DIMINUTION OF REAL POWER LOSS BY VALUE-ADDED BAT ALGORITHM

Authors

  • Dr.K.Lenin Researcher, Jawaharlal Nehru Technological University Kukatpally, Hyderabad 500 085, India

DOI:

https://doi.org/10.29121/granthaalayah.v5.i6.2017.2047

Keywords:

Value-Added Bat Algorithm, Chaotic Behaviour, Optimal Reactive Power, Transmission Loss

Abstract [English]

In this paper, a new Value-added Bat Algorithm (VBA) is proposed to solve reactive power problem. Echolocation is a significant feature of bat behavior and it produce a sound pulse and listens to the echo bouncing back from obstacles whilst flying. Projected VBA algorithm utilizes chaotic behaviour to produce a candidate solution in behaviours analogous to acoustic monophony.  Proposed VBA has been tested in Standard IEEE 118 bus system & practical 191 Indian utility system and simulation results show clearly the better performance of the proposed algorithm in decreasing the real power loss.

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

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

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

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

X.S. Yang. Bat algorithm for multi-objective optimisation. International Journal of Bio-Inspired Computation, 3(5):267– 274, 2011. DOI: https://doi.org/10.1504/IJBIC.2011.042259

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

X.S. Yang. Review of meta-heuristics and generalised evolutionary walk algorithm. International Journal of Bio-Inspired Computation, 3(2):77–84, 2011. DOI: https://doi.org/10.1504/IJBIC.2011.039907

L. M. Pecora and T. L. Carroll, "Synchronization in chaotic systems," Physical review letters, vol. 64, pp. 821-824, 1990. DOI: https://doi.org/10.1103/PhysRevLett.64.821

D. Yang, G. Li, and G. Cheng, "On the efficiency of chaos optimization algorithms for global optimization," Chaos, Solitons & Fractals, vol. 34, pp. 1366-1375, 2007.

A. H. Gandomi, G. J. Yun, X.-S. Yang, and S. Talatahari, "Chaos-enhanced accelerated particle swarm optimization," Communications in Nonlinear Science and Numerical Simulation, 2012. DOI: https://doi.org/10.1016/j.cnsns.2012.07.017

O. Abdel-Raouf, I. El-henawy and M. Abdel-Baset "chaotic Harmony Search Algorithm with Different Chaotic Maps for Solving Assignment Problems "International Journal of Computational Engineering & Management, Vol. 17, pp. 10-15 ,2014. DOI: https://doi.org/10.5120/15019-3307

W. Gong and S. Wang, "Chaos Ant Colony Optimization and Application," in Internet Computing for Science and Engineering (ICICSE), 2009 Fourth International Conference on, 2009, pp. 301-303. DOI: https://doi.org/10.1109/ICICSE.2009.38

B. Alatas, "Chaotic bee colony algorithms for global numerical optimization," Expert Systems with Applications, vol. 37, pp. 5682-5687, 2010.

A. Gandomi, X.-S. Yang, S. Talatahari, and A. Alavi, "Firefly algorithm with chaos," Communications in Nonlinear Science and Numerical Simulation, vol. 18, pp. 89-98, 2013. DOI: https://doi.org/10.1016/j.cnsns.2012.06.009

J. Mingjun and T. Huanwen, "Application of chaos in simulated annealing," Chaos, Solitons & Fractals, vol. 21, pp. 933-941, 2004. DOI: https://doi.org/10.1016/j.chaos.2003.12.032

L. d. S. Coelho and V. C. Mariani, "Use of chaotic sequences in a biologically inspired algorithm for engineering design optimization," Expert Systems with Applications, vol. 34, pp. 1905-1913, 2008.

He, Y.-Y., et al., Comparison of different chaotic maps in particle swarm optimization algorithm for long-term cascaded hydroelectric system scheduling," Chaos, Solitons and Fractals, Vol. 42, 3169-3176, 2009. DOI: https://doi.org/10.1016/j.chaos.2009.04.019

Lin, C. and Q.-Y. Feng, Chaotic particle swarm optimization algorithm based on the essence of particle swarm," Journal of Southwest Jiaotong University, Vol. 42, 665-669, 2007.

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.

Downloads

Published

2017-06-30

How to Cite

Lenin, K. (2017). DIMINUTION OF REAL POWER LOSS BY VALUE-ADDED BAT ALGORITHM. International Journal of Research -GRANTHAALAYAH, 5(6), 378–388. https://doi.org/10.29121/granthaalayah.v5.i6.2017.2047

Most read articles by the same author(s)

1 2 3 4 5 6 7 > >>