PSO based optimization algorithms have been proposed for solving optimal power flow problems with multiple objective functions. These algorithms take into consideration all the equality and inequality constraints. The improvement in system performance is based on reduction in cost of power generation and active power loss. The proposed algorithms have been compared with the other methods reported in the literature. Simulation studies have been carried out for the optimal solutions of the IEEE 14-bus and IEEE 30-bus systems.

References
  1. Kennedy J, Eberhart R. “Particle swarm optimization” Proceedings of IEEE International Conference on Neural Networks (ICNN’95) Perth, Australia: IEEE Press; 1995. Vol. IV. p. 1942–1948.
  2. Shi Y, Eberhart R. “A modified particle swarm optimizer” Proceedings of IEEE International Conference on Evolutionary Computation (ICEC’98). Anchorage: IEEE Press; 1998. p. 69–73.
  3. Shi Y, Eberhart R. “Parameter selection in particle swarm optimization” Proceedings of the 1998 Annual Conference on Evolutionary Programming. San Diego: MIT Press; 1998.
  4. Fukuyama Y. et al. “A particle swarm optimization for reactive power and voltage control considering voltage security assessment”. IEEE Trans Power Systems 2000; 15(4):1232–1239.
  5. Naka S, Genji T, Yura T, Fukuyama Y. “A hybrid particle swarm optimization for distribution state estimation” IEEE Trans Power Systems 2003; 18(1):60–68.
  6. IEEE Special Publication 90TH 0358-2PWR, “Voltage Stability of Power Systems: Concepts, Analytical Tools and Industry Experience", The IEEE Working Group on Voltage Stability, 1990.
  7. A J Wood and B F Wollenberg, “Power generation operation and control”, John Wiley and Sons Inc.Singapore, 1984.
  8. Brian Stott, Ongun Alsac, and Alcir J. Monticelli, “Security analysis and optimization”, Proc. of IEEE, Vol.75, No.12, December 1987, pp.1623-1644.
  9. Parker, C.J., I. F Morrison, and D. Sutanto, “Application of an optimization method for determining the reactive margin from voltage collapse in reactive power planning”, IEEE Trans. on Power Systems, Vol.11, No. 3, August 1996, pp. 1473-1481.
  10. Venikov, V.A., V.A Stroev, V.I. Idelchick, and V.I. Tarasov, “Estimation of electric power system steady state stability in load flow calculations", IEEE Trans. on PAS, Vol.PAS-94, No.3, May/June 1975, pp.1034-1040.
  11. P.A. Lof,G. Andersson, D. Hill, “Voltage dependent reactive power limits for voltage stability studies”, IEEE Trans.on power systems, Vol. 10, No. 1, Feb. 1995, pp. 220-228.
  12. P Kessel and H Glavitsch, “Estimating the voltage stability of a power system”, IEEE Trans. on PD, Vol.1, No.3, pp.346-354, 1986.
  13. W. Ongsakul and T. Tantimaporn, “Optimal power flow by improved evolutionary programming”, Electric Power Components and Systems, 2006, 34:pp.79-95,.
  14. Abido MA. “Optimal power flow using particle swarm optimization,” Electric Power Energy Syst 2002; 24(7): pp.563-71.
  15. Peerapol Jirapong and Weerakorn Ongsakul “Optimal placement of multi type FACTS devices for total transfer capability enhancement using hybrid evolutionary algorithm”, Electric power componenets and systems, 01 September 2007, 35:pp.981-1005.
  16. Ramasubramanian Jayashree and Mohammed Abdullah Khan “A unified optimization approach for the enhancement of available transfer capability and congestion management using unified power flow controller”, Serbian journal of electrical engineering, Vol.5, No.2, November 2008, pp.305-324.
  17. D.Devaraj and B.Yegnanarayana, “Genetic Algorithm-Based Optimal Power Flow for Security Enhancement”, IEE Proceedings on Generation, Transmission and Distribution 2005, 152(6), pp 899-905.
  18. X.P.Zhang, S.G.Petoussis and K.R.Godfrey “Nonlinear interior point optimal power flow method based on a current mismatch formulation”, IEE Proc.-Gener. Transm. Distrb. Vol.152, No.6, January 2005, pp.795-805.
Index Terms

Computer Science
Information Sciences

Keywords

EP PSO Active Power Loss

Powered by PhDFocusTM