International Journal of Information Engineering and Electronic Business (IJIEEB)
IJIEEB Vol. 6, No. 4, 8 Aug. 2014
Cover page and Table of Contents: PDF (size: 531KB)
Quantum Particle Swarm Optimization Algorithm for Solving Optimal Reactive Power Dispatch Problem
Full Text (PDF, 531KB), PP.32-37
Views: 0 Downloads: 0
Author(s)
K.Lenin
1,*
B.Ravindhranath Reddy
2
Index Terms
Quantum Behaved PSO, Optimization, Swarm Intelligence, Optimal Reactive Power, Transmission Loss
Abstract
This paper presents a quantum behaved particle swarm algorithm for solving the multi-objective reactive power dispatch problem .Particle swarm optimization (PSO) is a population-based swarm intellect algorithm that share various similarities with evolutionary computation methods. Yet, PSO is determined by the imitation of a societal psychosomatic metaphor aggravated by cooperative behaviours of bird and other societal organisms instead of, the endurance of the fittest individual. Stimulated by the traditional PSO method and quantum procedure theories, this work presents a new Quantum behaved PSO (QPSO). The simulation results reveal high-quality performance of the QPSO in solving an optimal reactive power dispatch problem. In order to appraise the proposed algorithm, it has been tested on IEEE 30 bus system and compared to other algorithms.
Cite This Paper
K.Lenin, B.Ravindhranath Reddy, "Quantum Particle Swarm Optimization Algorithm for Solving Optimal Reactive Power Dispatch Problem", International Journal of Information Engineering and Electronic Business(IJIEEB), vol.6, no.4, pp.32-37, 2014. DOI:10.5815/ijieeb.2014.04.05
Reference
[1]O.Alsac,and B. Scott, “Optimal load flow with steady state security”,IEEE Transaction. PAS -1973, pp. 745-751.
[2]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
[3]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.
[4]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
[5]E. Hobson ,’Network consrained reactive power control using linear programming, ‘ IEEE Transactions on power systems PAS -99 (4) ,pp 868-877, 1980
[6]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.
[7]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.
[8]S.R.Paranjothi ,and K.Anburaja, “Optimal power flow using refined genetic algorithm”, Electr.Power Compon.Syst , Vol. 30, 1055-1063,2002.
[9]D. Devaraj, and B. Yeganarayana, “Genetic algorithm based optimal power flow for security enhancement”, IEE proc-Generation.Transmission and. Distribution; 152, 6 November 2005.
[10]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 .
[11]Dorigo M, Stu¨ tzle T. Ant colony optimization. In: A Bradford book. Cambridge (MA): The MIT Press; 2004.
[12]Kennedy JF, Eberhart RC, Shi Y. Swarm intelligence. San Francisco (USA): Morgan Kaufmann Pub; 2001.
[13]Bonabeau E, Dorigo M, Theraulaz G. Swarm intelligence: from natural to artificial systems. USA: Oxford University Press;1999.
[14]Kennedy JF, Eberhart RC. Particle swarm optimization. In: Proceedings of IEEE international conference on neural networks, Perth, Australia, 1995. p. 1942–48.
[15]Eberhart RC, Kennedy JF. A new optimizer using particle swarm theory. In: Proceedings of international symposium on micro machine and human science, Japan, 1995. p. 39–43.
[16]Goldberg DE. Genetic algorithms in search, optimization, and machine learning. Reading (MA, USA): Addison Wesley; 1989.
[17]Pang XF. Quantum mechanics in nonlinear systems. River Edge (NJ, USA): World Scientific Publishing Company; 2005.
[18]Schweizer W. Numerical quantum dynamics, Hingham (MA, USA), 2001.
[19]Hogg T, Portnov DS. Quantum optimization. Inform Sci 2000;128:181–97.
[20]Protopescu V, Barhen J. Solving a class of continuous global optimization problems using quantum algorithms. Phys Lett A 2002;296:9–14.
[21]Bulger D, Baritompa WP, Wood GR. Implementing pure adaptive search with Grover’s quantum algorithm. J Optim: Theor Appl 2003;116(3):517–29.
[22]Sun J, Feng B, Xu W. Particle swarm optimization with particles having quantum behavior. In: Proceedings of congress on evolutionary computation, Portland (OR, USA), 2004. p. 325–31.
[23]Sun J, Xu W, Feng B. Adaptive parameter control for quantum-behaved particle swarm optimization on individual level. In: Proceedings of IEEE international conference on systems, man and cybernetics, Big Island (HI, USA), 2005. p. 3049–54.
[24]Liu J, Xu W, Sun J. Quantum-behaved particle swarm optimization with mutation operator. In: Proceedings of 17th international conference on tools with artificial intelligence, Hong Kong (China), 2005.
[25]Levin FS. An introduction to quantum theory. Cambridge University Press; 2002.
[26]Clerc M, Kennedy JF. The particle swarm: explosion, stability and convergence in a multi-dimensional complex space. IEEE Trans Evolution Comput 2002;6(1):58–73.
[27]Wu Q H, Ma J T. Power system optimal reactive power dispatch using evolutionary programming. IEEE Transactions on power systems 1995; 10(3): 1243-1248 .
[28]S.Durairaj, D.Devaraj, P.S.Kannan ,’ Genetic algorithm applications to optimal reactive power dispatch with voltage stability enhancement’ , IE(I) Journal-EL Vol 87,September 2006.
[29]D.Devaraj ,’ Improved genetic algorithm for multi – objective reactive power dispatch problem’ European Transactions on electrical power 2007 ; 17: 569-581.
[30]P. Aruna Jeyanthy and Dr. D. Devaraj “Optimal Reactive Power Dispatch for Voltage Stability Enhancement Using Real Coded Genetic Algorithm” International Journal of Computer and Electrical Engineering, Vol. 2, No. 4, August, 2010 1793-8163.
[31]Reza Baghipour, Seyyed Mehdi Hosseini “Placement of DG and Capacitor for Loss Reduction, Reliability and Voltage Improvement in Distribution Networks Using BPSO”, International Journal of Intelligent Systems and Applications(IJISA)IJISA Vol. 4, No. 12, PP.57-64,November 2012.
[32]Messaoudi Abdelmoumene, Belkacemi Mohamed, Azoui Boubakeur, Optimal Reactive Power Dispatch Using Differential Evolution Algorithm with Voltage Profile Control, International Journal of Intelligent Systems and Applications,IJISA Vol. 5, No. 10, PP.28-34, September 2013.