A REDUCTION OF REAL POWER LOSS BY ENRICHED GENETIC ALGORITHM

Authors

  • Dr.K.Lenin Professor, Department of EEE, Prasad V.Potluri Siddhartha Institute of Technology, Kanuru, Vijayawada, Andhra Pradesh -520007, India

DOI:

https://doi.org/10.29121/granthaalayah.v6.i5.2018.1438

Keywords:

Genetic Algorithm, Particle Swarm, Optimal Reactive Power, Transmission Loss

Abstract [English]

In this paper Enriched Genetic Algorithm (EGA) is proposed to solve the optimal reactive power problem. In order to overcome the drawbacks of standard genetic algorithm (GA) and particle swarm optimization (PSO) algorithm, some improved mechanisms based on non-linear ranking selection, competition and selection among several crossover offspring and adaptive change of mutation scaling are adopted in the genetic algorithm, and dynamical parameters are adopted in PSO. The new population is produced through three approaches to improve the global optimization performance. Proposed algorithm has been tested in standard IEEE 57 bus test system and simulation results reveal the better performance of the proposed algorithm in reducing the real power loss

Downloads

Download data is not yet available.

References

O.Alsac,and B. Scott, “Optimal load flow with steady state security”,IEEE Transaction. PAS -1973, pp. 745-751. DOI: https://doi.org/10.1109/TPAS.1974.293972

Lee K Y ,Park Y M , Oritz J L –A united approach to optimal real and reactive power dispatch , IEEE Transactions on power Apparatus and systems 1985: PAS-104 : 1147-1153 DOI: https://doi.org/10.1109/TPAS.1985.323466

A.Monticelli , M .V.F Pereira ,and S. Granville , “Security constrained optimal power flow with post contingency corrective rescheduling” , IEEE Transactions on Power Systems :PWRS-2, No. 1, pp.175-182.,1987. DOI: https://doi.org/10.1109/TPWRS.1987.4335095

DeebN ,Shahidehpur S.M ,Linear reactive power optimization in a large power network using the decomposition approach. IEEE Transactions on power system 1990: 5(2) : 428-435 DOI: https://doi.org/10.1109/59.54549

E. Hobson ,’Network consrained reactive power control using linear programming, ‘ IEEE Transactions on power systems PAS -99 (4) ,pp 868=877, 1980 DOI: https://doi.org/10.1109/TPAS.1980.319715

K.Y Lee ,Y.M Park , and J.L Oritz, “Fuel –cost optimization for both real and reactive power dispatches” , IEE Proc; 131C,(3), pp.85-93. DOI: https://doi.org/10.1049/ip-c.1984.0012

M.K. Mangoli, and K.Y. Lee, “Optimal real and reactive power control using linear programming” , Electr.PowerSyst.Res, Vol.26, pp.1-10,1993. DOI: https://doi.org/10.1016/0378-7796(93)90063-K

C.A. Canizares , A.C.Z.de Souza and V.H. Quintana , “ Comparison of performance indices for detection of proximity to voltage collapse ,’’ vol. 11. no.3 , pp.1441-1450, Aug 1996 .

S.R.Paranjothi ,andK.Anburaja, “Optimal power flow using refined genetic algorithm”, Electr.PowerCompon.Syst , Vol. 30, 1055-1063,2002. DOI: https://doi.org/10.1080/15325000290085343

D. Devaraj, and B. Yeganarayana, “Genetic algorithm based optimal power flow for security enhancement”, IEE proc-Generation.Transmission and. Distribution; 152, 6 November 2005. DOI: https://doi.org/10.1049/ip-gtd:20045234

A.Berizzi, C. Bovo, M. Merlo, and M. Delfanti, “A ga approach to compare orpf objective functions including secondary voltage regulation,” Electric Power Systems Research, vol. 84, no. 1, pp. 187 – 194, 2012. DOI: https://doi.org/10.1016/j.epsr.2011.11.014

C.-F. Yang, G. G. Lai, C.-H. Lee, C.-T. Su, and G. W. Chang, “Optimal setting of reactive compensation devices with an improved voltage stability index for voltage stability enhancement,” International Journal of Electrical Power and Energy Systems, vol. 37, no. 1, pp. 50 – 57, 2012. DOI: https://doi.org/10.1016/j.ijepes.2011.12.003

P. Roy, S. Ghoshal, and S. Thakur, “Optimal var control for improvements in voltage profiles and for real power loss minimization using biogeography based optimization,” International Journal of Electrical Power and Energy Systems, vol. 43, no. 1, pp. 830 – 838, 2012. DOI: https://doi.org/10.1016/j.ijepes.2012.05.032

B. Venkatesh, G. Sadasivam, and M. Khan, “A new optimal reactive power scheduling method for loss minimization and voltage stability margin maximization using successive multi-objective fuzzy lp technique,” IEEE Transactions on Power Systems, vol. 15, no. 2, pp. 844 – 851, may 2000. DOI: https://doi.org/10.1109/59.867183

W. Yan, S. Lu, and D. Yu, “A novel optimal reactive power dispatch method based on an improved hybrid evolutionary programming technique,” IEEE Transactions on Power Systems, vol. 19, no. 2, pp. 913 – 918, may 2004. DOI: https://doi.org/10.1109/TPWRS.2004.826716

W. Yan, F. Liu, C. Chung, and K. Wong, “A hybrid genetic algorithminterior point method for optimal reactive power flow,” IEEE Transactions on Power Systems, vol. 21, no. 3, pp. 1163 –1169, aug. 2006.

J. Yu, W. Yan, W. Li, C. Chung, and K. Wong, “An unfixed piecewiseoptimal reactive power-flow model and its algorithm for ac-dc systems,” IEEE Transactions on Power Systems, vol. 23, no. 1, pp. 170 –176, feb. 2008. DOI: https://doi.org/10.1109/TPWRS.2007.907387

F. Capitanescu, “Assessing reactive power reserves with respect to operating constraints and voltage stability,” IEEE Transactions on Power Systems, vol. 26, no. 4, pp. 2224–2234, nov. 2011.

Z. Hu, X. Wang, and G. Taylor, “Stochastic optimal reactive power dispatch: Formulation and solution method,” International Journal of Electrical Power and Energy Systems, vol. 32, no. 6, pp. 615 – 621, 2010. DOI: https://doi.org/10.1016/j.ijepes.2009.11.018

A.Kargarian, M. Raoofat, and M. Mohammadi, “Probabilistic reactive power procurement in hybrid electricity markets with uncertain loads,” Electric Power Systems Research, vol. 82, no. 1, pp. 68 – 80, 2012. DOI: https://doi.org/10.1016/j.epsr.2011.08.019

Jin, N. and Y. Rahmat-Samii, “Advances in particle swarm optimization for antenna designs: Real-number, binary, singleobjective and multiobjective implementations,” IEEE Trans. Antennas Propagat., Vol. 55, 556–567, 2007. DOI: https://doi.org/10.1109/TAP.2007.891552

Lee, K. C. and J. Y. Jhang, “Application of particle swarm algorithm to the optimization of unequally spaced antenna arrays,” Journal ofEle ctromagnetic Waves and Applications, Vol. 20, 2001–2012, 2006. DOI: https://doi.org/10.1163/156939306779322747

Liu, X. F. Y. B. Chen, Y. C. Jiao, et al., “Modified particle swarm optimization of patch antenna design based on IE3D,” Journal of Electromagnetic Waves and Applications, Vol. 21, 1819–1828, 2007. DOI: https://doi.org/10.1163/156939307781891021

Robinson, J., S. Sinton, and Y. Rahmat-Samii, “Particle swarm, genetic algorithm, and their hybrids: Optimization of a profiled corrugated horn antenna,” IEEE International Symposium on Antennas Propagat., Vol. 1, 314–317, 2002.

Juang, C. F., “A hybrid of genetic algorithm and particle swarm optimization for recurrent netword design,” IEEE Trans. Syst., Man, Cybern. - Part B: Cybern., Vol. 34, 997–1006, 2004. DOI: https://doi.org/10.1109/TSMCB.2003.818557

Chaohua Dai, Weirong Chen, Yunfang Zhu, and Xuexia Zhang, “Seeker optimization algorithm for optimal reactive power dispatch,” IEEE Trans. Power Systems, Vol. 24, No. 3, August 2009, pp. 1218-1231. DOI: https://doi.org/10.1109/TPWRS.2009.2021226

J. R. Gomes and 0. R. Saavedra, “Optimal reactive power dispatch using evolutionary computation: Extended algorithms,” IEE Proc.-Gener. Transm. Distrib.. Vol. 146, No. 6. Nov. 1999. DOI: https://doi.org/10.1049/ip-gtd:19990683

Downloads

Published

2018-05-31

How to Cite

Lenin, K. (2018). A REDUCTION OF REAL POWER LOSS BY ENRICHED GENETIC ALGORITHM. International Journal of Research -GRANTHAALAYAH, 6(5), 167–176. https://doi.org/10.29121/granthaalayah.v6.i5.2018.1438

Most read articles by the same author(s)

1 2 3 4 5 6 7 > >>