Dr. James Glynn, Vahid Aryanpur, Brian O'Gallachoir, Hancheng Dai and Wenying Chen

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National-scale energy systems optimisation models (ESOMs) have been limited in the past by the lack of sub-national data availability leading to aggregated treatment of spatial dynamics. This review paper first determines how a combination of supply and demand data requirements and socio-economic, environmental and political issues, can challenge the results of a low-spatial resolution model. It also demonstrates the incompleteness of single region ESOMs that do not capture sufficient spatial detail. Specifically, 36 multi-regional ESOMs from 22 countries with varying levels of spatiotemporal resolutionsectoral focus and planning horizon are systematically identified and comprehensively analysed. The review reveals that existing temporally explicit ESOMs with a single sector coverage can permit regional disaggregation up to the first-level administrative divisions within a country (such as state and province) while maintaining computationally tractable. Findings from the literature review also show when, how, and to what extent higher spatial resolution impact on the results of energy system analysis. (1) Finer spatial resolution in ESOMs offers significant added value for regions with heterogeneous renewable potential or across regions with higher variability in energy service demands. However, in homogeneous areas, aggregated single-region modelling is more efficient. (2) Spatially resolved models can significantly change the results of the scenarios with very high shares of variable renewable energies. But it is not straightforward to find a direct relationship between the level of geographic disaggregation and penetration of renewable energies. This trade-off should be explored case-by-case. (3) Total system costs can be under- or over-estimated in various levels of spatial resolutions. Disaggregation of renewable resources leads to lower costs, and disaggregation of transmission grids leads to higher costs.