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



Nelder-Mead Algorithm, Simulated Annealing, Optimal Reactive Power, Transmission Loss

Abstract [English]

This paper presents Hybridization of Simulated Annealing with Nelder-Mead algorithm (SN) is proposed to solve optimal reactive power problem. The proposed Hybridized - Simulated Annealing, Nelder-Mead algorithm starts with a prime solution, which is produced arbitrarily and then the solution is disturbed into partitions. The vicinity zone is created, arbitrary numbers of partitions are selected and variables modernizing procedure is started in order to create a trail of neighbour solutions. This procedure helps the SN algorithm to explore the region around an existing iterate solution. The Nelder- Mead algorithm is used in the last stage in order to progress the most excellent solution found so far and hasten the convergence in the closing stage. The proposed Hybridization of Simulated Annealing with Nelder-Mead algorithm (SN) has been tested in standard IEEE 57,118 bus systems and simulation results show the superior performance of the proposed SN algorithm in reducing the real power loss and voltage profiles are within the limits.


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O. Alsac, B. Scott, “Optimal load flow with steady state security”, IEEE Transaction. PAS -1973, pp. 745-751. DOI:

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:

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:

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:

E. Hobson,’ Network consrained reactive power control using linear programming, ‘IEEE Transactions on power systems PAS -99 (4), pp 868-877, 1980 DOI:

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:

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:

Berizzi. C. Bovo, M. Merlo, and M. 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. DOI:

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:

C.A. Canizares, 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. Kirkpatrick, C. Gelatt, M. Vecchi. "Optimization by simulated annealing", Science,220(4598):671-680, 1983. doi: 10.1016/s0736-5845(02)00013-3. DOI:

V. Cerny. "A thermodynamical approach to the traveling salesman problem". An efficient simulation algorithm, Journal of Optimization Theory and Applications,45:41-51, 1985. doi: 10.1007/bf00940812. DOI:

E. Cosola, K. Genovese, L. Lamberti, C. Pappalettere, A general framework for identification of hyper-elastic membranes with moiré techniques and multi-point simulated annealing, International Journal of Solids and Structures, 45 (2008) 6074-6099.

E.W. McGookin, D.J. Murray-Smith, Submarine manoeuvring controllers' optimisation using simulated annealing and genetic algorithms, Control Engineering Practice, 14 (2006) 1-15.

J. Nelder, R. Mead, " Asimplex method for function minimization", Computer journal, 7:308-313, 1965. doi: 10.1093/comjnl/7.4.308. DOI:

Ahmed Fouad Ali , “Hybrid Simulated Annealing And Nelder-Mead Algorithm For Solving Large-Scale Global Optimization Problems”, International Journal of Research in Computer Science eISSN 2249-8265 Volume 4 Issue 3 (2014) pp. 1-11.

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:

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:

IEEE, “The IEEE 30-bus test system and the IEEE 118-test system”, (1993),

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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