Optimal design of grid-connected hybrid renewable energy system considering electric vehicle station using improved multi-objective optimization: techno-economic perspectives
Electric vehicle charging stations (EVCSs) and renewable energy sources (RESs) have been widely integrated into distribution systems. Electric vehicles (EVs) offer advantages for distribution systems, such as increasing reliability and efficiency, reducing pollutant emissions, and decreasing depende...
Saved in:
Main Authors: | , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Multidisciplinary Digital Publishing Institute (MDPI)
2024
|
Online Access: | http://psasir.upm.edu.my/id/eprint/112764/1/112764.pdf http://psasir.upm.edu.my/id/eprint/112764/ https://www.mdpi.com/2071-1050/16/6/2491 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
id |
my.upm.eprints.112764 |
---|---|
record_format |
eprints |
spelling |
my.upm.eprints.1127642024-11-12T08:40:03Z http://psasir.upm.edu.my/id/eprint/112764/ Optimal design of grid-connected hybrid renewable energy system considering electric vehicle station using improved multi-objective optimization: techno-economic perspectives Al-Sahlawi, Ameer A. Kareim Md. Ayob, Shahrin Tan, Chee Wei Mohammed Ridha, Hussein Hachim, Dhafer Manea Electric vehicle charging stations (EVCSs) and renewable energy sources (RESs) have been widely integrated into distribution systems. Electric vehicles (EVs) offer advantages for distribution systems, such as increasing reliability and efficiency, reducing pollutant emissions, and decreasing dependence on non-endogenous resources. In addition, vehicle-to-grid (V2G) technology has made EVs a potential form of portable energy storage, alleviating the random fluctuation of renewable energy power. This paper simulates the optimal design of a photovoltaic/wind/battery hybrid energy system as a power system combined with an electric vehicle charging station (EVCS) using V2G technology in a grid-connected system. The rule-based energy management strategy (RB-EMS) is used to control and observe the proposed system power flow. A multi-objective improved arithmetic optimization algorithm (MOIAOA) concept is proposed to analyze the optimal sizing of the proposed system components by calculating the optimal values of the three conflicting objectives: grid contribution factor (GCF), levelled cost of electricity (LCOE), and energy sold to the grid ((Formula presented.)). This research uses a collection of meteorological data such as solar radiation, temperature, and wind speed captured every ten minutes for one year for a government building in Al-Najaf Governorate, Iraq. The results indicated that the optimal configuration of the proposed system using the MOIAOA method consists of eight photovoltaic modules, two wind turbines, and thirty-three storage batteries, while the fitness value is equal to 0.1522, the LCOE is equal to 2.66 × (Formula presented.) USD/kWh, the GCF is equal to 7.34 × (Formula presented.) kWh, and the (Formula presented.) is equal to 0.8409 kWh. The integration of RESs with an EV-based grid-connected system is considered the best choice for real applications, owing to their remarkable performance and techno-economic development. Multidisciplinary Digital Publishing Institute (MDPI) 2024 Article PeerReviewed text en cc_by_4 http://psasir.upm.edu.my/id/eprint/112764/1/112764.pdf Al-Sahlawi, Ameer A. Kareim and Md. Ayob, Shahrin and Tan, Chee Wei and Mohammed Ridha, Hussein and Hachim, Dhafer Manea (2024) Optimal design of grid-connected hybrid renewable energy system considering electric vehicle station using improved multi-objective optimization: techno-economic perspectives. Sustainability (Switzerland), 16 (6). art. no. 2491. pp. 1-35. ISSN 2071-1050 https://www.mdpi.com/2071-1050/16/6/2491 10.3390/su16062491 |
institution |
Universiti Putra Malaysia |
building |
UPM Library |
collection |
Institutional Repository |
continent |
Asia |
country |
Malaysia |
content_provider |
Universiti Putra Malaysia |
content_source |
UPM Institutional Repository |
url_provider |
http://psasir.upm.edu.my/ |
language |
English |
description |
Electric vehicle charging stations (EVCSs) and renewable energy sources (RESs) have been widely integrated into distribution systems. Electric vehicles (EVs) offer advantages for distribution systems, such as increasing reliability and efficiency, reducing pollutant emissions, and decreasing dependence on non-endogenous resources. In addition, vehicle-to-grid (V2G) technology has made EVs a potential form of portable energy storage, alleviating the random fluctuation of renewable energy power. This paper simulates the optimal design of a photovoltaic/wind/battery hybrid energy system as a power system combined with an electric vehicle charging station (EVCS) using V2G technology in a grid-connected system. The rule-based energy management strategy (RB-EMS) is used to control and observe the proposed system power flow. A multi-objective improved arithmetic optimization algorithm (MOIAOA) concept is proposed to analyze the optimal sizing of the proposed system components by calculating the optimal values of the three conflicting objectives: grid contribution factor (GCF), levelled cost of electricity (LCOE), and energy sold to the grid ((Formula presented.)). This research uses a collection of meteorological data such as solar radiation, temperature, and wind speed captured every ten minutes for one year for a government building in Al-Najaf Governorate, Iraq. The results indicated that the optimal configuration of the proposed system using the MOIAOA method consists of eight photovoltaic modules, two wind turbines, and thirty-three storage batteries, while the fitness value is equal to 0.1522, the LCOE is equal to 2.66 × (Formula presented.) USD/kWh, the GCF is equal to 7.34 × (Formula presented.) kWh, and the (Formula presented.) is equal to 0.8409 kWh. The integration of RESs with an EV-based grid-connected system is considered the best choice for real applications, owing to their remarkable performance and techno-economic development. |
format |
Article |
author |
Al-Sahlawi, Ameer A. Kareim Md. Ayob, Shahrin Tan, Chee Wei Mohammed Ridha, Hussein Hachim, Dhafer Manea |
spellingShingle |
Al-Sahlawi, Ameer A. Kareim Md. Ayob, Shahrin Tan, Chee Wei Mohammed Ridha, Hussein Hachim, Dhafer Manea Optimal design of grid-connected hybrid renewable energy system considering electric vehicle station using improved multi-objective optimization: techno-economic perspectives |
author_facet |
Al-Sahlawi, Ameer A. Kareim Md. Ayob, Shahrin Tan, Chee Wei Mohammed Ridha, Hussein Hachim, Dhafer Manea |
author_sort |
Al-Sahlawi, Ameer A. Kareim |
title |
Optimal design of grid-connected hybrid renewable energy system considering electric vehicle station using improved multi-objective optimization: techno-economic perspectives |
title_short |
Optimal design of grid-connected hybrid renewable energy system considering electric vehicle station using improved multi-objective optimization: techno-economic perspectives |
title_full |
Optimal design of grid-connected hybrid renewable energy system considering electric vehicle station using improved multi-objective optimization: techno-economic perspectives |
title_fullStr |
Optimal design of grid-connected hybrid renewable energy system considering electric vehicle station using improved multi-objective optimization: techno-economic perspectives |
title_full_unstemmed |
Optimal design of grid-connected hybrid renewable energy system considering electric vehicle station using improved multi-objective optimization: techno-economic perspectives |
title_sort |
optimal design of grid-connected hybrid renewable energy system considering electric vehicle station using improved multi-objective optimization: techno-economic perspectives |
publisher |
Multidisciplinary Digital Publishing Institute (MDPI) |
publishDate |
2024 |
url |
http://psasir.upm.edu.my/id/eprint/112764/1/112764.pdf http://psasir.upm.edu.my/id/eprint/112764/ https://www.mdpi.com/2071-1050/16/6/2491 |
_version_ |
1816132714046160896 |
score |
13.214268 |