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Reconfiguration of Radial Distribution Systems with Fuzzy Multi-Objective Approach Using Modified Big Bang-Big Crunch Algorithm

  • Research Article - Electrical Engineering
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Abstract

This paper presents an efficient method for the multi-objective reconfiguration of distribution networks in fuzzy framework using modified Big Bang-Big Crunch algorithm. The considered objectives are minimization of network real power, minimization of the deviation of nodes voltage, minimization of the branch current constraint violation and minimization of switching operations number. All the objectives are fuzzified with trapezoidal membership function and the max-geometric mean operator is applied to determine the best compromising solution among the four objectives. The 33-bus and 69-bus distribution networks are used to demonstrate effectiveness of the proposed method. The obtained results show that proposed method is powerful and promising for reconfiguration of multi-objective distribution systems.

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References

  1. Merlin, A.; Back, H.: Search for a minimal-loss operating tree configuration in an urban power distribution system. In: Proceedings of the 5th Power System Computation Conference, Cambridge, UK, pp. 1–18 (1975)

  2. Civanlar S., Grainger J.J., Yin H., Lee S.S.H.: Distribution feeder reconfiguration for loss reduction. IEEE Trans. Power Deliv. 3(3), 1217–1223 (1988)

    Article  Google Scholar 

  3. Baran M.E., Wu F.F.: Network reconfiguration in distribution systems for loss reduction and load balancing. IEEE Trans. Power Deliv. 4(2), 1401–1407 (1989)

    Article  Google Scholar 

  4. Zhu J., Xiong X., Zhang J.: A rule based comprehensive approach for reconfiguration of electrical distribution network. Electr. Power Syst. Res. 79, 311–315 (2009)

    Article  Google Scholar 

  5. Abul’Wafa A.R.: A new heuristic approach for optimal reconfiguration in distribution systems. Electr. Power Syst. Res. 81, 282–289 (2011)

    Article  Google Scholar 

  6. Das D.: A fuzzy multiobjective approach for network reconfiguration of distribution systems. IEEE Trans. Power Deliv. 21(1), 202–209 (2006)

    Article  Google Scholar 

  7. Swarnkar A., Gupta N., Niazi K.R.: Reconfiguration of radial distribution systems with fuzzy multi-objective approach using adaptive particle swarm optimization. IEEE Trans. Power Deliv. 21(1), 1202–1209 (2010)

    Google Scholar 

  8. Swarnkar A., Gupta N., Niazi K.R.: Multi-objective reconfiguration of distribution systems using adaptive genetic algorithm in fuzzy framework. IET Gener. Transm. Distrib. 4(12), 1288–1298 (2010)

    Article  Google Scholar 

  9. Su C., Chang C., Chiou J.: Distribution network reconfiguration for loss reduction by ant colony search algorithm. Electr. Power Syst. Res. 75, 190–199 (2005)

    Article  Google Scholar 

  10. Zhu J.Z.: Optimal reconfiguration of electrical distribution network using the refined genetic algorithm. Electr. Power Syst. Res. 62(1), 37–42 (2002)

    Article  Google Scholar 

  11. Niknam, T.: An efficient hybrid evolutionary based on PSO and ACO algorithm for distribution feeder reconfiguration. Eur. Trans. Electr. Power, forthcoming, (2009). doi:10.1002/etep.339

  12. Abdelaziz A., Mohammed F., Mekhamer S.: Distribution systems reconfiguration using a modified Tabu search algorithm. Electr. Power Syst. Res. 80, 943–953 (2010)

    Article  Google Scholar 

  13. Abdelaziz A., Mohammed F., Mekhamer S.: Distribution systems reconfiguration using a modified particle swarm optimization algorithm. Electr. Power Syst. Res. 79, 1521–1530 (2009)

    Article  Google Scholar 

  14. Shirmohammadi D., Hong H.W.: Reconfiguration of electric distribution networks for resistive line losses reduction. IEEE Trans. PWRD 4(2), 1492–1498 (1989)

    Google Scholar 

  15. Chiang H.D., Jean-Jumeau R.: Optimal network reconfiguration in distribution systems: part II. IEEE Trans. Power Deliv. 5(3), 1568–1574 (1990)

    Article  Google Scholar 

  16. Rugthaicharoencheep, N.; Sirisumrannukul, S.: Optimal feeder reconfiguration with distributed generators in distribution system by fuzzy multiobjective and Tabu search, sustainable power generation and supply conf., SUPERGEN 09, (April (6–7)) (2009), pp. 1–7

  17. Huang Y.C.: Enhanced genetic algorithm-based fuzzy multi-objective approach to distribution network reconfiguration. IEE Gener. Transm. Distrib. 149(5), 615–620 (2002)

    Article  Google Scholar 

  18. Erol O.K., Eksin I.: A new optimization method: big bang-big crunch. Electr. Power Syst. Res. 37, 106–111 (2006)

    Google Scholar 

  19. Goswami S.K., Basu S.K.: A new algorithm for the reconfiguration of distribution feeders for loss minimization. IEEE Trans. Power Deliv. 7(3), 1484–1491 (1992)

    Article  Google Scholar 

  20. Rao P.V.V.R., Sivanagaraju S.: Radial distribution network reconfiguration for loss reduction and load balancing using plant growth simulation algorithm. Int. J. Electr. Eng. Inform. 2, 266–277 (2010)

    Google Scholar 

  21. Sivanagaraju S.; et al.: An efficient genetic algorithm for loss minimum distribution system reconfiguration. Int. J. Electr. Power Compon. Syst. 34(3), 249–258 (2006)

    Article  Google Scholar 

  22. Niknam T.: An efficient multi-objective HBMO algorithm for distribution feeder reconfiguration. Expert Syst. Appl. 38(3), 2878–2887 (2011)

    Article  Google Scholar 

  23. Olamaei J., Niknam T., Badali Arefi S.: Distribution feeder reconfiguration for loss minimization based on modified honey bee mating optimization algorithm. Energy Procedia 14, 304–311 (2012)

    Article  Google Scholar 

  24. Niknam T., Azad Farsani E.: A hybrid self-adaptive particle swarm optimization and modified shuffled frog leaping algorithm for distribution feeder reconfiguration. Eng. Appl. Artif. Intell. 23(8), 1340–1349 (2010)

    Article  Google Scholar 

  25. Niknam T., Azadfarsani E., Jabbari M.: A new hybrid evolutionary algorithm based on new fuzzy adaptive PSO and NM algorithms for distribution feeder reconfiguration. Energy Convers. Manag. 54(1), 7–16 (2012)

    Article  Google Scholar 

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Authors and Affiliations

  1. Faculty of Electrical and Computer Engineering, Shahid Beheshti University, Tehran, Iran

    Mostafa Sedighizadeh, Maryam Ghalambor & Alireza Rezazadeh

Authors
  1. Mostafa Sedighizadeh
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  2. Maryam Ghalambor
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  3. Alireza Rezazadeh
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Correspondence to Mostafa Sedighizadeh.

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Sedighizadeh, M., Ghalambor, M. & Rezazadeh, A. Reconfiguration of Radial Distribution Systems with Fuzzy Multi-Objective Approach Using Modified Big Bang-Big Crunch Algorithm. Arab J Sci Eng 39, 6287–6296 (2014). https://doi.org/10.1007/s13369-014-1249-6

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  • DOI: https://doi.org/10.1007/s13369-014-1249-6

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