Open Access Open Access  Restricted Access Subscription or Fee Access

Fuzzy Satisfied Multiobjective Distribution Network Reconfiguration: an Application of Adaptive Weighted Improved Discrete Particle Swarm Optimization

(*) Corresponding author

Authors' affiliations



In this paper, a multiobjective framework for distribution network reconfiguration (DNR) is developed in the fuzzy domain to minimize power loss and improve load balancing. Since it is a nonlinear and combinatorial optimization problem a new fangled adaptive weighted improved discrete particle swarm optimization (AWIDPSO) algorithm is exercised. In this formulation each objective is normalized using fuzzy membership function, these are combined with the appropriate weight factor and maximized during the course of the iteration. In order to obtain high-quality solutions within lesser executing time, the constraint violations are handled perfectly so that intern produces a stable convergence characteristic. In this study, a 33-bus system is analyzed for optimum reconfiguration using the developed framework. Comparison of the simulated results with the results of well known prudent optimization technique confirms the applicability of the AWIDPSO algorithm for DNR problem.
Copyright © 2017 Praise Worthy Prize - All rights reserved.


Network Reconfiguration; Power Loss Reduction; Load Balancing; Fuzzified Multiobjective; Metaheuristic Algorithm

Full Text:



M. E. Baran, and F. F. Wu, Network reconfiguration in distribution systems for loss reduction and load balancing, IEEE Transactions on Power Delivery, Vol.4 (Issue 2): 1401-1407, April 1989.

H. D. Chiang, and R. J. Jumeau, Optimal Network Reconfigurations in Distribution Systems: Part 2: Solution Algorithms and Numerical Results, IEEE Transactions on Power Delivery, Vol. 5 (Issue 3): 1568-1574, July 1990.

C. T. Sua, C.F. Chang, and J. P. Chiou, Distribution network reconfiguration for loss reduction by ant colony search algorithm, Electric Power Systems Research, Vol. 75 (Issue 2-3): 190–199, August 2005.

K. Sathish Kumar, and T. Jayabarathi, Power system reconfiguration and loss minimization for a distribution system using bacterial foraging optimization algorithm, Electrical Power and Energy Systems, Vol. 36 (Issue 1): 13-17, March 2012.

T. T. Nguyen, and A. V. Truong, Distribution network reconfiguration for power loss minimization and voltage profile improvement using cuckoo search algorithm, Electrical Power and Energy Systems, Vol. 68: 233–242, June 2015.

Z. Li, Y. Bao, Y. Han, C. Guo, W.Wang, and Y.Xie, Multi objective distribution network reconfiguration based on system homogeneity, IEEE PES Asia-Pasific Power and Energy Engineering Conference, 1-5, November 2015.

D. SudhaRani, N. Subrahmanyam, and M. Sydulu, MultiObjective Invasive Weed Optimization –An application to optimal network reconfiguration in radial distribution systems, Electrical Power and Energy Systems, Vol. 73: 932–942, December 2015.

R. Syahputra, I. Robandi, and M. Ashari, PSO Based Multiobjective Optimization for Reconfiguration of Radial Distribution Network, International Journal of Applied Engineering Research, Vol 10 (Issue 6): 14573-14586. June 2015.

J. Z. Zhu, Optimal reconfiguration of electrical distribution network using the refined genetic algorithm, Electric Power Systems Research, Vol. 62 (Issue 1): 37-42, May 2002.

D. Das, Reconfiguration of distribution system using fuzzy multiobjective approach, Electrical Power and Energy Systems, Vol. 28 (Issue 5): 331–338, June 2006.

E. M. Carreno, R. Romero, and A. P. Feltrin, An Efficient Codification to Solve Distribution Network Reconfiguration for Loss Reduction Problem, IEEE Transactions on Power Systems, Vol. 23 (Issue 4): 1542-1551, November 2008.

T. Niknam, E. Azad Farsani and M. Nayeripour, An efficient multiobjective modified shuffled frog leaping algorithm for distribution feeder reconfiguration problem, European Transactions on Electrical Power, Vol. 21 (Issue 1): 721-739, January 2010.

S. H. Mirhoseini, S. M. Hosseini, M. Ghanbari, and M. Ahmadi, A new improved adaptive imperialist competitive algorithm to solve the reconfiguration problem of distribution systems for loss reduction and voltage profile improvement, Electrical Power and Energy Systems, Vo. 55: 128–143, February 2014.

S. K. Naveen, K. Sathish Kumar, and K. Rajalakshmi, Distribution system reconfiguration for loss minimization using modified bacterial foraging optimization algorithm, Electrical Power and Energy Systems, Vol. 69: 90–97, July 2015.

T. Niknam, An efficient hybrid evolutionary algorithm based on PSO and HBMO algorithms for multiobjective Distribution Feeder Reconfiguration, Energy Conversion and Management, Vol. 50 (Issue 8): 2074–2082, August 2009.

A. Saffar, R. Hooshmand, and A. Khodabakhshian, A new fuzzy optimal reconfiguration of distribution systems for loss reduction and load balancing using ant colony search-based algorithm, Applied Soft Computing, Vol. 11 (Issue 5): 4021–4028, July 2011.

M. Sedighizadeh, S. Ahmadi, and M. Sarvi, An Efficient Hybrid Big Bang–Big Crunch Algorithm for Multiobjective Reconfiguration of Balanced and Unbalanced Distribution Systems in Fuzzy Framework, Electric Power Components and Systems, Vol. 41 (Issue 1): 75–99, January 2013.

M. Sedighizadeh. and R. Bakhtiary, Optimal multiobjective reconfiguration and capacitor placement of distribution systems with the Hybrid Big Bang–Big Crunch algorithm in the fuzzy framework, Ain Shams Engineering Journal, Vol. 7 (Issue 1): 113–129, March 2016.

K. Rameshkumar, R. K. Suresh, and K. M. Mohanasundaram, Discrete Particle Swarm Optimization (DPSO) Algorithm for Permutation Flow shop Scheduling to Minimize Make-span, Advances in Natural Computation, LNCS, Vol. 3612: 572-581, 2005.

M. Li, B. Wu, P. Yi, C. Jin, Y. Hu, and T. Shi, An improved discrete particle swarm optimization algorithm for high-speed trains assembly sequence planning, Assembly Automation, Vol. 33 (Issue 4): 360 – 373, 2013.

Damiano, A., Gatto, G., Marongiu, I., Meo, S., Perfetto, A., Serpi, A., Single-stage grid connected PV inverter with active and reactive power flow control via PSO-PR based current controlled SVPWM, (2012) International Review of Electrical Engineering (IREE), 7 (4), pp. 4647-4654.

Esposito, F., Isastia, V., Meo, S., PSO based energy management strategy for pure electric vehicles with dual energy storage systems, (2010) International Review of Electrical Engineering (IREE), 5 (5), pp. 1862-1871.

Del Pizzo, A., Meo, S., Brando, G., Dannier, A., Ciancetta, F., An energy management strategy for fuel-cell hybrid electric vehicles via particle swarm optimization approach, (2014) International Review on Modelling and Simulations (IREMOS), 7 (4), pp. 543-553.

Meo, S., Zohoori, A., Vahedi, A., Optimal design of permanent magnet flux switching generator for wind applications via artificial neural network and multi-objective particle swarm optimization hybrid approach, (2016) Energy Conversion and Management, 110, pp. 230-239.


  • There are currently no refbacks.

Please send any question about this web site to
Copyright © 2005-2023 Praise Worthy Prize