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Journal article : Review

A comprehensive review of modeling approaches for grid-connected energy storage technologies

Abstract:
Energy Storage Systems (ESSs) play a pivotal role in the evolving landscape of electrical generation, distribution, and consumption worldwide. As these systems are increasingly developed and deployed across diverse applications, the need for effective and efficient modeling has become more critical. This work provides a comprehensive overview of key Energy Storage Technologies utilized in electrical applications, highlighting their strengths, limitations, and roles across various use cases. The review offers in-depth analysis and commentary on the current state of energy storage modeling, addressing the challenges and opportunities within this research domain, and providing a novel resource for researchers in this field. To assist researchers in selecting appropriate modeling approaches, this paper explores three levels of modeling complexity, examined through the lens of five prominent energy storage technologies. By evaluating the trade-offs of different approaches and their suitability for various applications, the study serves as a state-of-the-art resource for researchers pursuing new energy storage studies. Furthermore, it examines trends in software and hardware adoption, including case studies and hardware-in-the-loop implementations, while identifying research gaps and opportunities for innovation. The review concludes with insights into future challenges in the field and proposes avenues for advancing energy storage modeling and application research.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1016/j.est.2024.115057

Authors

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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author


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Funder identifier:
https://ror.org/0439y7842
Grant:
EP/W02764X/1


Publisher:
Elsevier
Journal:
Journal of Energy Storage More from this journal
Volume:
109
Article number:
115057
Publication date:
2024-12-27
Acceptance date:
2024-12-14
DOI:
EISSN:
2352-1538
ISSN:
2352-152X


Language:
English
Keywords:
Subtype:
Review
Pubs id:
2074554
Local pid:
pubs:2074554
Deposit date:
2025-01-28
ARK identifier:

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