CFP last date
20 January 2025
Call for Paper
February Edition
IJCA solicits high quality original research papers for the upcoming February edition of the journal. The last date of research paper submission is 20 January 2025

Submit your paper
Know more
The week's pick
Responsive image
SFLA-Based Line Balancing and Task Optimization in Master-Slave Controlled Hanger Transportation Systems for Garment Production

Duc Hoang Nguyen
Random Articles
Reseach Article

Optimal Power Flows with Security Constraints using Multi Agent based PSO Algorithms by Optimal Placement of Multiple SVCS

by K. Ravi Kumar, S. Anand, M. Sydulu
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 52 - Number 10
Year of Publication: 2012
Authors: K. Ravi Kumar, S. Anand, M. Sydulu
10.5120/8240-1514

K. Ravi Kumar, S. Anand, M. Sydulu . Optimal Power Flows with Security Constraints using Multi Agent based PSO Algorithms by Optimal Placement of Multiple SVCS. International Journal of Computer Applications. 52, 10 ( August 2012), 29-37. DOI=10.5120/8240-1514

@article{ 10.5120/8240-1514,
author = { K. Ravi Kumar, S. Anand, M. Sydulu },
title = { Optimal Power Flows with Security Constraints using Multi Agent based PSO Algorithms by Optimal Placement of Multiple SVCS },
journal = { International Journal of Computer Applications },
issue_date = { August 2012 },
volume = { 52 },
number = { 10 },
month = { August },
year = { 2012 },
issn = { 0975-8887 },
pages = { 29-37 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume52/number10/8240-1514/ },
doi = { 10.5120/8240-1514 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:51:56.069337+05:30
%A K. Ravi Kumar
%A S. Anand
%A M. Sydulu
%T Optimal Power Flows with Security Constraints using Multi Agent based PSO Algorithms by Optimal Placement of Multiple SVCS
%J International Journal of Computer Applications
%@ 0975-8887
%V 52
%N 10
%P 29-37
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper puts forward the implementation of multiagent based PSO algorithms (TDLSMADSO & CLSMAPSO) to obtain the optimal power flows by optimally placing SVC devices. The static var compensator (SVC) is modeled using susceptance model with modifications in the Y bus of the Newton Raphson Algorithm. The constraints related to violation limits, minimization of voltage stability index, and line loss are dealt using penalty factor approach. The new multi agent based cubic lattice and two dimensional lattice structured based PSO algorithms were considered for optimizing power flows while satisfying all the constraints mentioned above. These algorithms were tested on IEEE 30 and IEEE 14 bus systems to identify the suitable location, its susceptance value and firing angle. The results obtained were quite encouraging and will be useful in electrical restructuring.

References
  1. Hermann W. Dommel, and William F. Tinney,"optimal Power Flow Solutions"
  2. Sivasubramani. S, Shanti Swarup K, Multiagent Based Particle Swarm Optimization Approach to Economic Dispatch With Security Constraints December27-29'2009, International Conference on Power systems, ,Kharagpur" .
  3. Bo Yang,Yuping ChenmZunlian Zhao and Qiye Han, "Solving Optimal Power Flow Problems with improved Particle Swarm Optimization",Proceedings of 6th world congress on Intelligent Control and Automation,June 21-23,2006,Dalian,China.
  4. Taranto, L. M. V. G. Pinto, M. V. F. Pereira, "Repre-sentation of FACTS Devices in Power System Economic Dispatch," IEEE Trans. On Power $ystems, Vol. 7, No. 2, May 1992, pp. 572-576.
  5. Z. Lu, M. S. Li, W. J. Wang, Q. H. Wu, " Optimal Location for FACTS devices by Bacterial Swarming algorithm for reactive Power Planning', Proceedings of IEEE congress on Evolutionary Computation (CEC2007)
  6. J. Nanda, and B. R. Narayanan, "Application of genetic algorithm to economic load dispatch with line flow constraints," Int Journal of Electric Power Energy Systems, pp. 723-729, 2002.
  7. Hingorani NG. Power electronics in electrical utilities: Role of powerelectronics in future power systems. Proc IEEE 1988;76 (4):481–2. April.
  8. Hingorani NG, Gyugyi L. Understanding FACTS: concepts and technology of ?exible ac transmission systems. New York: IEEE Press; 1999.
  9. Taranto GN, Pinto LMVG, Pereira MVF. Representation of FACTS devices in power system economic dispatch. IEEE Trans Power Syst 1992;7 (2):572–6.
  10. Gotham DJ, Heydt GT. Power ?ow control and power ?ow studies for systems with FACTS devices. IEEE Trans Power Syst 1998;13 (1):60–5.
  11. Ge SY, Chung TS. Optimal active power ?ow incorporating powe r?ow control needs in ?exible AC transmission systems. IEEE Trans Power Syst 1999;14 (2):738–44.
  12. J. Kennedy, and R. Eberhart, "Particle swarm optimization," Proc IEEE Int Conf Neural Networks, Aust, pp. 1942-1948, 1995.
  13. Ambriz-Perez H, Acha E, Fuerte-Esquivel CR. Advanced SVC model for Newton–Raphson Load Flow and Newton optimal power ?ow studies. IEEE Trans Power Syst 2000;15 (1):129–36.
  14. M. Wooldridge, An introduction to multiagent system. New York: Wiley, 2002.
  15. W. Zhong, J. Liu, M. Xue, and L. Jiao, " A multiagent genetic algorithm for global numerical optimization," IEEE Trans on Sys, Man and Cybernatics, pp. 1128-1141, 2004.
  16. A. Wood. B. Woolenberg, power generation,operation and control, New York: Wiley,1996.
Index Terms

Computer Science
Information Sciences

Keywords

Multi agent systems Optimization techniques Particle swarm optimization Optimal power flows security constraints

Powered by PhDFocusTM