REAL POWER LOSS MINIMIZATION AND MAXIMIZATION OF STATIC VOLTAGE STABILITY MARGIN BY HYBRIDIZED 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.i7.2017.2159

Keywords:

Modal Analysis, Optimal Reactive Power, Transmission Loss, Hybridized Algorithm

Abstract [English]

This paper presents a new Hybridized Algorithm (HA) for solving the multi-objective reactive power dispatch problem. Inspired by Genetic Algorithm (GA), Particle Swarm Optimization (PSO) & the Bat Algorithm (BA), the HA was designed to retain some advantages of each method to improve the exploration and exploitation of the search. Scrutinizing PSO and BA reveals some differences, in that BA rejects the historical experience of each individual’s own position but admits an improved personal solution with some probability. We will adjust some of the updating mechanisms of BA and add a mutation method in order to try to solve reactive power problem more accurately. Proposed (HA) algorithm has been tested on standard IEEE 30 bus test system and simulation results shows clearly about the good performance of the proposed algorithm.

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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

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

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 .

Berizzi.C.Bovo,M.Merlo,andM.Delfanti,(2012), “A GA approach to compare ORPF objective functions including secondary voltage regulation,” Electric Power Systems Research, vol. 84, no. 1, pp. 187 – 194.

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

J. H. Holland. “Outline for a logical theory of adaptive systems”. Journal of the ACM, 3:297–314, 1962. DOI: https://doi.org/10.1145/321127.321128

Talbi, El-Ghazali. “Metaheuristics: from design to implementation”. Vol. 74. John Wiley & Sons, 2009. DOI: https://doi.org/10.1002/9780470496916

Bansal, J. C. et al. “Information Sharing Strategy among Particles in Particle Swarm Optimization Using Laplacian Operator”, Swarm Intelligence Symposium, 2009. IEEE, pages 30-36. DOI: https://doi.org/10.1109/SIS.2009.4937841

Wright, “A. Genetic Algorithms for Real Parameter Optimization, Foundations of Genetic Algorithms”, G. Rswlins(Ed.), Morgen Kaufmann publishers, CA, 1991, pp. 205-218. DOI: https://doi.org/10.1016/B978-0-08-050684-5.50016-1

Yu-hui Shi and Russell Eberhart,” A modified particle swarm optimizer,” in proceedings of IEEE world Congress on Computation intelligence,pp.69-73,1998.

Takahashi, Masato, and Hajime Kita. “A crossover operator using independent component analysis for real-coded genetic algorithms." Evolutionary Computation, 2001. Proceedings of the 2001 Congress on. Vol. 1. IEEE, 2001.

Zhi-Feng Hao,Zhi-Gang Wang,HanHuang,A Particle Swarm Optimization Algorithm With Crossover Operator Proceedings of the 6th international conference on Machine Learning and Cybernatics ,Hong Kong ,19-22 August 2007.

Chen, Stephen. "Particle swarm optimization with pbest crossover."Evolutionary Computation (CEC), 2012 IEEE Congress on. IEEE, 2012[23] DOI: https://doi.org/10.1109/CEC.2012.6256497

X.S. Yang. A new metaheuristic bat-inspired algorithm. Nature Inspired Cooperative Strategies for Optimization (NICSO 2010), pages 65–74, 2010. DOI: https://doi.org/10.1007/978-3-642-12538-6_6

A.H. Gandomi, X.S. Yang, A.H. Alavi, and S. Talatahari. Bat algorithm for constrained optimization tasks. Neural Computing & Applications, pages 1–17, 2012. DOI: https://doi.org/10.1007/s00521-012-1028-9

P.W. Tsai, J.S. Pan, B.Y. Liao, M.J. Tsai, and V. Istanda. Bat algorithm inspired algorithm for solving numerical optimization problems. Applied Mechanics and Materials, 148:134–137,2012. DOI: https://doi.org/10.4028/www.scientific.net/AMM.148-149.134

Wu Q H, Ma J T. “Power system optimal reactive power dispatch using evolutionary programming”, IEEE Transactions on power systems 1995; 10(3): 1243-1248 . DOI: https://doi.org/10.1109/59.466531

S.Durairaj, D.Devaraj, P.S.Kannan ,“Genetic algorithm applications to optimal reactive power dispatch with voltage stability enhancement”, IE(I) Journal-EL Vol 87,September 2006.

D.Devaraj , “Improved genetic algorithm for multi – objective reactive power dispatch problem”, European Transactions on electrical power 2007 ; 17: 569-581. DOI: https://doi.org/10.1002/etep.146

P. Aruna Jeyanthy and Dr. D. Devaraj “Optimal Reactive Power Dispatch for Voltage Stability Enhancement Using Real Coded Genetic Algorithm”, International Journal of Computer and Electrical Engineering, Vol. 2, No. 4, August, 2010 1793-8163. DOI: https://doi.org/10.7763/IJCEE.2010.V2.220

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Published

2017-07-31

How to Cite

Lenin, K. (2017). REAL POWER LOSS MINIMIZATION AND MAXIMIZATION OF STATIC VOLTAGE STABILITY MARGIN BY HYBRIDIZED ALGORITHM. International Journal of Research -GRANTHAALAYAH, 5(7), 506–519. https://doi.org/10.29121/granthaalayah.v5.i7.2017.2159

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