The increased deployment of intermittent renewable energy generators opens up
opportunities for grid-connected energy storage. Batteries offer significant
flexibility but are relatively expensive at present. Battery lifetime is a key
factor in the business case, and it depends on usage, but most techno-economic
analyses do not account for this. For the first time, this paper quantifies the
annual benefits of grid-connected batteries including realistic physical
dynamics and nonlinear electrochemical degradation. Three lithium-ion battery
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