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Smart optimization in battery energy storage systems: An overview

Authors :
Hui Song
Chen Liu
Ali Moradi Amani
Mingchen Gu
Mahdi Jalili
Lasantha Meegahapola
Xinghuo Yu
George Dickeson
Source :
Energy and AI, Vol 17, Iss , Pp 100378- (2024)
Publication Year :
2024
Publisher :
Elsevier, 2024.

Abstract

The increasing drive towards eco-friendly environment motivates the generation of energy from renewable energy sources (RESs). The rising share of RESs in power generation poses potential challenges, including uncertainties in generation output, frequency fluctuations, and insufficient voltage regulation capabilities. As a solution to these challenges, energy storage systems (ESSs) play a crucial role in storing and releasing power as needed. Battery energy storage systems (BESSs) provide significant potential to maximize the energy efficiency of a distribution network and the benefits of different stakeholders. This can be achieved through optimizing placement, sizing, charge/discharge scheduling, and control, all of which contribute to enhancing the overall performance of the network. In this paper, we provide a comprehensive overview of BESS operation, optimization, and modeling in different applications, and how mathematical and artificial intelligence (AI)-based optimization techniques contribute to BESS charging and discharging scheduling. We also discuss some potential future opportunities and challenges of the BESS operation, AI in BESSs, and how emerging technologies, such as internet of things, AI, and big data impact the development of BESSs.

Details

Language :
English
ISSN :
26665468
Volume :
17
Issue :
100378-
Database :
Directory of Open Access Journals
Journal :
Energy and AI
Publication Type :
Academic Journal
Accession number :
edsdoj.2b3458bd104e4f228f835f7ebff4a616
Document Type :
article
Full Text :
https://doi.org/10.1016/j.egyai.2024.100378