Research Article
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Year 2018, Volume: 31 Issue: 4, 1107 - 1121, 01.12.2018

Abstract

References

  • [1] Sreejith, S. Sishaj P Simon. and Selvan,M.P., “Performance Comparison of FACTS Devices For Steady State Power Flow Control” , International Review on Modeling and Simulations , pp: 576-587 Vol:5, April (2012).
  • [2]. Sreejith, S. Sishaj P Simon. and Selvan,M.P., “Optimal Location of Interline Power Flow Controller in a Power System Network using DE Algorithm”, International Review on Modeling and Simulations , pp: 690-701 Vol:5, April,( 2012).
  • [3].Dommel, H.W., Tinney, W.F., “Optimal power flow solutions”, IEEE, Trans. On power Apparatus and Systems, ,pp.1866-1876. VOL. PAS-87, October (1968).
  • [4] Lee, K., Park, Y., and Ortiz, J. A., “United approach to optimal real and reactive power dispatch”, IEEE Trans Power Appar. Syst. pp 1147-53.104(5) (1985).
  • [5] Sun,D.I., Ashley, B., Brewar., A., Hughes, W.F., and Tinny, “Optimal power flow by Newton approach”, IEEE Trans. Power Appar. syst. pp 2864–2880. 103 (1984).
  • [6]. Quintana, V.H., Santos-Nieto,M., “Reactive-power dispatch by successive quadratic programming”, IEEE Trans. Energy Conv. pp 425–435. 4 (1989).
  • [7]. Deeb, NI, Shahidehpour, SM., “An efficient technique for reactive power dispatch using a revised linear programming approach”, Electric Power System Research pp 5:121–34. 15: (1988).
  • [8]. Granville,S., “Optimal reactive power dispatch through interior point methods”, IEEE Trans. Power Syst. pp 136–146. 9 (1994).
  • [9] Subbaraj,P., Rajnarayanan, P.N., “Optimal reactive power dispatch using self-adaptive real coded genetic algorithm” Electric Power System Research pp 374-381. 79 (2009).
  • [10]. Haibo Zhang, Lizi Zhang, and Fanling Meng, “Reactive power Optimization Based on Genetic Algorithm”, Power System Technology, 1998.Proceedings. pp 1448-1453 POWERCON ’(1998).
  • [11]. Subbaraj, P., Rajnarayanan, P.N., “Optimal reactive power dispatch by particle swarm optimization with Cauchy and adaptive mutations”, In: Recent trends in information, telecommunication and computing (ITC), IEEE international conference.. pp 110-115 (2010).
  • [12].Hirotaka Yoshida, Kenichi Kawata, and Yoshikazu Fukuyama, Member, IEEE, Shinichi Takayama, and Yosuke Nakanishi, Member, IEEE A “Particle Swarm Optimization for Reactive Power and Voltage Control Considering Voltage Security Assessment” IEEE TRANSACTIONS ON POWER SYSTEMS, VOL. 15, NO. 4, pp 1232-1239 NOVEMBER( 2000).
  • [13]. Abido, M.A., “Optimal power flow using particle swarm optimization”, J. Electr. Power Energy Syst. 24 pp 563–571.(2002).
  • [14]. Liang, C.H., Chung,C.Y., Wong,K.P., Duan, X.Z., and Tse, C.T., “Study of differential evolution for optimal reactive power flow”, IET Gen. Transm. Disrib.1 pp 253–260. (2007).
  • [15]. M.Varadarajan, K.S.Swarup “Differential evolutionary algorithm for optimal reactive power dispatch” Electrical power and Energy Systems 30 pp 435-441.(2008).
  • [16].Varadarajan, M., Swarup, K.S., “Differential evolution approach for optimal reactive power dispatch”, Appl Soft Comput pp 1549-1561 8(4) (2008).
  • [17] Chung, C.Y., et al. “Hybrid algorithm of differential evolution and evolutionary programming for optimal reactive power flow”, IET Gener Transm Distrib. pp 4(1); 84-934(1): (2010).
  • [18] Liang C.H., Chung, C.Y., Wong, K.P., and Duan, X.Z., “Comparison and improvement of evolutionary programming techniques for power system optimal reactive power flow”, IET Gener Transm Distrib IEE Proc . 153(2): pp 228-36 (2006).
  • [19]..Ionescu,C.F., Eremia,M., Senior member IEEE, Bulac,C., Member IEEE “Reactive Power Optimization using Evolutionary Techniques: Differential Evolution and Particle Swarm.” Intelligent System Application to Power System ( ISAP), 16th International Conference on 25-28 Sept pp 1-5 (2011).
  • [20]. El Ela, A., Abido, M.A., and Spea, S.R., “Differential evolution algorithm for optimal reactive power dispatch”, Electric Power System Research. pp: 458–64. 81 (2011).
  • [21] Yocef Amrane, Mohamed Boudour, Ahmed Amine Ladjici, and Ali Elmaouhab, “Optimal VAR control for real power loss minimization using differential evolution algorithm”, Electrical Power and Energy System.pp 262-271 66 (2015).
  • [22]. Ayana, K., Kılıc, U., “Artificial bee colony algorithm solution for optimal reactive power flow”, Appl Soft Comput. pp 1477–82. (2012).
  • [23]. Li Yuancheng, Wang Yiliang, and Bin Li, “A hybrid artificial bee colony assisted differential evolution algorithm for optimal reactive power flow”, Int J Electrical Power Energy System pp 25-33 : 52 (2013).
  • [24]Duman, S.,Sonmez,Y., Guvenc, U., and Yorukeren,N., “Optimal reactive power dispatch using a gravitional search algorithm” IET Gener.Transm.Distrib.,vol-8 Iss,6,pp563-576 (2012).
  • [25]. Kanagasabai Lenin, Bhumanapally Ravindhranath Reddy, and Mungala Suryakalavathi, “Hybrid Tabu search-simulated annealing method to solve optimal reactive power problem” Electrical Power and Energy Systems pp 87-9182 (2016).
  • [26] Suliaman,M.H., Mohd Rashid,M.I., Aliman,O., Mohammed,M.R., Ahamad,A.Z., and Bakar, M.S., “Loss minimization by Optimal reactive power dispatch using Cuckoo search Algorithm” 3rd IET International Conference on Clean Energy and Technology (CEAT) DOI:10.1049/CP.2014.1479 (2014).
  • [27]. Power system case archive. Available at http:// www.ee.washington.edu / research / pstca /
  • [28]. Mirjalili,S., "Dragonfly Algorithm: A New Meta-heuristic Optimization Technique for Solving Single-objective, Discrete, and Multi-objective Problems", Neural Computing and Applications, in press, DOI: http://dx.doi.org/10.1007/s00521-015-1920-1 (2015) .
  • [29] Pandya , S., “Optimal Reactive Power Dispatch ( ORPD) Using Particle Swarm Optimization (PSO)”, ( email: kartikpandya.ee@ecchanga.ac.in)
  • [30]. Wood, A.J., Wallenberg, B.F., : “Power generation operation and control”, (John Wiley & Sons, Inc., New York, 1996, 2nd edn.)
  • [31].Saadat H. Power system analysis. 2nd ed. New York: McGraw-Hill; 2004.

A New Meta Heuristic Dragonfly Optimizaion Algorithm for Optimal Reactive Power Dispatch Problem

Year 2018, Volume: 31 Issue: 4, 1107 - 1121, 01.12.2018

Abstract

This research accesses a novel approach of
utilising an advanced Meta–heuristic Optimization technique with a single
objective to pledge with optimal reactive power dispatch problem in electrical
power system network. The prime focus of reactive power dispatch is to curtail
the total active power loss in transmission lines.  In this detailed study, the dragonfly
algorithm was realized on standard IEEE-14 bus and 30 bus systems. The outcome
of dragonfly algorithm lucidly indicate the capablity of increasing the
antecedent random population size for a liable global optimization problem,
focalized close to the global optimum and contributing precise outcome results
related to another popular algorithm.  

References

  • [1] Sreejith, S. Sishaj P Simon. and Selvan,M.P., “Performance Comparison of FACTS Devices For Steady State Power Flow Control” , International Review on Modeling and Simulations , pp: 576-587 Vol:5, April (2012).
  • [2]. Sreejith, S. Sishaj P Simon. and Selvan,M.P., “Optimal Location of Interline Power Flow Controller in a Power System Network using DE Algorithm”, International Review on Modeling and Simulations , pp: 690-701 Vol:5, April,( 2012).
  • [3].Dommel, H.W., Tinney, W.F., “Optimal power flow solutions”, IEEE, Trans. On power Apparatus and Systems, ,pp.1866-1876. VOL. PAS-87, October (1968).
  • [4] Lee, K., Park, Y., and Ortiz, J. A., “United approach to optimal real and reactive power dispatch”, IEEE Trans Power Appar. Syst. pp 1147-53.104(5) (1985).
  • [5] Sun,D.I., Ashley, B., Brewar., A., Hughes, W.F., and Tinny, “Optimal power flow by Newton approach”, IEEE Trans. Power Appar. syst. pp 2864–2880. 103 (1984).
  • [6]. Quintana, V.H., Santos-Nieto,M., “Reactive-power dispatch by successive quadratic programming”, IEEE Trans. Energy Conv. pp 425–435. 4 (1989).
  • [7]. Deeb, NI, Shahidehpour, SM., “An efficient technique for reactive power dispatch using a revised linear programming approach”, Electric Power System Research pp 5:121–34. 15: (1988).
  • [8]. Granville,S., “Optimal reactive power dispatch through interior point methods”, IEEE Trans. Power Syst. pp 136–146. 9 (1994).
  • [9] Subbaraj,P., Rajnarayanan, P.N., “Optimal reactive power dispatch using self-adaptive real coded genetic algorithm” Electric Power System Research pp 374-381. 79 (2009).
  • [10]. Haibo Zhang, Lizi Zhang, and Fanling Meng, “Reactive power Optimization Based on Genetic Algorithm”, Power System Technology, 1998.Proceedings. pp 1448-1453 POWERCON ’(1998).
  • [11]. Subbaraj, P., Rajnarayanan, P.N., “Optimal reactive power dispatch by particle swarm optimization with Cauchy and adaptive mutations”, In: Recent trends in information, telecommunication and computing (ITC), IEEE international conference.. pp 110-115 (2010).
  • [12].Hirotaka Yoshida, Kenichi Kawata, and Yoshikazu Fukuyama, Member, IEEE, Shinichi Takayama, and Yosuke Nakanishi, Member, IEEE A “Particle Swarm Optimization for Reactive Power and Voltage Control Considering Voltage Security Assessment” IEEE TRANSACTIONS ON POWER SYSTEMS, VOL. 15, NO. 4, pp 1232-1239 NOVEMBER( 2000).
  • [13]. Abido, M.A., “Optimal power flow using particle swarm optimization”, J. Electr. Power Energy Syst. 24 pp 563–571.(2002).
  • [14]. Liang, C.H., Chung,C.Y., Wong,K.P., Duan, X.Z., and Tse, C.T., “Study of differential evolution for optimal reactive power flow”, IET Gen. Transm. Disrib.1 pp 253–260. (2007).
  • [15]. M.Varadarajan, K.S.Swarup “Differential evolutionary algorithm for optimal reactive power dispatch” Electrical power and Energy Systems 30 pp 435-441.(2008).
  • [16].Varadarajan, M., Swarup, K.S., “Differential evolution approach for optimal reactive power dispatch”, Appl Soft Comput pp 1549-1561 8(4) (2008).
  • [17] Chung, C.Y., et al. “Hybrid algorithm of differential evolution and evolutionary programming for optimal reactive power flow”, IET Gener Transm Distrib. pp 4(1); 84-934(1): (2010).
  • [18] Liang C.H., Chung, C.Y., Wong, K.P., and Duan, X.Z., “Comparison and improvement of evolutionary programming techniques for power system optimal reactive power flow”, IET Gener Transm Distrib IEE Proc . 153(2): pp 228-36 (2006).
  • [19]..Ionescu,C.F., Eremia,M., Senior member IEEE, Bulac,C., Member IEEE “Reactive Power Optimization using Evolutionary Techniques: Differential Evolution and Particle Swarm.” Intelligent System Application to Power System ( ISAP), 16th International Conference on 25-28 Sept pp 1-5 (2011).
  • [20]. El Ela, A., Abido, M.A., and Spea, S.R., “Differential evolution algorithm for optimal reactive power dispatch”, Electric Power System Research. pp: 458–64. 81 (2011).
  • [21] Yocef Amrane, Mohamed Boudour, Ahmed Amine Ladjici, and Ali Elmaouhab, “Optimal VAR control for real power loss minimization using differential evolution algorithm”, Electrical Power and Energy System.pp 262-271 66 (2015).
  • [22]. Ayana, K., Kılıc, U., “Artificial bee colony algorithm solution for optimal reactive power flow”, Appl Soft Comput. pp 1477–82. (2012).
  • [23]. Li Yuancheng, Wang Yiliang, and Bin Li, “A hybrid artificial bee colony assisted differential evolution algorithm for optimal reactive power flow”, Int J Electrical Power Energy System pp 25-33 : 52 (2013).
  • [24]Duman, S.,Sonmez,Y., Guvenc, U., and Yorukeren,N., “Optimal reactive power dispatch using a gravitional search algorithm” IET Gener.Transm.Distrib.,vol-8 Iss,6,pp563-576 (2012).
  • [25]. Kanagasabai Lenin, Bhumanapally Ravindhranath Reddy, and Mungala Suryakalavathi, “Hybrid Tabu search-simulated annealing method to solve optimal reactive power problem” Electrical Power and Energy Systems pp 87-9182 (2016).
  • [26] Suliaman,M.H., Mohd Rashid,M.I., Aliman,O., Mohammed,M.R., Ahamad,A.Z., and Bakar, M.S., “Loss minimization by Optimal reactive power dispatch using Cuckoo search Algorithm” 3rd IET International Conference on Clean Energy and Technology (CEAT) DOI:10.1049/CP.2014.1479 (2014).
  • [27]. Power system case archive. Available at http:// www.ee.washington.edu / research / pstca /
  • [28]. Mirjalili,S., "Dragonfly Algorithm: A New Meta-heuristic Optimization Technique for Solving Single-objective, Discrete, and Multi-objective Problems", Neural Computing and Applications, in press, DOI: http://dx.doi.org/10.1007/s00521-015-1920-1 (2015) .
  • [29] Pandya , S., “Optimal Reactive Power Dispatch ( ORPD) Using Particle Swarm Optimization (PSO)”, ( email: kartikpandya.ee@ecchanga.ac.in)
  • [30]. Wood, A.J., Wallenberg, B.F., : “Power generation operation and control”, (John Wiley & Sons, Inc., New York, 1996, 2nd edn.)
  • [31].Saadat H. Power system analysis. 2nd ed. New York: McGraw-Hill; 2004.
There are 31 citations in total.

Details

Primary Language English
Subjects Engineering
Journal Section Electrical & Electronics Engineering
Authors

Anbarasan Palappan

Jayabarathi Thangavelu This is me

Publication Date December 1, 2018
Published in Issue Year 2018 Volume: 31 Issue: 4

Cite

APA Palappan, A., & Thangavelu, J. (2018). A New Meta Heuristic Dragonfly Optimizaion Algorithm for Optimal Reactive Power Dispatch Problem. Gazi University Journal of Science, 31(4), 1107-1121.
AMA Palappan A, Thangavelu J. A New Meta Heuristic Dragonfly Optimizaion Algorithm for Optimal Reactive Power Dispatch Problem. Gazi University Journal of Science. December 2018;31(4):1107-1121.
Chicago Palappan, Anbarasan, and Jayabarathi Thangavelu. “A New Meta Heuristic Dragonfly Optimizaion Algorithm for Optimal Reactive Power Dispatch Problem”. Gazi University Journal of Science 31, no. 4 (December 2018): 1107-21.
EndNote Palappan A, Thangavelu J (December 1, 2018) A New Meta Heuristic Dragonfly Optimizaion Algorithm for Optimal Reactive Power Dispatch Problem. Gazi University Journal of Science 31 4 1107–1121.
IEEE A. Palappan and J. Thangavelu, “A New Meta Heuristic Dragonfly Optimizaion Algorithm for Optimal Reactive Power Dispatch Problem”, Gazi University Journal of Science, vol. 31, no. 4, pp. 1107–1121, 2018.
ISNAD Palappan, Anbarasan - Thangavelu, Jayabarathi. “A New Meta Heuristic Dragonfly Optimizaion Algorithm for Optimal Reactive Power Dispatch Problem”. Gazi University Journal of Science 31/4 (December 2018), 1107-1121.
JAMA Palappan A, Thangavelu J. A New Meta Heuristic Dragonfly Optimizaion Algorithm for Optimal Reactive Power Dispatch Problem. Gazi University Journal of Science. 2018;31:1107–1121.
MLA Palappan, Anbarasan and Jayabarathi Thangavelu. “A New Meta Heuristic Dragonfly Optimizaion Algorithm for Optimal Reactive Power Dispatch Problem”. Gazi University Journal of Science, vol. 31, no. 4, 2018, pp. 1107-21.
Vancouver Palappan A, Thangavelu J. A New Meta Heuristic Dragonfly Optimizaion Algorithm for Optimal Reactive Power Dispatch Problem. Gazi University Journal of Science. 2018;31(4):1107-21.