BibTex RIS Kaynak Göster
Yıl 2010, Cilt: 10 Sayı: 2, 1257 - 1266, 20.01.2012

Öz

Kaynakça

  • J. Carpentier, "Optimal Power Flows: Uses, methods and developments", IFAC Symposium on planning and operation of electric energy systems. Rio de Janeiro, July 1985, Invited survey paper.
  • M. Huneault and F. D. Galiana, “A Survey of the Optimal Power Flow Literature,” IEEE Trans. Power Systems, vol. 6, pp. 762-770, May 1991.
  • Dommel, H.W.; Tinney, W.F., "Optimal Power Flow Solutions," power apparatus and systems, IEEE transactions on , vol.PAS-87, no.10, pp.1866-1876, Oct. 1968
  • Alguacil, N.; Conejo, A.J., "Multiperiod optimal power flow using Benders decomposition," Power Systems, IEEE Transactions on , vol.15, no.1, pp.196-201, Feb 2000
  • J. A. Momoh, M. E. El-Hawary, and R. Adapa, 1999, “A Review of Selected Optimal Power Flow Literature to 1993 Parts I & II,” IEEE Trans. on Power Systems, Vol. 14, No. 1, pp. 96–111.
  • Overbye TJ, Cheng Xu, Sun Yan. A Comparison of the AC and DC power flow models for LMP Calculations. In: 37th Hawaii international conference on system sciences, 2004, USA.
  • D. E. Goldberg Genetic Algorithms in Search, Optimization and Machine Learning,Addison Wesley Publishing Company, Ind. USA, 1989.
  • Holland J.H., 1975, 'Adaptation in Natural and Artificial System', Ann Arbor, the University of Michigan Press.
  • Z.Michlewicz,’Genetic Algorithms +Data Structures=Evolution Program, Springer-Verlag, 1994.
  • M. Mitchell, 1996, 'An Introduction to Genetic Algorithms', Cambridge, MIT Press.
  • M. D. Vose, 'The simple Genetic Algorithm: Foundations and theory', Cambridge, MIT Press, 1999.
  • Holland J.H., 1975,'Adaptation in Natural and Artificial System', Ann Arbor, the University of Michigan Press.
  • D. E Goldberg, “Sizing Populations for Serial and Parallel Genetic Algorithms”, in J.D. Schaffer, editor, Proceedings of the Third International Conference on Genetic Algorithms, Morgan Kaufmann, 1989.
  • TarekBouktir, Linda Slimani and M. Belkacemi, “Genetic Algorithm for Solving the Optimal Power Flow Problem,” Department of Electrical Engineering, University of Oum El Bouaghi, 04000, Algeria.
  • L.L. Lai, J. T. Ma, R. Yokoma and M. Zhao, “Improved Genetic Algorithms for Optimal Power Flow Under Both Normal and Contingent Operation States”, Electrical Power& Energy System, Vol. 19, pp. 287-292, 1997.
  • Devaraj, D.; Yegnanarayana, B., "Geneticalgorithm-based optimal power flow for security enhancement," Generation, Transmission and Distribution, IEE Proceedings- , vol.152, no.6, pp. 899-905, 4 Nov. 2005
  • Vijayakumar, K., Kumudinidevi, R. P., and Suchithra, D., "A Hybrid Genetic Algorithm for Optimal Power Flow Incorporating FACTS Devices", Proceedings of the international Conference on Computational intelligence and Multimedia Applications, Vol 01, Dec 2007
  • Paranjothi, S.R., and Anburaja, K.: ‘Optimal power flow using refined genetic algorithms’, Electr. PowerCompon. Syst., 2002, 30, pp. 1055– 1063
  • A. G. Bakirtzis, P. N. Biskas, C. E. Zoumas, and V. Petridis, “Optimal power flow by enhanced genetic algorithm,” IEEE Trans. PowerSyst.,vol. 17, pp. 229–236, May 2002.
  • J. T. Richardson, M. R. Palmer, G. Liepins, and M. Hilliard, “Some guidelines for genetic algorithms with penalty functions,” in Proc. Third Annual Conf. on Genetic Algorithms, June 1989, pp. 191– 197.
  • Bakirtzis, A.G.; Biskas, P.N.; Zoumas, C.E.; Petridis, V., "Optimal power flow by enhanced genetic algorithm," Power Systems, IEEE Transactions on , vol.17, no.2, pp.229-236, May 2002
  • Srinivas, M.; Patnaik, L.M., "Adaptive probabilities of crossover and mutation in genetic algorithms," Systems, Man and Cybernetics, IEEE Transactions on , vol.24, no.4, pp.656-667, Apr 1994
  • M SailajaKumari, M Sydulu, "A Fast and Reliable Quadratic Approach for Q-adjustments in Fast Decoupled Load FlowModel," 9th International Conference on Probabilistic Methods Applied to Power Systems KTH, Stockholm, Sweden, pp. 15, June 2006.

AN EXPERT BASED INITIAL GENERATION OF GENETIC ALGORITHM WITH ADAPTIVE PROBABILITY APPROACH FOR QUADRATIC OPF

Yıl 2010, Cilt: 10 Sayı: 2, 1257 - 1266, 20.01.2012

Öz

This paper presents a novel and superior Genetic Algorithm (GA) based resolver for Optimal Power flow (OPF) problem. Here, the main contrast to other Genetic Algorithm based approaches is that a novel expert based initial generation of population and adaptive probability approach (variable Cross over probability and mutation probability) is adopted in selection of offspring together with roulette wheel technique which reduces the computation time and increases the quality considerably. Selection and Placement of Shunt Devices are considered as a variable in this novel approach. Here continuous variables like Voltage Profile and discrete variable like transformer tapings are considered while minimizing the Fuel cost. The results obtained on standard IEEE 14 bus and 30 bus systems is compared with simple Genetic Algorithm and Particle Swarm Optimization (PSO) to Optimal Power flow and is found that this approach is more efficient, robust and promising. Keywords: Adaptive probability, Optimal Power Flow, Genetic Algorithm, Genetic Operators, Power system Optimization.

Kaynakça

  • J. Carpentier, "Optimal Power Flows: Uses, methods and developments", IFAC Symposium on planning and operation of electric energy systems. Rio de Janeiro, July 1985, Invited survey paper.
  • M. Huneault and F. D. Galiana, “A Survey of the Optimal Power Flow Literature,” IEEE Trans. Power Systems, vol. 6, pp. 762-770, May 1991.
  • Dommel, H.W.; Tinney, W.F., "Optimal Power Flow Solutions," power apparatus and systems, IEEE transactions on , vol.PAS-87, no.10, pp.1866-1876, Oct. 1968
  • Alguacil, N.; Conejo, A.J., "Multiperiod optimal power flow using Benders decomposition," Power Systems, IEEE Transactions on , vol.15, no.1, pp.196-201, Feb 2000
  • J. A. Momoh, M. E. El-Hawary, and R. Adapa, 1999, “A Review of Selected Optimal Power Flow Literature to 1993 Parts I & II,” IEEE Trans. on Power Systems, Vol. 14, No. 1, pp. 96–111.
  • Overbye TJ, Cheng Xu, Sun Yan. A Comparison of the AC and DC power flow models for LMP Calculations. In: 37th Hawaii international conference on system sciences, 2004, USA.
  • D. E. Goldberg Genetic Algorithms in Search, Optimization and Machine Learning,Addison Wesley Publishing Company, Ind. USA, 1989.
  • Holland J.H., 1975, 'Adaptation in Natural and Artificial System', Ann Arbor, the University of Michigan Press.
  • Z.Michlewicz,’Genetic Algorithms +Data Structures=Evolution Program, Springer-Verlag, 1994.
  • M. Mitchell, 1996, 'An Introduction to Genetic Algorithms', Cambridge, MIT Press.
  • M. D. Vose, 'The simple Genetic Algorithm: Foundations and theory', Cambridge, MIT Press, 1999.
  • Holland J.H., 1975,'Adaptation in Natural and Artificial System', Ann Arbor, the University of Michigan Press.
  • D. E Goldberg, “Sizing Populations for Serial and Parallel Genetic Algorithms”, in J.D. Schaffer, editor, Proceedings of the Third International Conference on Genetic Algorithms, Morgan Kaufmann, 1989.
  • TarekBouktir, Linda Slimani and M. Belkacemi, “Genetic Algorithm for Solving the Optimal Power Flow Problem,” Department of Electrical Engineering, University of Oum El Bouaghi, 04000, Algeria.
  • L.L. Lai, J. T. Ma, R. Yokoma and M. Zhao, “Improved Genetic Algorithms for Optimal Power Flow Under Both Normal and Contingent Operation States”, Electrical Power& Energy System, Vol. 19, pp. 287-292, 1997.
  • Devaraj, D.; Yegnanarayana, B., "Geneticalgorithm-based optimal power flow for security enhancement," Generation, Transmission and Distribution, IEE Proceedings- , vol.152, no.6, pp. 899-905, 4 Nov. 2005
  • Vijayakumar, K., Kumudinidevi, R. P., and Suchithra, D., "A Hybrid Genetic Algorithm for Optimal Power Flow Incorporating FACTS Devices", Proceedings of the international Conference on Computational intelligence and Multimedia Applications, Vol 01, Dec 2007
  • Paranjothi, S.R., and Anburaja, K.: ‘Optimal power flow using refined genetic algorithms’, Electr. PowerCompon. Syst., 2002, 30, pp. 1055– 1063
  • A. G. Bakirtzis, P. N. Biskas, C. E. Zoumas, and V. Petridis, “Optimal power flow by enhanced genetic algorithm,” IEEE Trans. PowerSyst.,vol. 17, pp. 229–236, May 2002.
  • J. T. Richardson, M. R. Palmer, G. Liepins, and M. Hilliard, “Some guidelines for genetic algorithms with penalty functions,” in Proc. Third Annual Conf. on Genetic Algorithms, June 1989, pp. 191– 197.
  • Bakirtzis, A.G.; Biskas, P.N.; Zoumas, C.E.; Petridis, V., "Optimal power flow by enhanced genetic algorithm," Power Systems, IEEE Transactions on , vol.17, no.2, pp.229-236, May 2002
  • Srinivas, M.; Patnaik, L.M., "Adaptive probabilities of crossover and mutation in genetic algorithms," Systems, Man and Cybernetics, IEEE Transactions on , vol.24, no.4, pp.656-667, Apr 1994
  • M SailajaKumari, M Sydulu, "A Fast and Reliable Quadratic Approach for Q-adjustments in Fast Decoupled Load FlowModel," 9th International Conference on Probabilistic Methods Applied to Power Systems KTH, Stockholm, Sweden, pp. 15, June 2006.
Toplam 23 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Bölüm Makaleler
Yazarlar

Mithun Bhaskar Bu kişi benim

Mohan Benarjı Bu kişi benim

Sydulu Maheswarapu Bu kişi benim

Yayımlanma Tarihi 20 Ocak 2012
Yayımlandığı Sayı Yıl 2010 Cilt: 10 Sayı: 2

Kaynak Göster

APA Bhaskar, M., Benarjı, M., & Maheswarapu, S. (2012). AN EXPERT BASED INITIAL GENERATION OF GENETIC ALGORITHM WITH ADAPTIVE PROBABILITY APPROACH FOR QUADRATIC OPF. IU-Journal of Electrical & Electronics Engineering, 10(2), 1257-1266.
AMA Bhaskar M, Benarjı M, Maheswarapu S. AN EXPERT BASED INITIAL GENERATION OF GENETIC ALGORITHM WITH ADAPTIVE PROBABILITY APPROACH FOR QUADRATIC OPF. IU-Journal of Electrical & Electronics Engineering. Ocak 2012;10(2):1257-1266.
Chicago Bhaskar, Mithun, Mohan Benarjı, ve Sydulu Maheswarapu. “AN EXPERT BASED INITIAL GENERATION OF GENETIC ALGORITHM WITH ADAPTIVE PROBABILITY APPROACH FOR QUADRATIC OPF”. IU-Journal of Electrical & Electronics Engineering 10, sy. 2 (Ocak 2012): 1257-66.
EndNote Bhaskar M, Benarjı M, Maheswarapu S (01 Ocak 2012) AN EXPERT BASED INITIAL GENERATION OF GENETIC ALGORITHM WITH ADAPTIVE PROBABILITY APPROACH FOR QUADRATIC OPF. IU-Journal of Electrical & Electronics Engineering 10 2 1257–1266.
IEEE M. Bhaskar, M. Benarjı, ve S. Maheswarapu, “AN EXPERT BASED INITIAL GENERATION OF GENETIC ALGORITHM WITH ADAPTIVE PROBABILITY APPROACH FOR QUADRATIC OPF”, IU-Journal of Electrical & Electronics Engineering, c. 10, sy. 2, ss. 1257–1266, 2012.
ISNAD Bhaskar, Mithun vd. “AN EXPERT BASED INITIAL GENERATION OF GENETIC ALGORITHM WITH ADAPTIVE PROBABILITY APPROACH FOR QUADRATIC OPF”. IU-Journal of Electrical & Electronics Engineering 10/2 (Ocak 2012), 1257-1266.
JAMA Bhaskar M, Benarjı M, Maheswarapu S. AN EXPERT BASED INITIAL GENERATION OF GENETIC ALGORITHM WITH ADAPTIVE PROBABILITY APPROACH FOR QUADRATIC OPF. IU-Journal of Electrical & Electronics Engineering. 2012;10:1257–1266.
MLA Bhaskar, Mithun vd. “AN EXPERT BASED INITIAL GENERATION OF GENETIC ALGORITHM WITH ADAPTIVE PROBABILITY APPROACH FOR QUADRATIC OPF”. IU-Journal of Electrical & Electronics Engineering, c. 10, sy. 2, 2012, ss. 1257-66.
Vancouver Bhaskar M, Benarjı M, Maheswarapu S. AN EXPERT BASED INITIAL GENERATION OF GENETIC ALGORITHM WITH ADAPTIVE PROBABILITY APPROACH FOR QUADRATIC OPF. IU-Journal of Electrical & Electronics Engineering. 2012;10(2):1257-66.