CFP last date
20 May 2024
Call for Paper
June Edition
IJCA solicits high quality original research papers for the upcoming June edition of the journal. The last date of research paper submission is 20 May 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

Performance comparison of DE, PSO and GA approaches in Transmission Power Loss minimization using FACTS Devices

by K. Chandrasekar Baboo, N. V. Ramana
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 33 - Number 5
Year of Publication: 2011
Authors: K. Chandrasekar Baboo, N. V. Ramana
10.5120/4020-5717

K. Chandrasekar Baboo, N. V. Ramana . Performance comparison of DE, PSO and GA approaches in Transmission Power Loss minimization using FACTS Devices. International Journal of Computer Applications. 33, 5 ( November 2011), 58-62. DOI=10.5120/4020-5717

@article{ 10.5120/4020-5717,
author = { K. Chandrasekar Baboo, N. V. Ramana },
title = { Performance comparison of DE, PSO and GA approaches in Transmission Power Loss minimization using FACTS Devices },
journal = { International Journal of Computer Applications },
issue_date = { November 2011 },
volume = { 33 },
number = { 5 },
month = { November },
year = { 2011 },
issn = { 0975-8887 },
pages = { 58-62 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume33/number5/4020-5717/ },
doi = { 10.5120/4020-5717 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:19:24.912764+05:30
%A K. Chandrasekar Baboo
%A N. V. Ramana
%T Performance comparison of DE, PSO and GA approaches in Transmission Power Loss minimization using FACTS Devices
%J International Journal of Computer Applications
%@ 0975-8887
%V 33
%N 5
%P 58-62
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper presents the performance comparison of meta–heuristics algorithms such as DE (Differential Evolution), PSO (Particle Swarm Optimization) and GA (Genetic Algorithm for the problem of Transmission Power Loss (TPL) minimization using Flexible AC Transmission System (FACTS) devices. In addition to that a novel power flow method is proposed using Broyden – Shamanski method with Sherman – Morrison formula (BSS) to reduce the computational time without loss of accuracy and the results are compared with the conventional Newton Raphson (NR) method. Simulation test are carried on WSCC 9 bus, New England 39 bus and IEEE 118 bus test systems. Results indicate that location of FACTS device using DE algorithm minimizes TPL better with higher computational efficacy when compared to PSO and GA.

References
  1. Mamandur K. R. C, Chenoweth R. D. “Optimal Control of Reactive Power Flow for Improvements in Voltage Profiles and for Real power Loss Minimization”, IEEE Trans. Power Apparatus and Syst., Vol. 100, no. 7, pp. 3185 – 3194, Jul. 1981.
  2. Bagriyanik F. G, “Power Loss Minimization using Fuzzy Multi Objective formulation and Genetic Algorithm”, IEEE Bologna Power Tech Conference, June 23-26, 2003.
  3. Wenjuan Zhang, Fangxing Li and Leon M Tolbert “Review of Reactive Power Planning: Objectives Constraints”, IEEE Trans. Power Syst., Vol. 22, no. 4, pp. 2177 – 2186, Nov 2007.
  4. Xin-She Yang, “Engineering Optimization – An Introduction to Metaheuristic Applications” John Wiley & Sons, Hoboken, New Jersy, 2010.
  5. K Y Lee, M.A. El-Sharkawi, “Modern Heuristic Optimization Techniques” IEEE press and Wiley – InterScience, New Jersy, 2008.
  6. Rody P S Oldenhuis, “Trajectory Optimization of a mission to the Solar Bow shock and minor planets”, MSc thesis report, Delft University of Technology, Netherlands, Jan 2010.
  7. Goldberg D.E. 1989, “Genetic Algorithms in Search, Optimization, and Machine Learning”, Kluwer Academic Publishers, Boston, 1989
  8. Storn, R. and Price, K., “Differential Evolution - a Simple and Efficient Heuristic for Global Optimization over Continuous Spaces,” Journal of Global Optimization, Vol. 11, pp. 341–359, 1997.
  9. Kennedy, J. and Eberhart, R. C., “Particle swarm optimization,” Proceedings of IEEE International Conference on Neural Networks, pp. 1942–1948, 1995.
  10. S. Gerbex, R. Cherkaoui, A.J. Germond, Optimal Location of Multitype FACTS Devices in a Power System by Means of Genetic Algorithms, IEEE Trans. Power Syst., vol. 16, no. 3, August 2001, pp. 537-544.
  11. S. Gerbex, R. Cherkaoui, and A. J. Germond, Optimal Location of FACTS Devices to Enhance Power System Security, IEEE Bologna Power Tech Conference, Bologna, Italy, June 2003, 3, pp. 23-26.
  12. N. V. Ramana and K. Chandrasekar, Multi Objective Genetic Algorithm to mitigate the composite problem of TTC, Voltage Stability and Transmission loss minimization, 39th IEEE North American Power Symposium, New Mexico, 2nd October 2007, USA.
  13. Wang Feng, and G. B. Shrestha, Allocation of TCSC devices to optimize Total Transfer capacity in a Competitive Power Market, IEEE PES Winter Meeting, Feb 2001, 2, pp. 587 -593.
  14. S. Buhmiler, N. Krejic and Z. Luzanin, Practical Qausi – Newton algorithms for singular non linear systems, Journal on Numerical Algorithms, Springer, vol. 55, n. 4, January 2010, pp 481-502.
  15. C. G. Broyden, A class of methods for solving Non Linear Simultaneous Equations, Mathematics of Computation, vol. 19, n. 92, October 1965, pp. 577-593.
  16. http://www.pserc.cornell.edu/tcc/tcc.md/.
  17. http://www.ee.washington.edu/research/pstca/.
  18. R. D. Zimmermann and Carlos E. Murillo-Sánchez, Matpower a Matlab® power system simulation package, User’s Manual, Version 3.2, 2007.
Index Terms

Computer Science
Information Sciences

Keywords

Differential Evolution Genetic Algorithm Particle Swarm Optimization Transmission Power Loss FACTS device.

Powered by PhDFocusTM