Heat decarbonisation is one of the main challenges of energy system decarbonisation. However, existing energy planning models struggle to compare heat decarbonisation approaches because they rarely capture trade-offs between heat supply, end-use technologies and network infrastructure at sufficient spatial resolution. A new optimisation model is presented that addresses this by including trade-offs between gas, electricity, and heat infrastructure, together with related supply and end-use technologies, with high spatial granularity. The model is applied in case studies for the UK. For the case modelled it is shown that electrification of heat is most cost-effective via district level heat pumps that supply heat networks, instead of individual building heat pumps. This is because the cost of reinforcing the electricity grid for installing individual heat pumps does not sufficiently offset heat infrastructure costs. This demonstrates the importance of considering infrastructure trade-offs. When modelling the utilisation of a decarbonised gas, the penetration of heat networks and location of district level heat supply technologies was shown to be dependent on linear heat density and on zone topology. This shows the importance of spatial aspects. Scenario-specific linear heat density thresholds for heat network penetration were identified. For the base case, penetration of high temperature heat networks was over 50% and 60% by 2050 for linear heat densities over 1500 and 2500 kWh/m. For the case when medium heat temperature networks were additionally available, a mix of both networks was observed. Medium temperature heat network penetration was over 20%, 30%, and 40% for linear heat densities of over 1500, 2500, and 3000 kWh/m, while high temperature heat network penetration was over 20% and 30% for linear heat densities of under 2000 and 1500 kWh/m respectively
This work presents the COMET (Cities Optimisation Model for Energy Technologies) model, a spatially-resolved urban energy systems model that takes into account energy service demands for heating, cooling, electricity, and transport, and finds cost-effective pathways for supplying these demands under carbon constraints, trading-off energy supply, network infrastructure, and end-use technologies. Spatially-resolved energy service demands were obtained for the city of Sao Paulo, and six scenarios were modelled. Results show that district cooling is cost-effective in the highest linear cooling density zones, with full penetration in zones with over 1100 kWh/m by 2050. This threshold diminishes with tighter carbon constraints. Heating is electrified in all scenarios, with electric boilers and air-source heat pumps being the main supply technologies for the domestic and commercial sectors respectively by 2050. In the most carbon constrained scenario with a medium decarbonised electricity grid, ground source heat pumps and hydrogen boilers appear as transition technologies between 2030 and 2045 for the commercial and domestic sectors respectively, reaching 95% and 40% of each sector's heat installed capacity in 2030. In the transport sector, ethanol cars replace gasoline, diesel, and compressed natural gas cars; compressed natural gas buses replace diesel and electric buses; and lorries continue using diesel. In carbon constrained scenarios, higher penetrations of electric cars and buses are obtained, while no change is observed for lorries. Finally, the most expensive scenario was only 6% more expensive than the reference scenario, meaning that achieving decarbonisation targets is not much costlier when comparing scenarios from a system-wide perspective.
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