Beta
43459

OPTIMAL DISTRIBUTED GENERATION PLACEMENT AND SIZING TO REDUCE ACTIVE POWER LOSS USING GA AND ACO ALGORITHM

Article

Last updated: 22 Jan 2023

Subjects

-

Tags

-

Abstract

In this paper, Genetic Algorithm (GA) and Ant colony Algorithm (ACO) optimization techniques
are proposed to find optimal sizing and location for distributed generation in electrical networks.
The objective function of the work relies upon a linearized model to compute the active power
losses as a function of power generators. This strategy based on a strong coupling between active
power and power flow taking into consideration the voltage angles. With the end goal to exhibit
the adequacy of the proposed method, the proposed strategy is applied on IEEE 30-bus standard
systems. Different maximum penetration level capacity of DG units with three ranges such as,
10%, 20% and 30% of maximum power load and various possible places of DG units among
several types of DG (active, reactive or active and reactive power) are considered. Results show
that the optimization tools employing GA and ACO are effective in reducing active power losses
and cost loss by finding the optimal placement and sizing of DG units.

DOI

10.21608/auej.2019.43459

Keywords

Genetic Algorithm, Distributed generation, Planning Of DG, Optimum Allocation Of DG, Genetic algorithm (GA), Ant Colony Algorithm (ACO)

Authors

First Name

Yousef

Last Name

Zakaria

MiddleName

Y

Affiliation

Power andMachines 1Engineering Department , Faculty of Engineering, Arab Academy for Science, Technology& Maritime Transport, Cairo, gypt.

Email

-

City

-

Orcid

-

First Name

Noha

Last Name

El-Amary

MiddleName

H

Affiliation

Power andMachines 1Engineering Department , Faculty of Engineering, Arab Academy for Science, Technology& Maritime Transport, Cairo, gypt.

Email

-

City

-

Orcid

-

First Name

R

Last Name

Swief

MiddleName

A

Affiliation

Electrical Power andMachines 1Engineering Department, Faculty of Engineering, Ain Shams University, Cairo, Egypt

Email

-

City

-

Orcid

-

First Name

Amr

Last Name

Ibrahim

MiddleName

-

Affiliation

Electrical Power andMachines 1Engineering Department, Faculty of Engineering, Ain Shams University, Cairo, Egypt

Email

-

City

-

Orcid

-

Volume

14

Article Issue

52

Related Issue

6641

Issue Date

2019-07-01

Receive Date

2019-08-01

Publish Date

2019-07-01

Page Start

909

Page End

925

Print ISSN

1687-8418

Link

https://jaes.journals.ekb.eg/article_43459.html

Detail API

https://jaes.journals.ekb.eg/service?article_code=43459

Order

26

Type

Original Article

Type Code

706

Publication Type

Journal

Publication Title

Journal of Al-Azhar University Engineering Sector

Publication Link

https://jaes.journals.ekb.eg/

MainTitle

-

Details

Type

Article

Created At

22 Jan 2023