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Artificial Bee Colony-Based Approach for Optimal Capacitor Placement in Distribution Networks

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Swarm, Evolutionary, and Memetic Computing (SEMCCO 2013)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8297))

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Abstract

This manuscript presents an approach to allocate static capacitors along radial distribution networks using the artificial bee colony algorithm. In general practice the high potential buses for capacitor placement are initially identified using loss sensitivity factors. However, that method has proven less than satisfactory as loss sensitivity factors may not always indicate the appropriate placement. In the proposed approach, the algorithm identifies optimal sizing and placement and takes the final decision for optimum location within the number of buses nominated. The result is enhancement of the overall system stability index and potential achievement of maximum net savings. The obtained results are compared with those achieved using recent heuristic methods and show that the proposed approach is capable of producing high-quality solutions.

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References

  1. Haque, M.H.: Capacitor placement in radial distribution systems for loss reduction. IEE Proc. Gener. Transm. Dis. 146(5), 501–505 (1999)

    Article  Google Scholar 

  2. Chis, M., Salama, M., Jayaram, S.: Capacitor placement in distribution system using heuristic search strategies. IEE Proc. Gener. Transm. Dist. 144(3), 225–230 (1997)

    Article  Google Scholar 

  3. Short, T.A.: Electric power distribution equipment and systems capacitor application. Taylor & Francias Group (2005)

    Google Scholar 

  4. Sirjani, R., Azah, M., Shareef, H.: Heuristic optimization techniques to determine optimal capacitor placement and sizing in radial distribution networks: a comprehensive review. Przegląd Elektrotechniczny (Electr. Rev.) 88(7a), 1–7 (2012)

    Google Scholar 

  5. Gallego, R.A., Monticelli, A.J., Romero, R.: Optimal capacitor placement in radial distribution networks using tabu search. IEEE Trans. Power Syst. 16(4), 630–637 (2001)

    Article  Google Scholar 

  6. Prakash, K., Sydulu, M.: Particle swarm optimization based capacitor placement on radial distribution systems. IEEE PES General Meeting, 1–5 (2007)

    Google Scholar 

  7. Yu, X.M., Xiong, X.Y., Wu, Y.W.: A PSO-based approach to optimal capacitor placement with harmonic distortion consideration. Electr. Power Syst. Res. 71, 27–33 (2004)

    Article  Google Scholar 

  8. Sirjani, R., Mohamed, A., Shareef, H.: Optimal capacitor placement in a radial distribution system using harmony search algorithm. J. Appl. Sci. 10(23), 2996–3006 (2010)

    Google Scholar 

  9. Chang, C.F.: Reconfiguration and capacitor placement for loss reduction of distribution systems by ant colony search algorithm. IEEE Trans. Power Syst. 23(4), 1747–1755 (2008)

    Article  Google Scholar 

  10. Annaluru, R., Das, S., Pahwa, A.: Multi-level ant colony algorithm for optimal placement of capacitors in distribution systems. In: Congress on Evol. Comput, CEC, vol. 2, pp. 1932–1937 (2004)

    Google Scholar 

  11. Chiang, H.D., Wang, J.C., Cockings, O., Shin, H.D.: Optimal capacitor place-ments in distribution systems: part 1: a new formulation and the overall problem. IEEE Trans. Power Deliv. 5(2), 634–642 (1990)

    Article  Google Scholar 

  12. Swarup, K.S.: Genetic Algorithm for optimal capacitor allocation in radial distribution systems. In: Proc. the 6th WSEAS Int. Conf. Evolut. Comput., Lisbon, Portugal, June 16-18, pp. 152–159 (2005)

    Google Scholar 

  13. Hsiao, Y.T., Chen, C.H., Chien, C.C.: Optimal capacitor placement in distribution systems using a combination fuzzy-GA method. Electr. Power Energy Syst. 26, 501–508 (2004)

    Article  Google Scholar 

  14. Tabatabaei, S.M., Vahidi, B.: Bacterial foraging solution based fuzzy logic decision for optimal capacitor allocation in radial distribution system. Electr. Power Syst. Res. 81, 1045–1050 (2011)

    Article  Google Scholar 

  15. Rao, R.S., Narasimham, S.V.L., Ramalingaraju, M.: Optimal capacitor placement in a radial distribution system using plant growth simulation algorithm. Int. J. Electr. Power Energy Syst. 33(5), 1133–1139 (2011)

    Article  Google Scholar 

  16. Huang, S.: An immune-based optimization method to capacitor placement in a radial distribution system. IEEE Trans. Power Deliv. 15(2), 744–749 (2000)

    Article  Google Scholar 

  17. El-Fergany, A.: Optimal capacitor allocations using integrated evolutionary algorithms. IET Gener. Transm. Distrib. 7(6), 593–601 (2013)

    Article  Google Scholar 

  18. Sedighizadeh, M., Arzaghi-haris, D.: Optimal allocation and sizing of capacitors to minimize the distribution line loss and to improve the voltage profile using big bang-big crunch optimization. Int. Rev. Electr. Eng. (IREE) 6(4), Part B, 2013–2019 (2011)

    Google Scholar 

  19. El Arini, M.: Optimal capacitor placement incorporating voltage stability and system security. Eur. Trans. Electr. Power 10(5), 319–325 (2000)

    Article  Google Scholar 

  20. Satpathy, P.K., Das, D., Gupta, P.B.: Critical switching of capacitors to prevent voltage collapse. Electr. Power Sys. Res., 11–20 (2004)

    Google Scholar 

  21. Jasmon, B., Lee, L.H.C.C.: Maximising voltage stability in distribution networks via loss minimization. J. Electr. Power Energy Sys. 13(3), 148–152 (1991)

    Article  Google Scholar 

  22. Graham, W.A., McDonald, J.R.: Planning for distributed generation within distribution networks in restructured electricity markets. IEEE Power Eng. Rev., 52–54 (2000)

    Google Scholar 

  23. Teng, J.H.: A direct approach for distribution system load flow solutions. IEEE Trans. Power Deliv. 18(3), 882–887 (2003)

    Article  Google Scholar 

  24. Gözel, T., Eminoglu, U., Hocaoglu, M.H.: A tool for voltage stability and optimization in radial distribution systems using MATLAB GUI. Simul. Model Pract. Theory 16(5), 505–518 (2008)

    Article  Google Scholar 

  25. Moghavemmi, M., Omar, F.M.: Technique for contingency monitoring and voltage collapse prediction. IEE Proc. Gener. Transm. Dist. 145, 634–640 (1998)

    Article  Google Scholar 

  26. Musirin, I., Rahman, T.K.A.: Estimating maximum loadability for weak bus identification using FVSI. IEEE Power Eng. Rev. 22, 50–52 (2002)

    Article  Google Scholar 

  27. Anhit, S., Ndarajah, M., Kwang, S.: A maximum loading margin method for static voltage stability in power systems. IEEE Trans. Power Syst. 21(2), 965–972 (2006)

    Article  Google Scholar 

  28. Charkravorty, M., Das, D.: Voltage stability analysis of radial distribution networks. Int. J. Electr. Power Energy Syst. 23(2), 129–135 (2001)

    Article  Google Scholar 

  29. Karaboga, D., Basturk, B.: A powerful and efficient algorithm for numerical function optimization: Artificial Bee Colony (ABC) algorithm. Journal of Global Optimization 39(3), 459–471 (2007)

    Article  MATH  MathSciNet  Google Scholar 

  30. Karaboga, D., Basturk, B.: On the performance of artificial bee colony algorithm. Appl. Soft Comput. 8, 687–697 (2008)

    Article  Google Scholar 

  31. Karaboga, D., Akay, B.: A comparative study of Artificial Bee Colony algorithm. J. Appl. Math. Comput. 214, 108–132 (2009)

    Article  MATH  MathSciNet  Google Scholar 

  32. Das, S., Biswas, S., Kundu, S.: Synergizing fitness learning with proximity-based food source selection in artificial bee colony algorithm for numerical optimization. Appl. Soft Comput. (in press, 2013), doi:10.1016/j.asoc.2013.07.009

    Google Scholar 

  33. Biswas, S., Kundu, S., Das, S., Vasilakos, A.: Information sharing in bee colony for detecting multiple niches in non-stationary environments. In: GECCO 2013 Companion Proceeding of the Fifteenth Annual Conference Companion on Genetic and Evolutionary Computation Conference Companion (2013), doi:10.1145/2464576.2464588

    Google Scholar 

  34. Mozaffari, A., Gorji-Bandpy, M., Gorji, T.B.: Optimal design of constraint engineering systems: application of mutable smart bee algorithm. International Journal of Bio-inspired Computation 4(3), 167–180 (2012)

    Article  Google Scholar 

  35. El-Fergany, A., Abdelaziz, A.Y.: Capacitor placement for net saving maximization and system stability enhancement in distribution networks using artificial bee colony-based approach. Int. J. Electr. Power Energy Syst. 54, 235–243 (2014)

    Article  Google Scholar 

  36. http://www.mathworks.com

  37. http://mf.erciyes.edu.tr/abc/

  38. Ali, E., Boudour, M., Rabah, G.: New evolutionary technique for optimization shunt capacitors in distribution networks. J. Electr. Eng. 62(3), 163–167 (2011)

    Google Scholar 

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El-Fergany, A., Abdelaziz, A.Y., Panigrahi, B.K. (2013). Artificial Bee Colony-Based Approach for Optimal Capacitor Placement in Distribution Networks. In: Panigrahi, B.K., Suganthan, P.N., Das, S., Dash, S.S. (eds) Swarm, Evolutionary, and Memetic Computing. SEMCCO 2013. Lecture Notes in Computer Science, vol 8297. Springer, Cham. https://doi.org/10.1007/978-3-319-03753-0_38

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  • DOI: https://doi.org/10.1007/978-3-319-03753-0_38

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-03752-3

  • Online ISBN: 978-3-319-03753-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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