Abstract
Selection of optimum location of a sub-station and distribution of load points to each available sub-station has been a major concern among researchers but all have made either the use of man machine interface or have made some approximations. Here in this paper, a soft computing approach Hierarchial Clustering method is used for grouping the various load points as per the number of distribution sub-stations available. The method further gives an optimum location of the distribution sub-station taking into aspects the distances of the various load points that it is feeding. The results of the discussed technique will lead to a configuration of distribution substations depending on the no. of load points and sub-stations required. It will have an effect of lowering the long range distribution expenses as it will lead to optimum feeder path. The application of the proposed methodology to a case study is presented.
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References
Turkay, B., Artac, T.: Optimal Distribution Network Design Using Genetic Algorithm. Electric Power Components and Systems 33, 513–524 (2005)
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)
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)
Crawford, D.M., Holt, S.B.: A Mathematical Optimization Technique For Locating Sizing Distribution Sub-stations, and Driving Their Optimal Service Areas. IEEE. Trans. on Power Apparatus and Systems PAS 94(2), 230–235 (1975)
El-Kady, M.A.: Computer Aided planning of Distribution Sub-station and Primary Feeders. IEEE. Trans. on Power Apparatus and Systems PAS 103(6), 1183–1189 (1984)
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)
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)
Khator, S.K., Leung, L.C.: Power Distribution Planning: A review of models and issues. IEEE Trans. Power Syst. 12, 1151–1159 (1997)
Bernal-Agustin, J.L.: Aplicacion de Algoritmos Geneticos al Diseno Optimo de Sistemas de Distribucion de Energia Electrical. Ph.D. dieesrtation, University de Zaragoza, Espana (1998)
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)
Nara, K., et al.: Distribution system expansion planning b multi-stage branch exchange. IEEE Trans. Power Syst. 7, 208–214 (1992)
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)
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)
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)
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)
Chakravorty, S., Ghosh, S.: Fuzzy Based Distribution Planning Technique. Journal of Electrical Engineering 9, 38–43 (2009)
Chakravorty, S., Ghosh, S.: Distribution Planning Based on Reliability and Contingency Criteria. International Journal of Computer and Electrical Engineering 1(2), 156–161 (2009)
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)
Chakravorty, S., Ghosh, S.: A Hybrid Model of Distribution Planning. International Journal of Computer and Electrical Engineering 1(3), 368–374 (2009)
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)
Chakravorty, S., Thukral, M.: Optimal Allocation of Load Using Optimization Technique. In: Proceedings of International Conference CISSE, Bridgeport, USA, pp. 435–437 (2007)
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)
Shabbiruddin, Chakravorty, S.: Distribution of Loads and Setting of Distribution Sub Station Using Clustering Technique. In: Proceedings of International Conference on Advances in Computing, Communication and Control–2011, pp. 88–94. Springer, Heidelberg (2011)
Shabbiruddin, Chakravorty, S.: Load Distribution Among Distribution Substation and Feeder Routing Using Fuzzy Clustering and Context Aware Decision Algorithm. Journal of Electrical Engineering 11, 57–67 (2011)
Shabbiruddin, Kibria, G.: An Efficient Method for Speed Control of DC Shunt Motor using Response Surface Methodology (RSM) Approach. Journal of Control Engineering and Technology 1, 11–16 (2011)
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Shabbiruddin, Chakravorty, S., Ray, A. (2013). Optimum Sub-station Positioning Using Hierarchial Clustering. In: Meghanathan, N., Nagamalai, D., Chaki, N. (eds) Advances in Computing and Information Technology. Advances in Intelligent Systems and Computing, vol 177. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31552-7_42
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DOI: https://doi.org/10.1007/978-3-642-31552-7_42
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