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226489

Multi-Objective Hybrid Genetic Algorithms and Equilibrium Optimizer GAEO to Integrate Renewable Energy Sources with Distribution Networks

Article

Last updated: 23 Jan 2023

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Abstract

This paper aims to implement the hybrid Genetic Algorithm Equilibrium Optimizer (GAEO) to enhance the overall performance of radial networks using renewable energy resources (RER) based multi-objective optimization. The GAEO is applied to determine the appropriate location, and capacity of RER unit to reduce the line losses, improve the voltage profile, fuel cost and reduce the pollution emission considering inequality constraints. The suggested hybrid GAEO is tested in three different networks with small, medium and large size. The test systems are IEEE-33 bus, IEEE-69 bus and IEEE-118 bus. A comparative study is performed to judge the accuracy of the proposed hybrid GAEO over GA and or EO in terms of fast conversions, and low RER unit capacity. The suggested RER systems are photovoltaic, fuel cell, and wind energy.

DOI

10.21608/aujst.2021.226489

Keywords

Distribution networks, Genetic Algorithms, Equilibrium optimizer, Renewable energy sources, Power loss minimization, Voltage profile, fuel cost minimization, Pollutant emissions

Authors

First Name

Omima

Last Name

Bakry

MiddleName

-

Affiliation

Electrical Engineering Department, Faculty of Engineering, Aswan University, Aswan, Egypt

Email

eng_omima_bakry@yahoo.com

City

-

Orcid

-

First Name

Mostafa

Last Name

Dardeer

MiddleName

-

Affiliation

Electrical Engineering Department, Faculty of Engineering, Aswan University, Aswan, Egypt

Email

mdardeer@aswu.edu.eg

City

-

Orcid

-

First Name

Tomonobu

Last Name

Senjyu

MiddleName

-

Affiliation

Electrical Engineering Department, Faculty of Engineering, Ryukyus University, Japan

Email

a985542@yahoo.co.jp

City

-

Orcid

-

First Name

Salem

Last Name

Alkhalaf

MiddleName

-

Affiliation

Computer Sciences Department, Faculty of Arts and Sciences, Qassim University, Saudi Arabia

Email

s.alkhalaf@qu.edu.sa

City

-

Orcid

-

Volume

1

Article Issue

2

Related Issue

32491

Issue Date

2021-12-01

Receive Date

2022-03-22

Publish Date

2021-12-01

Page Start

34

Page End

69

Print ISSN

2735-3087

Online ISSN

2735-3095

Link

https://aujst.journals.ekb.eg/article_226489.html

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https://aujst.journals.ekb.eg/service?article_code=226489

Order

226,489

Type

Original papers

Type Code

2,312

Publication Type

Journal

Publication Title

Aswan University Journal of Sciences and Technology

Publication Link

https://aujst.journals.ekb.eg/

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Details

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Article

Created At

23 Jan 2023