A Comparative Study of Optimization Methods for 33kV Distribution Network Feeder Reconfiguration.
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Based on the review, distribution network reconfiguration is important to minimize losses and improve voltage and service restoration helps to restore as many loads as
The literature review is past studies related to EP method, GA method and DNR system which is about reducing the power losses, improving the voltage profile
“ I hereby declare that I have read through this report entitle “Minimizing Power Losses by Using Improved Genetic Algorithm for Distribution Network Reconfiguration (DNR)” and
In this study network reconfiguration was carried out using genetic algorithm based optimization methods.. This algorithm is a popular algorithm in
Acronyms ABC: Artificial bee colony ACO: Ant colony optimization AI: Artificial intelligence AIS: Artificial immune system ANN: Artificial neural network BA: Bat algorithm BBO:
Several evolutionary optimization techniques; such as ant colony optimization [4], particle swarm optimization PSO [5,6], Taguchi optimization [7], invasive weed optimization [8],
Omar Muhammed Neda Chaotic Particle Swarm Optimization for Solving Reactive Power Optimization Problem enhancing the voltage profile of the power system through a proper alteration
This paper discusses application of the algorithm to the training of artificial neural network weights, Particle swarm optimization has also been demonstrated to perform well on genetic
