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Optimal location and sizing of battery energy storage system using grasshopper optimization algorithm

An energy storage system called a battery energy storage system (BESS) collects energy from various sources, builds up that energy, and then stores it in rechargeable batteries for future use. The battery's electrochemical energy can be discharged and supplied to buildings such as residences,...

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Main Authors: Mat Yasin, Zuhaila, Razali, Nur Syifa Nasyrah, Dahlan, Nofri Yenita, Mohammad Noor, Siti Zaliha, Ahmad, Nurfadzilah, Hassan, Elia Erwani
Format: Article
Language:English
Published: Intelektual Pustaka Media Utama 2024
Online Access:http://eprints.utem.edu.my/id/eprint/28367/2/0062827122024161920.pdf
http://eprints.utem.edu.my/id/eprint/28367/
https://ijaas.iaescore.com/index.php/IJAAS/article/view/21202
http://doi.org/10.11591/ijaas.v13.i3.pp647-654
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spelling my.utem.eprints.283672025-02-05T15:37:46Z http://eprints.utem.edu.my/id/eprint/28367/ Optimal location and sizing of battery energy storage system using grasshopper optimization algorithm Mat Yasin, Zuhaila Razali, Nur Syifa Nasyrah Dahlan, Nofri Yenita Mohammad Noor, Siti Zaliha Ahmad, Nurfadzilah Hassan, Elia Erwani An energy storage system called a battery energy storage system (BESS) collects energy from various sources, builds up that energy, and then stores it in rechargeable batteries for future use. The battery's electrochemical energy can be discharged and supplied to buildings such as residences, electric cars, and commercial and industrial buildings. The advantages of utilizing BESSs, such as minimizing energy loss, improving voltage profile, peak shaving, and increasing power quality, may be reduced if incorrect decisions about the appropriate position and capacity for BESSs are chosen. Furthermore, the optimal position and size for BESSs are critical since deploying a BESS at every bus, particularly in an extensive network, is not a cost-effective option, and installing oversized BESSs would result in higher investment expenses. Hence, this study suggests a proficient method for identifying the most suitable position and the sizes of BESS to save costs. The grasshopper optimization algorithm (GOA) and evolutionary programming (EP) were employed to address the optimization challenge on the IEEE 69-bus distribution test system. The goal of the optimization is to minimize the overall cost. The findings indicate that the GOA has strong resilience and possesses a superior capacity for optimizing cost reduction in comparison to EP. Intelektual Pustaka Media Utama 2024-09 Article PeerReviewed text en cc_by_sa_4 http://eprints.utem.edu.my/id/eprint/28367/2/0062827122024161920.pdf Mat Yasin, Zuhaila and Razali, Nur Syifa Nasyrah and Dahlan, Nofri Yenita and Mohammad Noor, Siti Zaliha and Ahmad, Nurfadzilah and Hassan, Elia Erwani (2024) Optimal location and sizing of battery energy storage system using grasshopper optimization algorithm. International Journal of Advances in Applied Sciences (IJAAS), 13 (3). pp. 647-654. ISSN 2252-8814 https://ijaas.iaescore.com/index.php/IJAAS/article/view/21202 http://doi.org/10.11591/ijaas.v13.i3.pp647-654
institution Universiti Teknikal Malaysia Melaka
building UTEM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknikal Malaysia Melaka
content_source UTEM Institutional Repository
url_provider http://eprints.utem.edu.my/
language English
description An energy storage system called a battery energy storage system (BESS) collects energy from various sources, builds up that energy, and then stores it in rechargeable batteries for future use. The battery's electrochemical energy can be discharged and supplied to buildings such as residences, electric cars, and commercial and industrial buildings. The advantages of utilizing BESSs, such as minimizing energy loss, improving voltage profile, peak shaving, and increasing power quality, may be reduced if incorrect decisions about the appropriate position and capacity for BESSs are chosen. Furthermore, the optimal position and size for BESSs are critical since deploying a BESS at every bus, particularly in an extensive network, is not a cost-effective option, and installing oversized BESSs would result in higher investment expenses. Hence, this study suggests a proficient method for identifying the most suitable position and the sizes of BESS to save costs. The grasshopper optimization algorithm (GOA) and evolutionary programming (EP) were employed to address the optimization challenge on the IEEE 69-bus distribution test system. The goal of the optimization is to minimize the overall cost. The findings indicate that the GOA has strong resilience and possesses a superior capacity for optimizing cost reduction in comparison to EP.
format Article
author Mat Yasin, Zuhaila
Razali, Nur Syifa Nasyrah
Dahlan, Nofri Yenita
Mohammad Noor, Siti Zaliha
Ahmad, Nurfadzilah
Hassan, Elia Erwani
spellingShingle Mat Yasin, Zuhaila
Razali, Nur Syifa Nasyrah
Dahlan, Nofri Yenita
Mohammad Noor, Siti Zaliha
Ahmad, Nurfadzilah
Hassan, Elia Erwani
Optimal location and sizing of battery energy storage system using grasshopper optimization algorithm
author_facet Mat Yasin, Zuhaila
Razali, Nur Syifa Nasyrah
Dahlan, Nofri Yenita
Mohammad Noor, Siti Zaliha
Ahmad, Nurfadzilah
Hassan, Elia Erwani
author_sort Mat Yasin, Zuhaila
title Optimal location and sizing of battery energy storage system using grasshopper optimization algorithm
title_short Optimal location and sizing of battery energy storage system using grasshopper optimization algorithm
title_full Optimal location and sizing of battery energy storage system using grasshopper optimization algorithm
title_fullStr Optimal location and sizing of battery energy storage system using grasshopper optimization algorithm
title_full_unstemmed Optimal location and sizing of battery energy storage system using grasshopper optimization algorithm
title_sort optimal location and sizing of battery energy storage system using grasshopper optimization algorithm
publisher Intelektual Pustaka Media Utama
publishDate 2024
url http://eprints.utem.edu.my/id/eprint/28367/2/0062827122024161920.pdf
http://eprints.utem.edu.my/id/eprint/28367/
https://ijaas.iaescore.com/index.php/IJAAS/article/view/21202
http://doi.org/10.11591/ijaas.v13.i3.pp647-654
_version_ 1823541847357652992
score 13.239859

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