Reconfiguration and Capacitor Placement Using Opposition Based Differential Evolution Algorithm in Power Distribution System

R. Muthu Kumar(1*), K. Thanushkodi(2)

(1) Anna University, Chennai, India
(2) E&I, EEE, CSE & IT Departments at Government College of Technology, Coimbatore, India
(*) Corresponding author

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Distribution system is a critical link between customer and utility. The control of power loss is the main factor which decides the performance of the distribution system. There are two methods such as (i) distribution system reconfiguration and (ii) inclusion of capacitor banks, used for controlling the real power loss. Distribution system reconfiguration helps to operate the system at minimum cost and at the same time improves the system reliability and security. Under normal operating conditions, optimization of network configuration is the process of changing the topology of distribution system by altering the open/closed status of switches to find a radial operating structure that minimizes the system real power loss while satisfying operating constraints.Considering the improvement in voltage profile with the power loss reduction, later method produces better performance than former method. This paper presents an advanced evolutionary algorithm for capacitor inclusion for loss reduction. The conventional sensitivity analysis is used to find the optimal location for the capacitors. In order to achieve a better approximation for the current candidate solution, Opposition based Differential Evolution (ODE) is introduced. The effectiveness of the proposed technique is validated through IEEE-33 bus Power Distribution systems.
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Capacitor Placement; Distribution Network Reconfiguration; Differential Evolution; Loss Reduction; Switching Operation

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S. Civanlar, J. J. Grainger, H. Yin, and S. S. H. Lee, “Distribution feeder reconfiguration for loss reduction,” IEEE Trans. Power Del., vol. 3, no. 3, pp. 1217–1223, Jul. 1988.

Baran ME and Wu FF, ‘Network reconfiguration in distribution systems for loss reduction and load balancing,” IEEE Trans. Power Del., vol. 4, no. 1, pp. 401-1407, Jan. 1989.

Aoki K, Kawabara H, and Satoh. M, “An efficient algorithm for load balancing of transformers and feeders,” IEEE Trans. Power Del., vol. 3, no. 4, pp. 1865-1872, Jul. 1988.

D. Shirmohammadi and H.W. Hong, “Reconfiguration of electric distribution networks for resistive line losses reduction,” IEEE Trans. Power Del., vol. 4, no. 2, pp. 1492–1498, Apr. 1989.

H. C. Cheng and C. C. Ko, “Network reconfiguration in distribution systems using simulated anealing”, Elect. Power Syst. Res., vol. 29, pp. 227-238, May 1994.

K. Huang and H. Chin, “Distribution feeder energy conservation by using heuristics fuzzy approach,” Electrical Power and Energy Systems, vol. 24,pp. 439-445, 2002.

H. Salazar, R. Gallego, and R. Romero, “Artificial neural networks and clustering techniques applied in the reconfiguration of distribution sys- tems,” IEEE Trans. Power Del., vol. 21, no. 3, pp. 1735–1742, 2006.

Ying-Yi .H and Saw-Yu .H, “Determination of network configuration considering multiobjective in distribution systems using genetic algorithms”, IEEE Trans. on Power Sys., vol. 20, no. 2, pp. 1062-1069, 2006.

K. Qin and P. N. Suganthan, “Self-adaptive differential evolution algorithm for numerical optimization,” in Proc. IEEE Congr. Evolut. Comput., Edinburgh, Scotland, , pp. 1785–1791, 2005

Wang and H.Z. Cheng, “Optimization of Network configuration in Large distribution systems using plant growth simulation algorithm,” IEEE Trans. Power Syst., vol.23, No. 1, pp. 119-126, 2008.

R. Srinivasa Rao, S. V. L. Narasimham, M. Ramalinga Raju, and A. Srinivasa Rao, “Optimal network reconfiguration of large-scale distribution system using harmony search algorithm,” IEEE Trans. on Power Systems, vol. 26, no. 3, pp. 1080–1088, 2011.

Schmill JV. Optimum size and location of shunt capacitors on distribution feeders. IEEE Trans Power Apparat Syst; 84:825–32, 1965.

Duran H. Optimum number, location and size of shunt capacitors in radial distribution feeders: a dynamic programming approach. IEEE Trans Power Apparat Syst.., 87:1769–74, 1968.

Grainger JJ, Lee SH, “ Optimum size and location of shunt capacitors for reduction of losses on distribution feeders”, IEEE Trans Power Apparat Syst;100(3):1105–18, 1981.

Das D, “ Reactive power compensation for radial distribution networks using genetic algorithms”, Electrical Power Energy Syst.,24:573–81, 2002.

B. A. Souza, H. N. Alves, and H. A. Ferreira, “Microgenetic algorithms and fuzzy logic applied to the optimal placement of capacitor banks in distribution networks,” IEEE Trans. Power Syst., vol. 19, no. 2, pp. 942–947, May 2004.

Prakash K, Sydulu M, “Particle swarm optimization based capacitor placement on radial distribution systems” IEEE power engineering society, general meeting; 2007. p. 1–5.

Srinivasas Rao R, Narasimham S.V.L, Ramalingaraju M, “Optimal capacitor placement in a radial distribution system using Plant Growth Simulation Algorithm”, Electrical Power Energy Syst 2011;33: 1133-1139.

M. J. Kasaei and M. Gandomkar, “Loss Reduction in Distribution Network Using Simultaneous Capacitor Placement and Reconfiguration With Ant Colony Algorithm”, IEEE Proceeding, DOI: 978-1-4244-4813-5/10, 2010.

Sedighizadeh, M., Arzaghi-Haris, D., Optimal allocation and sizing of capacitors to minimize the distribution line loss and to improve the voltage profile using Big Bang-Big Crunch optimization, (2011) International Review of Electrical Engineering (IREE), 6 (4), pp. 2013-2019.

Diana P. Montoya and Juan M, “Reconfiguration and optimal capacitor placement for losses reduction”, IEEE Proceedings, DOI: 978-1-4673-2673-5, 2012.

Farahai, Behrooz and Hossein, “Reconfiguration and capacitor placement simultaneously for energy loss reduction based on an improved reconfiguration method,” IEEE Trans. Power Syst., vol. 27, no. 2, pp. 587-595 , May 2012.

S. Rahnamayan, R. Tizhoosh, and M. A. Salama, “Opposition-Based Differential Evolution,” IEEE Trans. on Evolutionary Computation, vol. 12, no. 1, pp. 64-79, 2008.


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