Optimal sizing and location of distributed generation for power loss minimization using bee colony algorithm
Recently, the rapid growth development of the Distribution system has caused the problem arising due to the usage Distributed Generation (DG). The DG units have a few advantages, for example reduced distribution losses, improve the voltage profile, reduced capacity costs and the most important thing...
Saved in:
Main Author: | |
---|---|
Format: | text::Final Year Project |
Language: | English |
Published: |
2023
|
Subjects: | |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
id |
my.uniten.dspace-20443 |
---|---|
record_format |
dspace |
spelling |
my.uniten.dspace-204432024-09-02T11:36:47Z Optimal sizing and location of distributed generation for power loss minimization using bee colony algorithm Mohamad Zunnurain Fauzi Distribution generation Recently, the rapid growth development of the Distribution system has caused the problem arising due to the usage Distributed Generation (DG). The DG units have a few advantages, for example reduced distribution losses, improve the voltage profile, reduced capacity costs and the most important thing being environmentally friendly. All these advantages are very important in solving the issues arise in the Distribution system. However, the misplacement of the DG location and incorrectly DG size chosen will lead to another problem network. There are many methods that can be used for power losses minimization such as Firefly Algorithm (FA), Ant Colony Optimization (ACO) and B-losses coefficient. Therefore, a method which is Artificial Bee Colony (ABC) algorithm is proposed in this project for the optimal location and size of DG used in minimizing power losses and improve voltage profile. The minimization of power losses and the improvement of the voltage stability are important considerations as the power system will be more efficient and the quality of the performance will increase while supplying electricity to the customer. The ABC algorithm method has been implemented into the test system of IEEE 33 bus system which is showed in 3 cases. The first case the system will operate without DG installation and the rest of the cases system will operate with single and multiple DG installation with specified power factor. MATLAB is used by the assigned ABC algorithm to run the programme. This project performance has been compared with single and multiple DG installation as the system operate without DG installation being a reference point and the project showed the best result. The comparison between single and multiple DG installation showed the multiple DG installation is better for power losses minimization. 2023-05-03T15:01:05Z 2023-05-03T15:01:05Z 2020-02 Resource Types::text::Final Year Project https://irepository.uniten.edu.my/handle/123456789/20443 en application/pdf |
institution |
Universiti Tenaga Nasional |
building |
UNITEN Library |
collection |
Institutional Repository |
continent |
Asia |
country |
Malaysia |
content_provider |
Universiti Tenaga Nasional |
content_source |
UNITEN Institutional Repository |
url_provider |
http://dspace.uniten.edu.my/ |
language |
English |
topic |
Distribution generation |
spellingShingle |
Distribution generation Mohamad Zunnurain Fauzi Optimal sizing and location of distributed generation for power loss minimization using bee colony algorithm |
description |
Recently, the rapid growth development of the Distribution system has caused the problem arising due to the usage Distributed Generation (DG). The DG units have a few advantages, for example reduced distribution losses, improve the voltage profile, reduced capacity costs and the most important thing being environmentally friendly. All these advantages are very important in solving the issues arise in the Distribution system. However, the misplacement of the DG location and incorrectly DG size chosen will lead to another problem network. There are many methods that can be used for power losses minimization such as Firefly Algorithm (FA), Ant Colony Optimization (ACO) and B-losses coefficient. Therefore, a method which is Artificial Bee Colony (ABC) algorithm is proposed in this project for the optimal location and size of DG used in minimizing power losses and improve voltage profile. The minimization of power losses and the improvement of the voltage stability are important considerations as the power system will be more efficient and the quality of the performance will increase while supplying electricity to the customer. The ABC algorithm method has been implemented into the test system of IEEE 33 bus system which is showed in 3 cases. The first case the system will operate without DG installation and the rest of the cases system will operate with single and multiple DG installation with specified power factor. MATLAB is used by the assigned ABC algorithm to run the programme. This project performance has been compared with single and multiple DG installation as the system operate without DG installation being a reference point and the project showed the best result. The comparison between single and multiple DG installation showed the multiple DG installation is better for power losses minimization. |
format |
Resource Types::text::Final Year Project |
author |
Mohamad Zunnurain Fauzi |
author_facet |
Mohamad Zunnurain Fauzi |
author_sort |
Mohamad Zunnurain Fauzi |
title |
Optimal sizing and location of distributed generation for power loss minimization using bee colony algorithm |
title_short |
Optimal sizing and location of distributed generation for power loss minimization using bee colony algorithm |
title_full |
Optimal sizing and location of distributed generation for power loss minimization using bee colony algorithm |
title_fullStr |
Optimal sizing and location of distributed generation for power loss minimization using bee colony algorithm |
title_full_unstemmed |
Optimal sizing and location of distributed generation for power loss minimization using bee colony algorithm |
title_sort |
optimal sizing and location of distributed generation for power loss minimization using bee colony algorithm |
publishDate |
2023 |
_version_ |
1809152807536689152 |
score |
13.214268 |