Optimising renewable hydrogen hub locations: A GIS-based spatio-temporal integration framework

This paper presents a Geographic Information System (GIS)-integrated spatio-temporal optimisation framework for the design of renewable hydrogen hubs. This framework embeds high-resolution spatial datasets directly into an hourly Mixed-Integer Linear Programming (MILP) formulation to co-optimise the siting, sizing, and hourly operation of system components, thereby minimising the Levelised Cost of Hydrogen (LCOH 2 ). This integration enables realistic evaluation of trade-offs between resource quality, land availability, storage dynamics, and delivery pathways. The framework is illustrated through a case study in northern Tasmania, Australia, which yields a baseline LCOH 2 of 3.50 USD/kg under the stated modelling assumptions. Key insights include the cost advantage of co-locating electrolysers with renewable generation, the influence of storage technology choice on hub economics, and that relaxing supply reliability to 90% reduces expenses by up to 0.5 USD/kg. Verification against benchmark studies confirms that the optimiser produces coherent system designs under varied assumptions. Overall, the framework offers a transferable methodological tool for planning and benchmarking renewable hydrogen hubs globally.