Unraveling the spatial complexity of national energy system models: A systematic review

The energy transition poses spatial planning challenges owing to reliance on renewable sources, featured by a decentralized nature and substantial space requirements. Developing national energy system models capable of integrating spatial details while being robust enough for coherent policy development remains challenging. This study aims to review and analyze necessary spatial modeling details at the national level and methodologies for integration into energy system models. We conduct a systematic literature review on integrating spatially dependent parameters in bottom-up energy system models. The essential role of spatial aspects is highlighted by introducing a classification system for comparing energy system models. We critically evaluate and explore various approaches for assessing spatially dependent parameters in energy systems (energy sources, demand, and infrastructure), spatial aggregation methods (clustering and regionalization), and linking techniques (soft-linking and hard-linking) for incorporating spatially dependent parameters into the energy system models. Results show that energy system models have some spatial capabilities, yet certain crucial elements, like energy infrastructure distribution, are highly aggregated or neglected. Clustering methods can effectively capture spatial variations, and soft-linking techniques can incorporate these spatial details into the energy system model. Here, we propose a novel framework to facilitate the integration of spatial elements into energy system model, a spatial converter to exchange information with the energy system model, a detailed energy system model, and a converter to exchange feedback to the spatial model. Additionally, we advocate for using a soft-linking method with a recursive procedure to exchange feedback between the energy system model and spatial model.