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Distribution of Loads and Setting of Distribution Sub Station Using Clustering Technique

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Advances in Computing, Communication and Control (ICAC3 2011)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 125))

Abstract

Choosing an optimum location of a distribution substation and grouping the various load points to be fed from a particular distribution substation has always been a concern to the distribution planners. A lot of work has been carried out in this regards but all have made either the use of man machine interface or have made some approximations. Here in this paper we present a Hard Clustering method for grouping the various load points as per the number of distribution transformers available. The method further gives an optimum location of the distribution substation taking into aspects the distances of the various load points that it is feeding. The results of the discussed techniques will lead to a configuration of substations that will minimize substation construction cost. It will further lower long range distribution expenses as it will lead to optimum feeder path.

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References

  1. Turkay, B., Artac, T.: Optimal Distribution Network Design Using Genetic Algorithm. Electric Power Components and Systems 33, 513–524 (2005)

    Article  Google Scholar 

  2. Gomez, J.F., et al.: Ant Colony System Algorithm for the Planning of Primary Distribution Circuits. IEEE Transactions on Power Systems 19(2) (May 2004)

    Google Scholar 

  3. Li, K.K., Chung, T.S.: Distribution Planning Using Rule Based Expert System Approach. In: IEEE International Conference on Electric Utility Deregulation and Power Technologies, DRPT 2004 (April 2004)

    Google Scholar 

  4. Crawford, D.M., Holt, S.B.: A Mathematical Optimization Technique For Locating Sizing Distribution Substations, and Driving Their Optimal Service Areas. IEEE. Trans. on Power Apparatus and Systems PAS 94(2), 230–235 (1975)

    Article  Google Scholar 

  5. El-Kady, M.A.: Computer Aided planning of Distribution Substation and Primary Feeders. IEEE. Trans. on Power Apparatus and Systems PAS 103(6), 1183–1189 (1984)

    Article  Google Scholar 

  6. Gonen, T., Ramirez-Rosado, I.J.: Optimal Multi Stage Planning of Power Distribution Systems. IEEE Trans. on Power Delivery PWRD-2(2), 512–519 (1987)

    Article  Google Scholar 

  7. Partanen, J.: A Modified Dynamic Programming Algorithm for Sizing, Locating and Timing of Feeder Reinforcements. IEEE Trans. on Power Delivery 5(1), 227–283 (1990)

    Article  Google Scholar 

  8. Khator, S.K., Leung, L.C.: Power Distribution Planning: A review of models and issues. IEEE Trans. Power Syst. 12, 1151–1159 (1997)

    Article  Google Scholar 

  9. Bernal-Agustin, J.L.: Aplicacion de Algoritmos Geneticos al Diseno Optimo de Sistemas de Distribucion de Energia Electrica, Ph.D. dieesrtation, University de Zaragoza, Espana (1998)

    Google Scholar 

  10. Boardman, J.T., Meekiff, C.C.: A branch and bound formulation of an electricity distribution planning problem. IEEE Trans. Power App. Syst. 104, 2112–2118 (1985)

    Article  Google Scholar 

  11. Nara, K., et al.: Distribution system expansion planning b multi-stage branch exchange. IEEE Trans. Power Syst. 7, 208–214 (1992)

    Article  Google Scholar 

  12. Carvalho, P.M.S., Ferreira, L.A.F.M.: Optimal distribution network expansion planning under uncertainty by evolutionary decision convergence. Int. J. Elect. Power Energy Syst. 20(2), 125–129 (1998)

    Article  MathSciNet  Google Scholar 

  13. Dorigo, M., Gambardella, L.M.: Ant colony system: A cooperative learning approach to the traveling salesman problem. IEEE Trans. Evol. Comput. 1, 29–41 (1997)

    Article  Google Scholar 

  14. Diaz Dorado, E., Cidras, J., Miguez, E.: Application of evolutionary algorithms for the planning of urban distribution networks of medium voltage. IEEE Trans. Power Syst. 17, 879–884 (2002)

    Article  Google Scholar 

  15. Chakravorty, S., Ghosh, S.: An Improvised Method for Distribution of Loads and Configuration of Distribution Sub Station. International Journal of Engineering Research and Industrial Applications 2(II), 269–280 (2009)

    Google Scholar 

  16. Chakravorty, S., Ghosh, S.: Fuzzy Based Distribution Planning Technique. Journal of Electrical Engineering 9(2), 38–43 (2009)

    Google Scholar 

  17. Chakravorty, S., Ghosh, S.: Distribution Planning Based on Reliability and Contingency Criteria. International Journal of Computer and Electrical Engineering 1(2), 156–161 (2009)

    Google Scholar 

  18. Chakravorty, S., Ghosh, S.: A Novel Approach to Distribution Planning in an Unstructured Environment. International Journal of Computer and Electrical Engineering 1(3), 362–367 (2009)

    Google Scholar 

  19. Chakravorty, S., Ghosh, S.: A Hybrid Model of Distribution Planning. International Journal of Computer and Electrical Engineering 1(3), 368–374 (2009)

    Google Scholar 

  20. Chakravorty, S., Ghosh, S.: Power Distribution Planning Using Multi-Criteria Decision Making Method. International Journal of Computer and Electrical Engineering 1(5), 622–627 (2009)

    Google Scholar 

  21. Chakravorty, S., Thukral, M.: Optimal Allocation of Load Using Optimization Technique. In: Proceedings of International Conference CISSE, Bridgeport, USA, pp. 435–437 (2007)

    Google Scholar 

  22. Chakravorty, S., Thukral, M.: Choosing Distribution Sub Station Location Using Soft Computing Technique. In: Proceedings of International Conference on Advances in Computing, Communication and Control – 2009, Mumbai, India, pp. 53–55 (2009)

    Google Scholar 

  23. Dhar, S., Ray, A., Bera, R., Sur, S.N., Ghosh, D.: A Complete Simulation Of Intra Vehicle Link Through Best PossibleWireless Network. International Journal of Computer and Electrical Engineering 2(4), 673–681 (2010)

    Article  Google Scholar 

  24. Ray, A., et al.: Process Cost Prediction: A Soft Computing Approach. International Journal of Intelligent Computing and Cybernetics 3(3), 431–448 (2010)

    Article  MathSciNet  Google Scholar 

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Shabbiruddin, Sandeep, C. (2011). Distribution of Loads and Setting of Distribution Sub Station Using Clustering Technique. In: Unnikrishnan, S., Surve, S., Bhoir, D. (eds) Advances in Computing, Communication and Control. ICAC3 2011. Communications in Computer and Information Science, vol 125. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-18440-6_11

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  • DOI: https://doi.org/10.1007/978-3-642-18440-6_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-18439-0

  • Online ISBN: 978-3-642-18440-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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