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




Particle Swarm Optimization, Polar, Optimal Reactive Power, Transmission Loss

Abstract [English]

This paper presents Polar Particle Swarm optimization (PPSO) algorithm for solving optimal reactive power problem. The standard Particle Swarm Optimization (PSO) algorithm is an innovative evolutionary algorithm in which each particle studies its own previous best solution and the group’s previous best to optimize problems. In the proposed PPSO algorithm that enhances the behaviour of PSO and avoids the local minima problem by using a polar function to search for more points in the search space in order to evaluate the efficiency of proposed algorithm, it has been tested on IEEE 30 bus system and compared to other algorithms. Simulation results demonstrate good performance of the Polar Particle Swarm optimization (PPSO) algorithm in solving an optimal reactive power problem.


Download data is not yet available.


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 .

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

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 piecewise optimal 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. Kennedy and R. Eberhart, “Particle Swarm Optimization,” Proc. Proceedings of the IEEE International Conference on Neural Networks,Perth, Australia, IEEE Service Center, Vol. 4. Piscataway, NJ, 1995, pp.1942C1948.

R.C.Eberhart and J.Kennedy, “A new optimizer using particle swarmtheory,” Proc. Proceedings of the 6th Int. Symp. Mcro Machine Human Science, Nagoya, Japan, 1995, pp. 39 - 43.

R.C.Eberhart and Y.Shi, “Particle Swarm Optimization: developments, applications and resourses,” Proc. Proceedings of the IIEEE Congresson Evolutionary Computation, Seoul, South Korea, Vol. 1, 2001, pp. 81- 86.

H. W. Ge, Y. C. Liang, Y. Zhou, X. C. Guo, “A Particle SwarmOptimization-based Algorithm for Job-shop Scheduling Problem,” International Journal of Computational Methods, vol. 2, no. 3, 2005, pp.419-430.

Y.Tan and Z.M.Xiao, “Clonal particle swarm optimization and itsapplications,” Proc. Proceedings of the IEEE Congress on Evolutionary Computation, Singapore, 2007, pp. 2303 - 2309. DOI: https://doi.org/10.1109/CEC.2007.4424758

Boyer, C. B. (1949). Newton as an originator of polar coordinates. The American Mathematical Monthly, 56(2),73-78.

Campos, M., Bonabeau, E., Theraulaz, G., & Deneubourg, J. L. (2000). Dynamic scheduling and division oflabor in social insects. Adaptive Behavior, 8(2), 83-95. DOI: https://doi.org/10.1177/105971230000800201

Clerc, M. (2012). Standard particle swarm optimisation.

Coolidge, J. L. (1952). The origin of polar coordinates. The American Mathematical Monthly, 59(2), 78-85. DOI: https://doi.org/10.1080/00029890.1952.11988074

Wu.Q.H,Y.J.Cao,andJ.Y.Wen,(1998),“Optimal reactive power dispatch using an adaptive genetic algorithm”, Int.J.Elect.Power Energy Syst. Vol 20. Pp. 563-569.

Zhao.B,C.X.Guo,andY.J.CAO,(2005),“Multiagent-based particle swarm optimization approach for optimal reactive power dispatch”, IEEE Trans. Power Syst. Vol. 20, no. 2, pp. 1070-1078. DOI: https://doi.org/10.1109/TPWRS.2005.846064

Mahadevan.K,KannanP.S,(2010)“Comprehensive Learning Particle Swarm Optimization for Reactive Power Dispatch”, Applied Soft Computing, Vol. 10, No. 2, pp. 641–52. DOI: https://doi.org/10.1016/j.asoc.2009.08.038

Khazali.A.H,M.Kalantar,(2011),“Optimal Reactive Power Dispatch based on Harmony Search Algorithm”, Electrical Power and Energy Systems, Vol. 33, No. 3, pp. 684–692. DOI: https://doi.org/10.1016/j.ijepes.2010.11.018

Sakthivel.S,M.Gayathri,V.Manimozhi,(2013),“A Nature Inspired Optimization Algorithm for Reactive Power Control in a Power System”,

International Journal of Recent Technology and Engineering, pp29-33Vol.2, Issue-1.

Tejaswini Sharma, Laxmi Srivastava,Shishir Dixit (2016). “Modified Cuckoo Search Algorithm For Optimal Reactive Power Dispatch”, Proceedings of 38 th IRF International Conference, pp4-8. 20th March, 2016, Chennai, India, ISBN: 978-93-85973-76-5.




How to Cite

Lenin, K. (2018). POLAR PARTICLE SWARM OPTIMIZATION ALGORITHM FOR SOLVING OPTIMAL REACTIVE POWER PROBLEM. International Journal of Research -GRANTHAALAYAH, 6(6), 335–345. https://doi.org/10.29121/granthaalayah.v6.i6.2018.1378

Most read articles by the same author(s)

1 2 3 4 5 6 7 > >>