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

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

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Abstract

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.

Item Type:	Article
Uncontrolled Keywords:	Battery energy storage system, Cost minimization, Evolutionary programming, Grasshopper optimization algorithm
Divisions:	Faculty of Electrical Engineering
Depositing User:	Norfaradilla Idayu Ab. Ghafar
Date Deposited:	05 Feb 2025 15:37
Last Modified:	05 Feb 2025 15:37
URI:	http://eprints.utem.edu.my/id/eprint/28367
Statistic Details:	View Download Statistic

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