Optimization of network reconfiguration by using Particle swarm optimization

Reconfiguration of radial distribution system is a significant way of altering the power flow through the lines. This paper presents a novel method to interpret the network reconfiguration problem with an objective of minimizing real power loss and simultaneously, improving the voltage profile in radial distribution system (RDS). A Meta-heuristic Particle swarm optimization (PSO) is used to reconfigure and recognize the optimal tie switches for reduction of real power loss in a radial distribution system. Different scenarios of reconfiguration of distributed network are precise to study the performance of the proposed technique. The constraints of voltage and branch current carrying capacity are incorporated in the assessment of the objective function. The proposed method has been tested on IEEE 33-bus and 69-bus systems at different load patterns to demonstrate the performance and effectiveness of the predictable method. The outcomes attained, illustrates that improvement in voltages and a reduction in the real power loss.

[1]  Felix F. Wu,et al.  Network reconfiguration in distribution systems for loss reduction and load balancing , 1989 .

[2]  Bala Venkatesh,et al.  Optimal radial distribution system reconfiguration using fuzzy adaptation of evolutionary programming , 2003 .

[3]  Hsiao-Dong Chiang,et al.  Optimal network reconfigurations in distribution systems. II. Solution algorithms and numerical results , 1990 .

[4]  Mostafa Sedighizadeh,et al.  Optimal reconfiguration and capacitor placement for power loss reduction of distribution system using improved binary particle swarm optimization , 2014 .

[5]  K. Sathish Kumar,et al.  Distribution system reconfiguration for loss minimization using modified bacterial foraging optimization algorithm , 2015 .

[6]  R. Taleski,et al.  Distribution network reconfiguration for energy loss reduction , 1997 .

[7]  Debapriya Das Reconfiguration of distribution system using fuzzy multi-objective approach , 2006 .

[8]  M. Damodar Reddy,et al.  A two-stage methodology of optimal capacitor placement for the reconfigured network , 2010 .

[9]  H. Chiang,et al.  Optimal network reconfigurations in distribution systems. I. A new formulation and a solution methodology , 1990 .

[10]  Men-Shen Tsai,et al.  Application of Enhanced Integer Coded Particle Swarm Optimization for Distribution System Feeder Reconfiguration , 2011, IEEE Transactions on Power Systems.

[11]  Hoyong Kim,et al.  Artificial neural-network based feeder reconfiguration for loss reduction in distribution systems , 1993 .

[12]  K. Ravindra,et al.  Power Loss Minimization in Distribution System Using Network Reconfiguration in the Presence of Distributed Generation , 2013, IEEE Transactions on Power Systems.