Novel Optimization Techniques for Distribution Systems Reconfiguration
Tabu Search and Particle Swarm Optimization
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This book presents an efficient meta-heuristic method for distribution systems reconfiguration for lower losses and better voltage profile. A modified Tabu Search (MTS) algorithm is used to reconfigure distribution systems so that active power losses are minimized with turning on/off sectionalizing switches. A new method to check the radial topology of the system is presented. Also, the reconfiguration problem is solved using the particle swarm optimizer (PSO), a member of the recently growing swarm intelligent-based algorithms. In most of the PSO publications, the algorithm is used for solvin...
This book presents an efficient meta-heuristic method for distribution systems reconfiguration for lower losses and better voltage profile. A modified Tabu Search (MTS) algorithm is used to reconfigure distribution systems so that active power losses are minimized with turning on/off sectionalizing switches. A new method to check the radial topology of the system is presented. Also, the reconfiguration problem is solved using the particle swarm optimizer (PSO), a member of the recently growing swarm intelligent-based algorithms. In most of the PSO publications, the algorithm is used for solving problems of unconstrained optimization. Consequently, to address the feeder reconfiguration problem, some modifications to the standard PSO are proposed to allow dealing with such highly constrained optimization problem. To verify the effectiveness of the proposed methods, comparative studies are conducted on four test systems with encouraging results. The proposed methods are applied to 16-node, 32-node, 69-node, and 119-node distribution systems. The obtained results are compared with results obtained using other approaches in the previous literature work to examine the performance.
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