Unlocking extra value from grid batteries using advanced models

JOURNAL OF POWER SOURCES

卷:487

Article

Reniers, Jorn M.^1,2,3  Mulder, Grietus^2,3  Howey, David A.^1,4 

[1] Univ Oxford, Dept Engn Sci, Oxford OX1 3PJ, England

[2] EnergyVille, B-3600 Genk, Belgium

[3] VITO, B-2400 Mol, Belgium

[4] Faraday Inst, Harwell Campus, Didcot OX11 0RA, Oxon, England

关键词: Lithium-ion;    Degradation;    Lifetime;    Battery;    Energy trading;   

DOI  :  10.1016/j.jpowsour.2020.229355

来源: Elsevier

【 摘 要 】

Lithium-ion batteries are increasingly being deployed in liberalised electricity systems, where their use is driven by economic optimisation in a specific market context. However, battery degradation depends strongly on operational profile, and this is particularly variable in energy trading applications. Here, we present results from a year-long experiment where pairs of batteries were cycled with profiles calculated by solving an economic optimisation problem for wholesale energy trading, including a physically-motivated degradation model as a constraint. The results confirm the conclusions of previous simulations and show that this approach can increase revenue by 20% whilst simultaneously decreasing degradation by 30% compared to existing methods. Analysis of the data shows that conventional approaches cannot increase the number of cycles a battery can manage over its lifetime, but the physics-based approach increases the lifetime both in terms of years and number of cycles, as well as the revenue per year, increasing the possible lifetime revenue by 70%. Finally, the results demonstrate the economic impact of model inaccuracies, showing that the physics-based model can reduce the discrepancy in the overall business case from 170% to 13%. There is potential to unlock significant extra performance using control engineering incorporating physical models of battery ageing.

【 授权许可】

Free