Demand for beer products fluctuates throughout the year, with a substantial increase occurring for the duration of global sporting events. Beer fermentation is frequently the production bottleneck due to its significant duration (often exceeding 1 week). Therein lies a strong incentive for fermentation optimisation and batch duration reduction such that maximum production capacity can be elevated during peak demand periods. Beer fermentation optimisation has received considerable attention, however a limitation of prior work is the universal assumption of direct and instantaneous control of fermentor temperature. With the addition of only two more ODEs to the system model, heat transfer dynamics is approximated in this work. A novel, comprehensive visualisation of the attainable performance maps for key process variables is presented, obtained via a large-scale dynamic simulation campaign of viable cooling policies. These attainable performance maps are compared to equivalent results produced previously, to elucidate how fermentor performance varies once production scale increases beyond the point of the previous simplifying assumption. Utilising orthogonal polynomials on finite elements allows a finite dimensional optimisation NLP problem to be formulated for ethanol yield maximisation, which has been solved with IPOPT. Optimal operation involves a novel cooling policy to effectively manage the active yeast population in the fermentor for improved performance versus previous approaches for beer fermentation.