Back to Search Start Over

A review of modelling approaches to characterize lithium-ion battery energy storage systems in techno-economic analyses of power systems.

Authors :
Vykhodtsev, Anton V.
Jang, Darren
Wang, Qianpu
Rosehart, William
Zareipour, Hamidreza
Source :
Renewable & Sustainable Energy Reviews. Sep2022, Vol. 166, pN.PAG-N.PAG. 1p.
Publication Year :
2022

Abstract

The penetration of the lithium-ion battery energy storage system (LIBESS) into the power system environment occurs at a colossal rate worldwide. This is mainly because it is considered as one of the major tools to decarbonize, digitalize, and democratize the electricity grid. The economic viability and technical reliability of projects with batteries require appropriate assessment because of high capital expenditures, deterioration in charging/discharging performance and uncertainty with regulatory policies. Most of the power system economic studies employ a simple power-energy representation coupled with an empirical description of degradation to model the lithium-ion battery. This approach to modelling may result in violations of the safe operation and misleading estimates of the economic benefits. Recently, the number of publications on techno-economic analysis of LIBESS with more details on the lithium-ion battery performance has increased. The aim of this review paper is to explore these publications focused on the grid-connected LIBESS applications and to discuss the impacts of using more sophisticated modelling approaches. First, an overview of the three most popular battery models is given, followed by a review of the applications of such models. The possible directions of future research of employing detailed battery models in power systems' techno-economic studies are then explored. • Overview of lithium-ion battery models employed in techno-economic studies of power systems. • The impact of various battery models on the decision-making problems in power systems. • Justification for more advanced battery models in the optimization frameworks. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
13640321
Volume :
166
Database :
Academic Search Index
Journal :
Renewable & Sustainable Energy Reviews
Publication Type :
Academic Journal
Accession number :
157562855
Full Text :
https://doi.org/10.1016/j.rser.2022.112584