226485

Multi-Objective Self-Adaptive a Non-Dominated Sorting Genetic (NSGA) Algorithm for Optimal Sizing of PV/Wind/Diesel Hybrid Microgrid System

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Last updated: 05 Jan 2025

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Abstract

In this article, A mix of different types of micro grid system (Hybrid Micro grid System-HMS) such as solar photovoltaic (PV) power, wind energy (WT), and diesel generators with storage system is presented. Multi-Objective Self-Adaptive a non-dominated sorting genetic (NSGA) algorithm is used to find the optimal sizing of a PV/wind/diesel HMS with battery storage for the city of Yanbu, Saudi Arabia. The problem of optimal component sizing is formulated in multi-objective optimization framework to analyze the Loss of Power Supply Probability (LPSP), the Cost of Electricity (COE), and the Renewable Factor (RF) in relation to HMS cost and reliability considering three objective functions, and is tested using three cases studies involving differing house numbers. The proposed algorithm is carried out on the city of Yanbu with various cases. 

DOI

10.21608/aujst.2021.226485

Keywords

Non-dominated Sorting Genetic Algorithm III, Power loss reduction, renewable factor, cost, renewable energy source

Authors

First Name

Doaa

Last Name

Hasanin

MiddleName

-

Affiliation

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

Email

dodom5335@gmail.com

City

-

Orcid

-

First Name

Ayat

Last Name

Saleh

MiddleName

-

Affiliation

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

Email

eng_ayat87@yahoo.com

City

-

Orcid

-

First Name

Mountasser

Last Name

Mahmoud

MiddleName

-

Affiliation

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

Email

mountasser.mahmoud@aswu.edu.eg

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

1

Page End

15

Print ISSN

2735-3087

Online ISSN

2735-3095

Link

https://aujst.journals.ekb.eg/article_226485.html

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https://aujst.journals.ekb.eg/service?article_code=226485

Order

226,485

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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/

MainTitle

Multi-Objective Self-Adaptive a Non-Dominated Sorting Genetic (NSGA) Algorithm for Optimal Sizing of PV/Wind/Diesel Hybrid Microgrid System

Details

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Article

Created At

23 Jan 2023