Operating energy storage to reduce Australia's grid emissions

Energy storage will play an essential role in meeting current Commonwealth policy emissions targets. Using two commonly compared metrics in literature, the marginal and average emissions factors (MEF & AEF), this paper looks to quantify and forecast Australia's grid emissions when energy storage is increased. Forecasted MEF values, based on a random forest machine learning algorithm, has an accuracy of 87.68% for 5-minute MEF intervals. The AEF is directly calculated based on current and future generation mix. In 2021, the AEF is seen, on average, higher than the MEF. In 2030, due to the increasing percentage of renewables in the grid, the AEF is seen to be, on average, lower than the forecast MEF. Of the two metrics, it can be seen that MEF is more representative of the impact an intervention has on the electricity network and, therefore, is more appropriate for short-term optimisation of energy storage in the National Electricity Market (NEM). Using MEF, optimising energy storage to minimise emissions reduced grid emissions by 29% compared to optimising energy storage to minimise cost for 2021, and similarly 19% in 2030. This translates to a carbon offset price per tonne of $6.05 & $9.45 respectively.