Real Power Loss Reduction in Distribution System by Optimal placement of Distributed Generation after Network Reconfiguration using Genetic Algorithm
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Power loss reduction is one of the main targets in power industry and so in this paper, the problem of finding the optimal configuration and optimal allocation of Distributed Generation in a radial distribution system is considered. Optimal Network Reconfiguration and identification of the optimal location and sizing of Distributed Generation gives the reduction in power losses and the improvement in voltage profile. Genetic Algorithm is used to find the optimal reconfiguration, Distributed Generation size and location and also find the losses at the condition with Distributed Generation and with Reconfiguration. The method has been tested on 33-bus radial distribution system to demonstrate the performance and effectiveness of the proposed method.
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A. Merlin, H. Back, “Search for a minimal-loss operating spanning tree configuration in an urban power distribution system, Proceedings of 5th Power System Corporation Conference (PSCC). Cambridge, UK, 1975, pp. 1-18.
M. E. Baran, F. F. Wu, “Network reconfiguration in distribution systems for loss reduction and load balancing, IEEE Trans. Power Del., vol. 4, no. 2, pp. 1401-1407, Apr. 1989.
S. Civanlar, J. J. Grainger, H. Yin, and S. S. H. Lee, “Distrbution feeder reconfiguration for loss reduction, IEEE Trans. Power Delivery, vol. 3, no. 3, pp. 1217-1223, Jul. 1988.
D. Shirmohammadi and H. W. Hong, “Reconfiguration of electric distribution networks for resistive line loss reduction, IEEE Trans. Power Delivery, vol. 4, no. 2, pp. 1492-1498, Apr. 1989
J. Fan, L. Zhang, D. McDonald, “Distribution network reconfiguration single loop optimization, IEEE Trans. On Power Syst. 2(3) 1996.
H. D. Chang, R. J. Jumeau, “Optimal network reconfiguration in distribution systems, part la new formulation and a solution methodology, IEEE Trans. Power Delivery, 5(4) (1990) 1902_/1909.
K. Nara, A. Shiose, M. Kitagawa, T. Ishihara, “Implementation of genetic algorithm for distribution system loss minimum configuration, IEEE Trans. Power Systems 7(3) (1992) 1044_/1051.
S. K. Goswami, S. K. Basu, “A new algorithm for the reconfiguration of distribution feeders for loss minimization, IEEE Trans. On Power Delivery, volume 7, N0 3, July 1992.
R. Srinivasa Rao, S. V. L. Narasimham, “A new heuristic approach for optimal network reconfiguration in distribution systems, International Journal of Applied Science, Engineering and Technology 5(1) (2009).
M. A. Kashem, V. Ganapathy, G. B. Jamson, and M. I. Buhari, “A Novel model for loss minimization in distribution networks, IEEE International Power Technologies 2000 Conference on Electric Utility deregulation restructuring at City University London, 4-7 April 2000, pp. 251-256.
Jazebi, S., Jazebi, S., Rashidinejad, M., Application of a novel real genetic algorithm to accelerate the distribution network reconfiguration, (2009) International Review of Electrical Engineering (IREE), 4 (1), pp. 114-121.
W. Rosehart and E. Nowicki, “Optimal placement of disributed generation, in Proc. 14th Power Systems Computations Conf., Servilla, 2002, pp. 1-5, Section 11, paper 2.
C. Wang and M. H. Nehir, “Analytical approaches for optimal placement of distributed generation sources in power systems, IEEE Trans. Power Syst.., vol. 19, no. 4, pp. 2068-2076, Nov. 2004.
P. Agalgaonkar, S. V. Kulkurni, S. A. Khaparde, and S. A. Soman, “Placement and penetration of distributed generation under standard market design, Int. J. Emerg. Elect. Power Syst., vol. 1, no. 1, p. 2004.
Abu-Mouti FS, El-Hawary ME. “Heuristic curve-fitted technique for distributedgeneration optimisation in radial distribution feeder systems, IET GenerTransmDistrib 2011;5(2):172–80.
I. Pisică, C. Bulac, L. Toma, M. Eremia, “Optimal SVC placement inelectric power systems using a genetic algorithms based method,” IEEE Bucharest Power Tech Conference, Romania 2009.
Celli G, Ghiani E, Mocci S, Pilo F. “A multi objective evolutionary algorithm forthe sizing and siting of distributed generation, IEEE Trans Power Syst. 2005;20(2):750–7.
M. Sedighizadeh, and A. Rezazadeh,“Using Genetic Algorithm for DistributedGeneration Allocation to Reduce Losses and Improve Voltage Profile, World Academy of Science, Engineering and Technology 37 2008.
I. Pisică, C. Bulac, and M. Eremia, “Optimal Distributed Generation Location and Sizing using Genetic Algorithms, 15th International Conference on Intelligent System Applications to Power Systems, 2009. ISAP '09. 8-12 Nov. 2009.
M.F.Kotb, K.M.Shebl, M. El Khazendar A. El Husseiny “Genetic Algorithm for Optimum Siting andSizing of Distributed Generation, Proceedings of the 14th International Middle East Power Systems Conference (MEPCON’10), Cairo University, Egypt, December 19-21, 2010, Paper ID 196.
Sattianadan, D., Sudhakaran, M., Dash, S.S., Vijayakumar, K., Cost / loss minimization by the placement of DG in distribution system using ga and PSO - A comparative analysis, (2013) International Review of Electrical Engineering (IREE), 8 (2), pp. 769-775.
Porkar, S., Poure, P., Abbaspour-Tehrani-fard, A., Saadate, S., Distributed generation planning for losses, voltage profile, line congestion and total system cost improvement, (2009) International Review of Electrical Engineering (IREE), 4 (3), pp. 434-440.
Khanjanzadeh, A., Sedighizadeh, M., Rezazadeh, A., DG allocation using clonal selection algorithm (CSA) to minimize losses and improve voltage security, (2011) International Review on Modelling and Simulations (IREMOS), 4 (1), pp. 214-219.
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