REDUCTION OF ACTIVE POWER LOSS BY GROUP COMPETITION 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.v5.i11.2017.2352

Keywords:

Optimal Reactive Power, Transmission Loss, Group Competition, Optimization

Abstract [English]

This paper proposes Group Competition (GC) algorithm for solving optimal reactive power problem. Group Competition (GC) algorithm stimulated from the contest of sport teams in a sport group. A number of individuals as sport teams contend in a simulated group for numerous weeks. Based on the group schedule in every week, teams play in pairs and their game result is determined in terms of win or loss, given known the playing strength along with the teams’ planned formations. Modeling an artificial match analysis, each team devises a new playing strategy for the subsequent week competition and this procedure is repetitive for number of seasons. In order to evaluate the validity of the proposed Group Competition (GC) algorithm, it has been tested on Standard IEEE 57,118 bus systems and simulation results reveal about the good performance of the proposed algorithm in reducing real power loss and voltage profiles are within the limits.

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 ,Paru 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

Deeb N ,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.Power Syst.Res, Vol.26, pp.1-10,1993. DOI: https://doi.org/10.1016/0378-7796(93)90063-K

K.Anburaja, “Optimal power flow using refined genetic algorithm”, Electr.Power Compon.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

Husseinzadeh Kashan, “League Championship Algorithm: A new algorithm for numerical function optimization,” in Proceedings of the International Conference of Soft Computing and Pattern Recognition (SoCPaR 2009), IEEE Computer Society, pp. 43-48, 2009. DOI: https://doi.org/10.1109/SoCPaR.2009.21

http://en.wikipedia.org/wiki/ Sports_league.

http://www.talkfootball.co.uk/guides/football_formations.html.

E. Bruke, D. de Werra, and J Kingstone, “Colorings and related topics; Applications to timetabling,” in Handbook of Graph Theory, J. L. Gross, and J. Yellen, Ed. CRC PRESS, 2004.

Husseinzadeh Kashan, B. Karimi, and F. Jolai, “Effective hybrid genetic algorithm for minimizing makespan on a single-batchprocessing machine with non-identical job sizes,” Int J Prod Res, vol. 44, pp. 2337-2360, 2006.

K. Deb, “An efficient constraint handling method for genetic algorithms,” Comput Method Appl M, vol. 186, pp. 311–338, 2000. DOI: https://doi.org/10.1016/S0045-7825(99)00389-8

R. Monroy, G.Arroyo-Figueroa, L. E. Sucar, and H. Sossa, Eds. Heidelberg, Germany: Springer Verlag, lecture Notes in Artificial Intelligence No. 2972, pp. 707–716, 2004.

E. Mezura-Montes, J. Vel´azquez-Reyes, and C. A. C. Coello, “Promising Infeasibility and Multiple Offspring Incorporated to Differential Evolution for Constrained Optimization,” in Proceedings of the Genetic and Evolutionary Computation Conference (GECCO’2005), pp. 225–232, 2005. DOI: https://doi.org/10.1145/1068009.1068043

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

IEEE, “The IEEE 30-bus test system and the IEEE 118-test system”, (1993), http://www.ee.washington.edu/trsearch/pstca/.

Jiangtao Cao, Fuli Wang and Ping Li, “An Improved Biogeography-based Optimization Algorithm for Optimal Reactive Power Flow” International Journal of Control and Automation Vol.7, No.3 (2014), pp.161-176.

Downloads

Published

2017-11-30

How to Cite

Lenin, K. (2017). REDUCTION OF ACTIVE POWER LOSS BY GROUP COMPETITION ALGORITHM. International Journal of Research -GRANTHAALAYAH, 5(11), 260–270. https://doi.org/10.29121/granthaalayah.v5.i11.2017.2352

Most read articles by the same author(s)

<< < 1 2 3 4 5 6 7 > >>