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cpso based lfc for a Two-Area

by R. Arivoli, Dr. I. A. Chidambaram
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 38 - Number 7
Year of Publication: 2012
Authors: R. Arivoli, Dr. I. A. Chidambaram
10.5120/4697-6846

R. Arivoli, Dr. I. A. Chidambaram . cpso based lfc for a Two-Area. International Journal of Computer Applications. 38, 7 ( January 2012), 1-10. DOI=10.5120/4697-6846

@article{ 10.5120/4697-6846,
author = { R. Arivoli, Dr. I. A. Chidambaram },
title = { cpso based lfc for a Two-Area },
journal = { International Journal of Computer Applications },
issue_date = { January 2012 },
volume = { 38 },
number = { 7 },
month = { January },
year = { 2012 },
issn = { 0975-8887 },
pages = { 1-10 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume38/number7/4697-6846/ },
doi = { 10.5120/4697-6846 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:25:12.555569+05:30
%A R. Arivoli
%A Dr. I. A. Chidambaram
%T cpso based lfc for a Two-Area
%J International Journal of Computer Applications
%@ 0975-8887
%V 38
%N 7
%P 1-10
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper the design of Proportional Integral (PI) controller is proposed using Craziness Particle Swarm Optimization (CPSO) based Integral Square Error (CPSOISE), CPSO based Apex Stability Verge (CPSOASV) and Multi-Objective based CPSO (MOCPSO) are used to design the controller for a two-area power system considering Governor Dead Band (GDB) and Generation Rate Constraint (GRC) nonlinearities coordinate with Super Conducting Magnetic Energy Storage (SMES) units and interconnected through Thyristor Controlled Phase Shifter (TCPS). CPSO algorithm is a powerful optimum search technique, the salient advantage is that it is highly insensitivity to large load changes and disturbances in the presence of plant parameter variations and system nonlinearities under load following variations. For the proposed method, two types of controllers namely, Mutual Aid Criterion (MAC) based Integral Square Error (ISE) and Apex Stability Verge (ASV) controllers are designed first and then the proposed MOCPSO controller is designed. Simulation results of the proposed MOCPSO controller is not only effective in damping out frequency oscillations, but also capable of alleviating the transient frequency swing caused by the disturbances. From the dynamic responses it reveals that the MOCPSO based controller for the two area reheat power system with SMES, interconnected with TCPS ensures better transient performance and faster settling time than that of the CPSOISE based controller.

References
  1. B . Shayeghi, H. A. Shayanfar, A. Jalili, “Load frequency Control Strategies: A state-of-the-art survey for the researcher”, Energy Conservation and Management, Vol. 50(2), pp. 344-353, 2009.
  2. I. Ibraheem, P. Kumar, DP. Kothari, “Recent Philosophies of Automatic Generation Control Strategies in Power Systems” IEEE Transactions on Power Systems, pp. 346-357, 2005.
  3. L. Basanez, J. Riera, J. Ayza, “Modeling and simulation of Multi area Power System Load frequency Control” Mathematics and computers in Simulation, PP. 54-62, 1984.
  4. Janardan Nanda, Ashish Mangla, Sanjay Suri, “Some new findings on Automatic Generation Control of an interconnected hydrothermal system with conventional controllers”, IEEE Transactions on Energy Conversion, Vol. 21(1), pp.187-194, 2006 .
  5. I. A. Chidambaram, S. Velusami, “Design of Decentralized Biased Controllers for Load-Frequency Control of Interconnected Power Systems”, Electric Power Components and Systems, Vol. 33, PP. 1313-1331, 2005.
  6. I. A. Chidambaram, S.Velusami, “Design of decentralized biased dual mode controllers for load-frequency control of interconnected power systems considering GDB and GRC nonlinearities”, International Journal of Energy Conversion and Management (Elsevier), Vol. 48, pp.1691-1702, 2007.
  7. Gayadhar Panda, Sidhartha Panda, Cemal Ardil, “Automatic Generation Control of Interconnected Power System with Generation Rate Constraints by Hybrid Neuro Fuzzy Approach”, World Academy of Science, Engineering and Technology, Vol. 52, pp.543-548, 2009.
  8. I. A. Chidambaram, S. Velusami, “Design of decentralized biased controllers for load-frequency control of interconnected power systems considering governor deadband nonlinearity”, IEEE International Conference (INDICON 2005), Chennai, pp. 521-525, December 2005.
  9. B. Paramasivam, R. Arivoli, I. A. Chidambaram, “Design of GA based decentralized controller for Load-Frequency Control of interconnected power systems considering Thyristor controlled phase shifter (TCPS) in the tie-line”, UGC sponsored National Conference on Planning, Operation and Control of interconnected Power Systems, Annamalai University, Annamalainagar, pp. 66-76, March 2009.
  10. S. C. Tripathy, Balasubramanian, and P. S. Chandramohanan Nair “Effect of superconducting magnetic energy storage in power systems”, IEEE Transactions on Power systems, Vol. 7. No. 3, pp. 1266-1273, Aug. 1992.
  11. R. J. Abraham, D. Das and A. Patra, “Automatic Generation Control of an Interconnected Hydrothermal Power System Considering Superconducting Magnetic Energy Storage”, Electrical Power and Energy Systems; 29, pp. 271-579, 2007.
  12. Sathans Suhag and Akhilesh Swarup, “Automatic Generation Control of Multi-Area Multi Unit Power System with SMES using Fuzzy Gain Scheduling Approach”, International Journal of Research and Reviews in Electrical and Computer Engineering (IJRRECE), Vol. 1, No. 2, pp. 83-91, June 2011.
  13. Pal, B. C., Coonick, A. H., and Macdonald, D. C.: ‘Robust damping controller design in power systems with superconducting magnetic energy storage devices’, IEEE Trans. Power Syst., 15, (1), pp. 320–325, 2000.
  14. Rajesh Joseph Abraham; Das, D.; and Patra, A., “AGC Study of a Hydrothermal System with SMES and TCPS”, European Transactions on Electrical Power, 2008; DOI: 10. 1002/etep. 235, 2008.
  15. Mairaj Uddin Mufti, Shameem Ahmad Lone, Sheikh Javed Iqbal, Imran Mushtaq, “Improved Load Frequency Control with Superconducting Magnetic Energy Storage in Interconnected Power System”, IEEJ Transaction, Vol. 2, pp. 387-397, 2007.
  16. Baker, R., Guth, G., Egli, W., and Eglin, P.: ‘Control algorithm for a static phase shifting transformer to enhance transient and dynamic stability of large power systems’, IEEE Trans. Power Appar. Syst., 1982, 101, (9), pp. 3532–3542.
  17. Wang HF.; Shift FJ.; Li M., “Analysis of Thyristor Controlled Phase Shifter Applied in Damping Power System Oscillations”, International Journal of Electrical Power and Energy Systems, 19:1–9, 1997.
  18. R. J. Abraham, D. Das, A. Patra, “AGC of a hydrothermal system with thyristor controlled phase shifter in the tie-line”, IEEE Transaction on Power Systems, 2006: 0-7803-9525, 2006.
  19. Y. L. Karnavas, and D. P. Papadopoulos, ‘AGC for autonomous power system using combined intelligent techniques’, Int. J. Electr. Power Syst. Res., 2002, 62, pp. 225–239, 2002.
  20. J. Kennedy and R. Eberhart, “Particle swarm optimization”, Neural Networks, 1995. Proceedings., IEEE International Conference on Neural networks vol. 1, pp 1942-1948, vol. 4, 1995.
  21. M. Clere, J.Kennady, “The particle swarm explosion, stability and convergence in multi dimensional complex space,” IEEE Transaction Evolutionary Computation, vol. 6, pp. 58-73, 2002.
  22. Tetsuo Sasaki, KazuhiroEnomoto, “Statistical and Dynamic Analysis of Generation control performance standards,” IEEE Transactions on Power Systems, Vol. xx PP 100-105, 2001.
  23. Davoud Sedighizadeh and Ellips Masehian, “Particle Swarm Optimization Methods, Taxonomy and Applications,” International Journal of Computer Theory and Engineering, Vol. 1, No. 5, pp.1793-8201, 2009.
  24. Margarita Reyes-Sierra and Carlos A. Coello-Coello, “Multi-Objective Particle Swarm Optimizers: A Survey of the State-of-the-Art”, International Journal of Computational Intelligence Research, Vol. 2, No. 3, pp. 287–308, 2006.
  25. SL.Ho, S. Yang, G. Ni,E.Wc.Lo, H.C. Wong.”A Particle Swarm Optimization based method for multi-objective design optimization based method for multi- objective design optimization,” IEEE Transaction on magnetic, vol. 41 (5), pp. 1756-1759, 2005.
  26. Katsuhiko Ogata, Modern Control Engineering, Prentice Hall of India Private Limited, New Delhi, India, July 1986.
Index Terms

Computer Science
Information Sciences

Keywords

Apex Stability Verge (ASV) Craziness Particle Swarm Optimization based Apex Stability Verge (CPSOASV) CPSO based Integral Square Error (CPSOISE) Multi-Objective CPSO (MOCPSO).

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