Lifetime Degradation Cost Analysis for Li-Ion Batteries in Capacity Markets using Accurate Physics-Based Models

Ahmed Gailani, Maher Al-Greer, Michael Short, Tracey Crosbie and Nashwan Dawood
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Ahmed Gailani: School of Computing, Engineering and Digital Technologies, Teesside University, Middlesbrough TS1 3BX, UK
Maher Al-Greer: School of Computing, Engineering and Digital Technologies, Teesside University, Middlesbrough TS1 3BX, UK
Michael Short: School of Computing, Engineering and Digital Technologies, Teesside University, Middlesbrough TS1 3BX, UK
Tracey Crosbie: School of Computing, Engineering and Digital Technologies, Teesside University, Middlesbrough TS1 3BX, UK
Nashwan Dawood: School of Computing, Engineering and Digital Technologies, Teesside University, Middlesbrough TS1 3BX, UK

Energies, 2020, vol. 13, issue 11, 1-21

Abstract: Capacity markets (CM) are energy markets created to ensure energy supply security. Energy storage devices provide services in the CMs. Li-ion batteries are a popular type of energy storage device used in CMs. The battery lifetime is a key factor in determining the economic viability of Li-ion batteries, and current approaches for estimating this are limited. This paper explores the potential of a lithium-ion battery to provide CM services with four de-rating factors (0.5 h, 1 h, 2 h, and 4 h). During the CM contract, the battery experiences both calendar and cycle degradation, which reduces the overall profit. Physics-based battery and degradation models are used to quantify the degradation costs for batteries in the CM to enhance the previous research results. The degradation model quantifies capacity losses related to the solid–electrolyte interphase (SEI) layer, active material loss, and SEI crack growth. The results show that the physics-based degradation model can accurately predict degradation costs under different operating conditions, and thus can substantiate the business case for the batteries in the CM. The simulated CM profits can be increased by 60% and 75% at 5 °C and 25 °C, respectively, compared to empirical and semiempirical degradation models. A sensitivity analysis for a range of parameters is performed to show the effects on the batteries’ overall profit margins.

Keywords: capacity market; degradation cost; physics-based modelling; de-rating factors (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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