LESSENING OF ACTUAL POWER LOSS BY MODIFIED ALGORITHM

Authors

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

DOI:

https://doi.org/10.29121/granthaalayah.v6.i8.2018.1418

Keywords:

Optimal Reactive Power, Transmission Loss, Modified Teaching Learning

Abstract [English]

This paper presents a Modified Teaching-Learning-Based Optimization (MTLBO) algorithm for solving reactive power flow problem. Basic Teaching-Learning-Based Optimization (TLBO) is reliable, accurate and vigorous for solving the optimization problems. Also, it has been found that TLBO algorithm slow in convergence due to its high concentration in the accuracy. This paper presents an, Modified version of TLBO algorithm, called as Modified Teaching-Learning-Based Optimization (MTLBO). A parameter called as “weight” has been included in the fundamental TLBO equations & subsequently it increases the rate of convergence. In order to evaluate the proposed algorithm, it has been tested in practical 191 test bus system. Simulation results reveal about the better performance of the proposed algorithm in reducing the real power loss & 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

R. V. Rao, V. J. Savsani and D. P. Vakharia, “Teaching- Learning-Based Optimization: A Novel Method for Con- strained Mechanical Design Optimization Problems,” Computer-Aided Design, Vol. 43, No. 1, 2011, pp. 303- 315. doi:10.1016/j.cad.2010.12.015 . DOI: https://doi.org/10.1016/j.cad.2010.12.015

R. V. Rao, V. J. Savsani and D. P. Vakharia, “Teach- ing-Learning-Based Optimization: An Optimization Me- thod for Continuous Non-Linear Large Scale Problems,” INS 9211 No. of Pages 15, Model 3G 26 August 2011.

R. V. Rao, V. J. Savsani and J. Balic, “Teaching Learning Based Optimization Algorithm for Constrained and Un- constrained Real Parameter Optimization Problems,” En- gineering Optimization, Vol. 44, No. 12, 2012, pp. 1447- 1462. doi:10.1080/0305215X.2011.652103. DOI: https://doi.org/10.1080/0305215X.2011.652103

R. V. Rao and V. J. Savsani, “Mechanical Design Opti- mization Using Advanced Optimization Techniques,” Springer-Verlag, London, 2012. doi:10.1007/978-1-4471-2748-2 DOI: https://doi.org/10.1007/978-1-4471-2748-2

V. Toğan, “Design of Planar Steel Frames Using Teach- ing-Learning Based Optimization,” Engineering Struc- tures, Vol. 34, 2012, pp. 225-232. doi:10.1016/j.engstruct.2011.08.035 DOI: https://doi.org/10.1016/j.engstruct.2011.08.035

R. V. Rao and V. D. Kalyankar, “Parameter Optimization of Machining Processes Using a New Optimization Algo- rithm,” Materials and Manufacturing Processes, Vol. 27, No. 9, 2011, pp. 978-985. doi:10.1080/10426914.2011.602792. DOI: https://doi.org/10.1080/10426914.2011.602792

S. C. Satapathy and A. Naik, “Data Clustering Based on Teaching-Learning-Based Optimization. Swarm, Evolu- tionary, and Memetic Computing,” Lecture Notes in Com- puter Science, Vol. 7077, 2011, pp. 148-156, doi:10.1007/978-3-642-27242-4_18. DOI: https://doi.org/10.1007/978-3-642-27242-4_18

Downloads

Published

2018-08-31

How to Cite

Lenin, K. (2018). LESSENING OF ACTUAL POWER LOSS BY MODIFIED ALGORITHM. International Journal of Research -GRANTHAALAYAH, 6(8), 159–167. https://doi.org/10.29121/granthaalayah.v6.i8.2018.1418

Most read articles by the same author(s)

1 2 3 4 5 6 7 > >>