A comparative study of optimization methods for 33kV distribution network feeder reconfiguration
Distribution Network Reconfiguration (DNR) has been a part of importance strategies in order to reduce the power losses in the electrical network system. Due to the increase of demand for the electricity and high cost maintenance, feeder reconfiguration has become more popular issue to discuss. In...
Saved in:
Main Authors: | , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Research India Publications
2014
|
Subjects: | |
Online Access: | http://eprints.utem.edu.my/id/eprint/12894/1/2014_-_A_Comparative_Study_of_Optimization_Methods_for_33kV.pdf http://eprints.utem.edu.my/id/eprint/12894/ https://www.ripublication.com/ijaerv6/ijaerv9n9_15.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Summary: | Distribution Network Reconfiguration (DNR) has been a part of importance strategies in order to reduce the power losses in the electrical network system. Due to the increase of demand for the electricity and high cost maintenance,
feeder reconfiguration has become more popular issue to discuss. In this paper, a comparative study has been made by using several optimization methods which are Artificial Bee Colony (ABC), Particle Swarm Optimization (PSO) and Genetic Algorithm (GA). The objectives of this study are to compare the performance in terms of Power Losses Reduction (PLR), percentage of Voltage Profile Improvement (VPI), and Convergence Time (CT) while select the best method as a suggestion for future research. The programming has been simulated in MATLAB environment and IEEE 33-bus system is used for real testing. ABC method has shown the superior results in the analysis of two objectives function. The suggestion has been concluded and it is hoped to help the power system engineer in deciding a better feeder arrangement in the future. |
---|