Replacing fossil fuels in district heating - modelling investments, impacts, and uncertainties

Heating and cooling, including industrial heat, consume half of the final energy use in the EU and only 20% of it is produced from renewable sources. District heating (DH) could help decarbonizing heating, but DH sector must reduce its current emission first. In this Thesis, energy system modelling is applied to study investments to fossil-free DH production and related uncertainties. This Thesis uses an existing long-term energy system model TIMES-VTT and develops new more detailed DH models that capture additional real-life constraints and have faster solve times allowing extended uncertainty analysis. The electrification route includes many scalable technologies to replace fossil fuels in DH generation. Large heat pumps were the most robust of the studied investment options unless suffering from high electricity grid fees and taxes. However, local excess heat sources are often significantly smaller than the heat demand, especially in large cities. Ambient heat sources, such as sea water or air, could complement the available heat sources, but this depends highly on local conditions and heat demand density. The biomass route provides a range of well-rounded technologies to replace fossil fuels in district heating. However, this Thesis further strengthens the conclusion that there is not enough biomass available to replace all fossil fuels in DH even in Finland. Increasing biomass demand and decreasing forest sinks in the EU create significant uncertainties over the future availability and price of sustainable biomass. Certain upcoming technologies, such as nuclear district heating and bioenergy with carbon capture and storage, seem promising future decarbonization options, but they need technology development and demonstration units first. In the course of work, large system models proved to be more flexible the more detailed DH models. As a result, large system models indicated faster decarbonization leading to a situation where studies giving background information for climate and energy policies have lower-cost and faster decarbonization of heating sector than what may be achievable. Each modelling study should consider a large range of uncertainties, or they risk drawing flawed conclusions based on too narrow set of modelled cases and assumption ranges. The main sources of uncertainties in the results of this Thesis were related to the variability of electricity generation and price, biomass availability and price, natural gas price, investment costs of new units, breakthrough of new technologies, and the required phase of emission reductions.