Network Reconfiguration for Load Balancing in Distribution System with Distributed Generation and Capacitor Placement
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 32807
Network Reconfiguration for Load Balancing in Distribution System with Distributed Generation and Capacitor Placement

Authors: T. Lantharthong, N. Rugthaicharoencheep

Abstract:

This paper presents an efficient algorithm for optimization of radial distribution systems by a network reconfiguration to balance feeder loads and eliminate overload conditions. The system load-balancing index is used to determine the loading conditions of the system and maximum system loading capacity. The index value has to be minimum in the optimal network reconfiguration of load balancing. A method based on Tabu search algorithm, The Tabu search algorithm is employed to search for the optimal network reconfiguration. The basic idea behind the search is a move from a current solution to its neighborhood by effectively utilizing a memory to provide an efficient search for optimality. It presents low computational effort and is able to find good quality configurations. Simulation results for a radial 69-bus system with distributed generations and capacitors placement. The study results show that the optimal on/off patterns of the switches can be identified to give the best network reconfiguration involving balancing of feeder loads while respecting all the constraints.

Keywords: Network reconfiguration, Distributed generation Capacitor placement, Load balancing, Optimization technique

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1076546

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4172

References:


[1] D. Das, "A fuzzy multiobjective approach for network reconfiguration of distribution systems," IEEE Trans. Power Delivery, vol. 21, no 1, pp. 1401-1407, Jan. 2006.
[2] P. Ravibabu, K. Venkatesh, and C. S. Kumar, "Implementation of genetic algorithm for optimal network reconfiguration in distribution systems for load balancing," in Proc Conf. Computation Technology in Electrical and Electronics Engineering, Novosibirsk, 2008, pp.124-128.
[3] C. T. Su, and C. S. Lee, "Network reconfiguration of distribution systems using improved mixed-integer hybrid differential evolution," IEEE Trans. Power Delivery, vol. 18, no. 3, pp. 1022-1027, July 2003.
[4] Y. K. Wu, and et al., "Study of Reconfiguration for the distribution system with distributed generators," IEEE Trans. Power Delivery, vol. 25, no. 3, pp. 1678-1685, July 2010.
[5] E. Carpaneto, G. Chicco, and J. S. Akilimali, "Branch current decomposition method for loss allocation in radial distribution systems with distributed generation," IEEE Trans. Power Systems, vol. 21, no. 3, pp. 1170-1179, Aug. 2006.
[6] H. Kim, Y. ko, and K. H. Jung, "Artificial neural network based feeder reconfiguration for loss reduction in distribution systems," IEEE Trans Power Delivery, vol. 8, no. 3, pp. 1356-1366, July 1993.
[7] T. Taylor, and D. Lubkeman, "Implementation of heuristic search strategies for distribution feeder reconfiguration," IEEE Trans Power Delivery, vol. 5, no. 1, pp.239-246, Jan. 1990.
[8] M. A. Kashem, V. Ganapathy, and G. B. Jasmon, "Network reconfiguration for load balancing in distribution networks," IEE Proc.- Gener. Transm. Distrib., vol. 146, no. 6, pp. 563-567, Nov. 1999.
[9] K. Aoki, and et al., "An efficient algorithm for load balancing of transformers and feeders," IEEE Trans. Power Delivery, vol. 3, no. 4, pp. 1865-1872, Oct. 1988.
[10] M. E. Baran, and F. F. Wu, "Network reconfiguration in distribution systems for loss reduction and load balancing," IEEE Trans. Power Delivery, vol. 4, no. 2, pp. 1401-1407, Apr. 1989.
[11] H. D. Chiang, and R.J Jumeau, "Optimal network reconfigurations in distribution systems: Part 1: A new formulation and a solution methodology," IEEE Trans. Power Delivery, vol. 5, no. 4, pp. 1902- 1909, Nov. 1990.
[12] G. Pepionis, and M. Papadopoulos, "Reconfiguration of radial distribution networks: application of heuristic methods on largescale networks,"IEE Proc., Gener., Transm. Distrib, vol. 142, no. 6, pp. 631 - 638, Nov. 1995.
[13] Mukwanga and et al., "Reconfiguration and load balancing in the LV and MV distribution networks for optimal performance," IEEE Trans. on Power Delivery, vol. 22, no. 4, pp. 2534-1407, Oct. 2007.
[14] G. K. V. Raju, and P.R. Bijwe, "Efficient reconfiguration of balanced and unbalanced distribution systems for loss minimization," IEE Proc.- Gener. Transm. Distrib., vol. 2, no. 1, pp. 7-12, Jan. 2008.
[15] H. A. Gil, and G. Joos, "Models for quantifying the economic benefits of distributed generation," IEEE Trans. Power Systems, vol. 23, no 2, pp. 327- 335, May 2008.
[16] G. Levitin, and et al., "Optimal capacitor allocation in distribution systems using a genetic algorithm and a fast energy loss computation technique," IEEE Trans. on Power Delivery, vol. 15, no 2, pp. 623-628, Oct. 2000.
[17] V. H. M. Quezada, J. R. Abbad, and T. G. S. Roman, "Assessment of energy distribution losses for increasing penetration of distributed generation," IEEE Trans. Power Systems, vol. 21, no. 2, pp. 533-540, May 2006.
[18] B. Dengiz, and C. Alabas, "Simulation optimization using tabu search," in Conf. Winter Simulation, 2000, pp. 805-810.
[19] F. Glover, "Tabu search-part I," ORSA J. Computing, vol. 1, no.3, 1989.
[20] H. Mori, and Y. Ogita, "Parallel tabu search for capacitor placement in radial distribution system," in Conf. Power Engineering Society Winter Meeting, 2002, pp 2334-2339.
[21] J. S. Savier, and D. Das, "Impact of network reconfiguration on loss allocation of radial distribution systems," IEEE Trans. Power Delivery, vol. 22, no. 4, pp. 2473-2480, Oct. 2007.