In the UK, 45% of the total energy demand in 2016 was used for heating purposes, 68% of which was supplied by natural gas. Credible alternatives for decarbonising heat include district heating combined with low carbon heat sources, heat electrification using heat pumps (with a decarbonised electricity system), or hydrogen-fuelled heat technologies. Adoption of these technologies must proceed alongside network infrastructure investment and developments in the broader energy system, such as increased renewable power generation.
At the time of writing, no systematic framework exists that trades off individual building and district heat supply technologies and their associated infrastructures at high spatial resolutions. This work formulates and applies such framework. It presents a mixed integer linear optimisation model that decides on investments and operation of gas, electricity, heat, and hydrogen technologies and associated network infrastructures, for supplying commercial and domestic heat and electricity demands in spatially-resolved urban areas, minimising the net present cost through 2050.
This model is implemented to study four key issues related to heat decarbonisation: Comparing different temperature heat networks for decarbonising heat; the effect of spatial resolution in outcomes of energy systems models for heat; the role of hydrogen in heat decarbonisation pathways in the UK; and the sensitivity of heat decarbonisation outcomes to uncertainty in techno-economic parameters.
Results show that adoption of heat technologies depends, among several factors, on linear heat density, zone-to-zone connectivity, and scenario-specific techno-economic assumptions such as technology, fuels, or electricity prices. Linear heat density adoption thresholds were found for individual technologies. Medium and high temperature heat networks were adopted in high and medium/high linear heat density zones, respectively. Hydrogen boilers were adopted when enabling gas networks to be retrofitted to transport hydrogen. Finally, spatial resolution was shown to be a determining factor for finding cost-effective heat decarbonisation pathways through energy systems models.