Improving optimal control of grid-connected lithium-ion batteries through more accurate battery and degradation modelling

The increased deployment of intermittent renewable energy generators opens up many new opportunities for grid-connected energy storage. Batteries offer significant flexibility compared with most other storage technologies, but are relatively expensive. The lifetime of the battery is a key factor in the business case. The lifetime depends on how the battery is used, but most techno-economic analyses do not account for this. Here, three lithium-ion battery dynamic and degradation models of increasing realism are formulated, and the predicted degradation of each is compared with a large-scale experimental degradation data set (Mat4Bat). A respective improvement in RMS capacity prediction error from 11% to 5% is found by increasing the model accuracy. The three models are then used within an optimal control algorithm to perform price arbitrage over one year, including degradation. Results show that the revenue can be increased substantially while degradation can be reduced by using more realistic models. The estimated best case profit using a sophisticated model is a 175% improvement compared with the simplest model. This illustrates that using a simplistic battery model in a techno-economic assessment of grid-connected batteries might substantially underestimate the business case and lead to erroneous conclusions. keywords: Lithium Ion, Degradation, Grid-connected Battery, Optimal control, Battery ageing, Battery modelling ∗Corresponding author Email addresses: [email protected] (Jorn M. Reniers), [email protected] (Grietus Mulder), [email protected] (Sina Ober-Blöbaum), [email protected] (David A. Howey ) URL: http://epg.eng.ox.ac.uk/ (David A. Howey ) Preprint submitted to Elsevier October 13, 2017 ar X iv :1 71 0. 04 55 2v 1 [ cs .S Y ] 1 2 O ct 2 01 7