AN ANFIS BASED FAULT LOCATION IN POWER DISTRIBUTION NETWORKS

Surender Kumar Yellagoud, Purnachandra Rao Talluri, and Gondlala N. Sreenivas

References

  1. [1] T. Gonen, Electric Power Distribution Systems, 2nd ed. (Boca Raton, FL: CRC Press, 2008), 21.
  2. [2] M.M. Saha, J. Ezikowski, and E. Rosolowski, Fault Location on Power Networks (London: Springer Verlag London Limited, 2010), 362.
  3. [3] H.X. Li, P.C.L. Chen, and H.P. Huang, Fuzzy neural intelligent systems, in Mathematical Foundation and the Applications in Engineering (Boca Raton, FL: CRC Press, 2001).
  4. [4] S.M. Yeo, C.H. Kim, and K.S. Hong, A novel algorithm for fault classification in transmission lines using a combined adaptive network and fuzzy inference system, International Journal of Electrical Power and Energy System, 25(9), 2003, 747–758.
  5. [5] N. Zhang and M. Kezunovic, Coordinating fuzzy ART neural networks to improve transmission line fault detection and classification, in IEEE PES, General Meeting, 2005, San Francisco.
  6. [6] M. Joorabian and M. Monadi, Anfis based fault location for EHV transmission lines, AUPEC 2005, Australia.
  7. [7] R.A. Ghani, H. Shareef and A. Mohamed, Fault diagnosis in power distribution network using Adaptive Neuro-Fuzzy Inference System (ANFIS), in M.F. Azeem (ed.), Fuzzy Inference System – Theory and Applications, ISBN: 978-953-51-0525-1 (Croatia: InTech, 2012).
  8. [8] G. Banu and S. Suja, Fault location technique using GA-ANFIS for UHV line, Archives in Electrical Engineering, 63(2), 2014, 247–262.
  9. [9] M.J.B. Reddy, D.V. Rajesh, P. Gopakumar, and D.K. Mohanta, Smart fault location for smart grid operation using RTUs and computational intelligence techniques, IEEE Systems Journal, 8, 2014, 1260–1271.
  10. [10] T.S. Kamel, M. Hassan, and A. El-Morshedy, Advanced distance protection scheme for long transmission lines in electric power systems using multiple classified ANFIS networks, in Fifth International Conference on Soft Computing, Computing with Words and Perceptions in System Analysis, Decision and Control, Famagusta, North Cyprus, 2009, 1–5.
  11. [11] K. Chen, C. Huang, and J. He, Fault detection, classification and location for transmission lines and distribution systems: A review on the methods, High Voltage, IET, 1(1), 2016, 25–33.
  12. [12] H. Eristi, Fault diagnosis system for series compensated transmission line based on wavelet transform and adaptive neuro-fuzzy inference system, Measurement, 46, 2013, 393–401.
  13. [13] J.J. Mora and G. Carrillo, Fault location in power distribution systems using ANFIS nets and current patterns, IEEE PES Transmission and Distribution Conference and Exposition Latin America, Venezuela, 2006.
  14. [14] V.P. Huan and L.K. Hung, An ANFIS based approach toimprove the fault location on 110 kV transmission line DakMil–Dak Nong, International Journal of Computer ScienceIssues, 11(3), May 2014.
  15. [15] J.S.R. Jang, ANFIS: Adaptive network based fuzzy Inference system, IEEE Transactions on Systems, Man and Cybernetics, 23(3), 1993, 665–685.
  16. [16] L.-X. Wang, A Course in Fuzzy Systems and Control (Upper Saddle River, NJ: Prentice Hall, 1996).
  17. [17] T. Takagi and M. Sugeno, Derivation of fuzzy control rules from human operator’s control actions, Proceedings of the IFAC Symposium on Fuzzy Information, Knowledge Representation and Decision Analysis, Marseille, France, 1983, 55–60.
  18. [18] Zadeh, L.A., The concept of a linguistic variable and its application to approximate reasoning – I, Information Sciences (American Elsevier Publishing Company), 8, 1975, 199–249.
  19. [19] IEEE Distribution Planning Working Group Report, Radial distribution test feeders, IEEE Transactions on Power Systems, 6(3), 1991, 975–985.
  20. [20] N.K. Kasabov, Foundations in Neural Networks, Fuzzy Systems and Knowledge Engineering (Cambridge, MA: A Bradford Book, MIT Press, 1988), 179.

Important Links:

Go Back

IASTED
Rotating Call For Paper Image