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Energy systems modellers often resort to simplified system representationsand deterministic model formulations (i.e., not considering uncertainty) topreserve computational tractability. However, reduced levels of detail andneglected uncertainties can both lead to sub-optimal system designs. In thispaper, we present a novel method that quantitatively compares the impact ofdetail and uncertainty to guide model development and help prioritisation ofthe limited computational resources. By considering modelling choices as anadditional 'uncertain' parameter in a global sensitivity analysis, the methoddetermines their qualitative ranking against conventional input parameters. Asa case study, the method is applied to a peer-reviewed heat decarbonisationmodel for the United Kingdom with the objective of assessing the importance ofspatial resolution. The results show that while for the optimal total systemcost the impact of spatial resolution is negligible, it is the most importantfactor determining the capacities of electricity, gas and heat networks.

Detail or uncertainty? Applying global sensitivity analysis to strike a balance in energy system models