Whose Futures Are Computable? Spatial Architecture and the Geographies of Expertise in Energy-System Optimisation Modelling

Energy-system optimisation models play a central role in shaping climate policy, infrastructure investment, and the range of decarbonisation pathways considered feasible. A growing reflexive literature within the modelling community has shown that these tools are not neutral representations of future energy systems, but embed normative assumptions, epistemic values, and political choices. However, two structural blind spots remain. First, existing critiques pay limited attention to the spatial architectures of optimisation models: how decisions regarding spatial resolution, regional aggregation, and system boundaries determine which places, infrastructures, and inequalities are rendered computationally visible. Second, debates over model politics remain largely situated within Northern modelling communities, with insufficient attention to the geographies of expertise that shape who builds, adapts, and contests these models, and whose futures become computationally representable. We argue that these blind spots matter because the spatial and institutional organisation of modelling is not incidental, but constitutive of the transition pathways that models can produce. Building on insights from critical climate geography, we conceptualise energy-system optimisation modelling as a spatial and epistemic practice that participates in producing uneven and governable transition futures. We illustrate this argument through widely used open-source modelling frameworks applied in lower-income countries, highlighting the distinction between additive and constitutive treatments of space and politics. We conclude by outlining a research and capacity-building agenda for a more spatially grounded, reflexive, and globally distributed approach to energy modelling, one that takes seriously the question of whose places, knowledges, and futures are made computationally visible.