Abstract
In this paper a Genetic Algorithm (GA) method based on graphs theory is proposed to determine the distribution network reconfiguration in presence of wind turbine based DG considering all technical and topological constraints. The objective function considered in this study is the minimization of real power loss. A detailed performance analysis is applied on (33 bus, 69 bus and 84 bus networks) to illustrate the effectiveness of the proposed method. Then this method was validated on Algerian distribution network (116 bus).
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Civanlar, S., Grainger, J., Yin, H., Lee, S.S.: Distribution feeder reconfiguration for loss reduction. IEEE Trans. Power Deliv. 3(3), 1217–1223 (1988)
Shirmohammadi, D., Hong, H.W.: Reconfiguration of electric distribution networks for resistive line loss reduction. IEEE Trans. Power Deliv. 4(1), 1492–1498 (1989)
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)
Solo, A.M.G., Ramakrishna, G., Sarfi, R.J.: A knowledge-based approach for network radiality in distribution system reconfiguration. IEEE Trans. Power Eng. Soc. Gen. Meet. (2006)
Aoki, K., Nara, K., Satch, T., Kitagawa, M., Yamanaka, K.: New approximate optimization method for distribution system planning. IEEE Trans. Power Syst. 5(1), 126–132 (2006)
Abnndams, R.N., Laughton, M.A.: Optimal planning of networks using mixed-integer programming. IEE Proc. 121(2), 139–148 (1974)
Ahmadi, H., Marti, J.R.: Minimum-loss network reconfiguration: a minimum spanning tree problem. Sustain. Energy Grids Netw. 1(xx), 1–9 (2015)
Jabr, R.A., Singh, R., Pal, B.C.: Minimum loss network reconfiguration using mixed-integer convex programming. IEEE Trans. Power Syst. 27(2), 1106–1115 (2012)
Tomoiaga, B., et al.: Optimal reconfiguration of power distribution systems using a genetics algorithm based on NSGA-II. Energies 6(3), 1439–1455 (2013)
Th Nguyen, T., et al.: Multi-objective electric distribution network reconfiguration solution using runner-root algorithm. Appl. Soft Comput. 52, 93–108 (2017)
Chicco, G., Mazza, A.: Assessment of optimal distribution network reconfiguration results using stochastic dominance concepts. Sustain. Energy Grids Netw. 9, 75–79 (2017)
Badran, O., et al.: Optimal reconfiguration of distribution system connected with distributed generations: a review of different methodologies. Renew. Sustain. Energy Rev. 73, 854–867 (2017)
Mosbah, M., Mohammedi, R.D., Arif, S., Hellal, A.: Optimal of shunt capacitor placement and size in Algerian distribution network using particle swarm optimization. In: 8th International Conference on Modelling, Identification and Control (ICMIC), IEEE, Algiérs, January 2017
Mosbah, M., Hellal, A., Mohammedi, R.D., Arif, S.: Genetic algorithms based optimal load shedding with transient stability constraints. In: IEEE Proceedings of the International Electrical Sciences and Technologies in Maghreb, pp. 1–6 (2014)
Mosbah, M., et al.: Optimal sizing and placement of distributed generation in transmission systems. ICREGA-2016, Belfort, France, February, 8–10 ( 2016)
Holland, J.H.: Adaptation in Nature and Artificial Systems. The University of Michigan Press, Ann Arbor (1975)
Hong, Y.-Y., Ho, S.-Y.: Determination of network configuration considering multiobjective in distribution systems using genetic algorithms. IEEE Trans. Power Syst. 20, 1062–1069 (2005)
Niknam, T.: An efficient multi-objective HBMO algorithm for distribution feeder reconfiguration. Exp. Syst. Appl. 38(3), 2878–2887 (2011)
Liu, L., Chen, X.Y.: Reconfiguration of distribution networks based on fuzzy genetic algorithms. CSEE Proc. 20, 66–69 (2000)
Ahuja, A., Das, S., Pahwa, A.: An AIS-ACO hybrid approach for multi-objective distribution system reconfiguration. IEEE Trans. Power Syst. 22, 1101–1111 (2007)
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Mosbah, M., Arif, S., Mohammedi, R.D., Zine, R. (2018). Optimal Reconfiguration of an Algerian Distribution Network in Presence of a Wind Turbine Using Genetic Algorithm. In: Hatti, M. (eds) Artificial Intelligence in Renewable Energetic Systems. ICAIRES 2017. Lecture Notes in Networks and Systems, vol 35. Springer, Cham. https://doi.org/10.1007/978-3-319-73192-6_41
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DOI: https://doi.org/10.1007/978-3-319-73192-6_41
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