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Energy system models based on linear programming have been growing in sizewith the increasing need to model renewables with high spatial and temporaldetail. Larger models lead to high computational requirements. Furthermore,seemingly small changes in a model can lead to drastic differences in runtime.Here, we investigate measures to address this issue. We review the mathematicalstructure of a typical energy system model, and discuss issues of sparsity,degeneracy and large numerical range. We introduce and test a method toautomatically scale models to improve numerical range. We test this method aswell as tweaks to model formulation and solver preferences, finding thatadjustments can have a substantial impact on runtime. In particular, thebarrier method without crossover can be very fast, but affects the structure ofthe resulting optimal solution. We conclude with a range of recommendations forenergy system modellers.

Harder, better, faster, stronger: understanding and improving the tractability of large energy system models