ENHANCED MINE BLAST ALGORITHM FOR SOLVING REACTIVE POWER PROBLEM

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.i9.2017.2232

Keywords:

Enhanced Mine Blast Algorithm, Optimal Reactive Power, Transmission Loss

Abstract [English]

In this paper Enhanced Mine Blast (EMB) algorithm which based on mine bomb explosion concept is proposed to solve optimal reactive power problem.The clue of the projected Enhanced Mine Blast (EMB) algorithm is based on the examination of a mine bomb explosion, in which the thrown pieces of shrapnel crash with other mine bombs near the explosion area resulting in their explosion. In this paper convergence speed has been enhanced. Proposed Enhanced Mine Blast (EMB) algorithm has been tested in standard IEEE 118 & practical 191 bus test systems and simulation results show clearly the superior performance of the projected Enhanced Mine Blast (EMB) algorithm in reducing the real power loss.

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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

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 .

K.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

A. Sadollah, A. Bahreininejad, H. Eskandar, M. Hamdi, Mine blast algorithm foroptimization of truss structures with discrete variables, Computers & Structures102–103 (2012) 49–63. DOI: https://doi.org/10.1016/j.compstruc.2012.03.013

Ali Sadollaha, ArdeshirBahreininejada, HadiEskandarb, MohdHamdia,Mine blast algorithm: A new population based algorithm for solving constrained engineering optimization problems,Applied Soft Computing 13 (2013) 2592–2612.

E.M. Montes, C.A.C. Coello, An empirical study about the usefulness of evolution strategies to solve constrained optimization problems, International Journal ofGeneral Systems 37 (2008) 443–473. DOI: https://doi.org/10.1080/03081070701303470

A. Kaveh, S. Talatahari, A particle swarm ant colony optimization for truss structures with discrete variables, Journal of Constructional Steel Research 65 (2009)1558–1568. DOI: https://doi.org/10.1016/j.jcsr.2009.04.021

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.

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Published

2017-09-30

How to Cite

Lenin, K. (2017). ENHANCED MINE BLAST ALGORITHM FOR SOLVING REACTIVE POWER PROBLEM. International Journal of Research -GRANTHAALAYAH, 5(9), 206–216. https://doi.org/10.29121/granthaalayah.v5.i9.2017.2232

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