The aerobic granular sludge (AGS) process treats wastewater with a significantly lower footprint and energy consumption compared to conventional activated sludge systems. Nevertheless, there is still potential for optimizing its performance, and mathematical models are most valuable tools to this end. Aeration energy consumption deserves particular attention, as it is the largest remaining operating cost for AGS systems. Batch-wisely operated reactors show an increasing oxygen transfer efficiency during aeration, which translates into a dynamic alpha factor. However, the dynamic nature of alpha is neglected in current models. The impact of this simplification on the operating performance was addressed for the first time in this study. Through the development of a novel 1-D biofilm reactor model, calibrated to a full-scale AGS plant, it was shown that the alpha dynamics affect both model structure and calibration, as well as the process performance. The description of the dynamic nature of alpha through the empirical relationship with the soluble biodegradable organic carbon required the addition of the state variable representing soluble slowly biodegradable organic carbon (S_CB) to the biokinetic ASM2d model. Simulation results showed that alpha dynamics significantly influences simultaneous nitrification and denitrification and therefore need to be included in mathematical models to optimize AGS process performance. Different process variables such as volume exchange ratio, aeration capacity and granule size can be manipulated to improve reactor design and performance. The practical application of these new insights were discussed regarding the optimization of AGS systems, as well as other batch-wisely operated aerobic wastewater treatment systems.