A 33kV Distribution Network Feeder Reconfiguration byUsing REPSO for Voltage Profile Improvement

The complexity of modern power system has contributed to the high power losses and over load in the distribution network. Due to that reason, Feeder Reconfiguration (FR) is required to identify the best topology network in order to fulfill the power demand with reduced power losses while stabilizing the magnitude of voltage. This paper addresses a new optimization method which is called as Rank Evolutionary Particle Swarm Optimization (REPSO). It has been produced by a hybridization of the conventional Particle Swarm Optimization (PSO) and the traditional Evolutionary Programming (EP) algorithm. The main objective of this paper is to improve the voltage profile while solves the overload problem by reducing the power losses respectively. The proposed method has been implemented and the real power losses in the 33kVdistribution system has been investigated and analyzed accordingly. The results are compared to the conventional Genetic Algorithm (GA), EP and PSO techniques and it is hoped to help the power system engineer in securing the network in the future.

[1]  G. Peponis,et al.  Reconfiguration of radial distribution networks: application of heuristic methods on large-scale networks , 1995 .

[2]  P. J. Angeline,et al.  Using selection to improve particle swarm optimization , 1998, 1998 IEEE International Conference on Evolutionary Computation Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98TH8360).

[3]  Mauro Birattari,et al.  Swarm Intelligence , 2012, Lecture Notes in Computer Science.

[4]  Wang Jiaying,et al.  A modified particle swarm optimization algorithm , 2005 .

[5]  Felix F. Wu,et al.  Network Reconfiguration in Distribution Systems for Loss Reduction and Load Balancing , 1989, IEEE Power Engineering Review.

[6]  Vladimiro Miranda,et al.  EPSO-evolutionary particle swarm optimization, a new algorithm with applications in power systems , 2002, IEEE/PES Transmission and Distribution Conference and Exhibition.

[7]  Toshiyuki Sawa,et al.  Radial network reconfiguration method in distribution system using mutation Particle Swarm Optimization , 2009, 2009 IEEE Bucharest PowerTech.

[8]  Men-Shen Tsai,et al.  Application of Grey Correlation Analysis in Evolutionary Programming for Distribution System Feeder Reconfiguration , 2010, IEEE Transactions on Power Systems.

[9]  H. Mokhlis,et al.  Network reconfiguration for loss reduction with distributed generations using PSO , 2012, 2012 IEEE International Conference on Power and Energy (PECon).

[10]  Jae-Chul Kim,et al.  Network reconfiguration at the power distribution system with dispersed generations for loss reduction , 2000, 2000 IEEE Power Engineering Society Winter Meeting. Conference Proceedings (Cat. No.00CH37077).

[11]  Cui-Ru Wang,et al.  DISTRIBUTION NETWORK RECONFIGURATION BASED ON MODIFIED PARTICLE SWARM OPTIMIZATION ALGORITHM , 2006 .

[12]  Hazlie Mokhlis,et al.  A DNR Using Evolutionary PSO for Power Loss Reduction , 2013 .

[13]  S. Kamakshaiah,et al.  Global optimal solution for network reconfiguration problem using AMPSO algorithm , 2012, 2012 IEEE International Conference on Power System Technology (POWERCON).

[14]  N. Kamaraj,et al.  Optimal Location of Multi Type Facts Devices for Multiple Contingencies Using Particle Swarm Optimization , 2008 .

[15]  H. Mokhlis,et al.  Discrete evolutionary programming to solve network reconfiguration problem , 2013, IEEE 2013 Tencon - Spring.

[16]  Russell C. Eberhart,et al.  A discrete binary version of the particle swarm algorithm , 1997, 1997 IEEE International Conference on Systems, Man, and Cybernetics. Computational Cybernetics and Simulation.

[17]  P Rezaei,et al.  Distribution system efficiency improvement by reconfiguration and capacitor placement using a modified particle swarm optimization algorithm , 2010, 2010 IEEE Electrical Power & Energy Conference.

[18]  D. Shirmohammadi,et al.  Reconfiguration of electric distribution networks for resistive line losses reduction , 1989 .

[19]  Naing Win Oo.  A comparison study on particle swarm and Evolutionary Particle Swarm Optimization using capacitor placement problem , 2008, 2008 IEEE 2nd International Power and Energy Conference.

[20]  J. J. Grainger,et al.  Distribution feeder reconfiguration for loss reduction , 1988 .

[21]  Bruno Canizes,et al.  Reactive power compensation by EPSO technique , 2010, 2010 IEEE International Conference on Systems, Man and Cybernetics.