Decarbonization of existing heating networks through optimal producer retrofit and low-temperature operation.

District heating networks are considered crucial for enabling emission-free heat supply, yet many existing networks still rely heavily on fossil fuels. With network pipes often lasting over 30 years, retrofitting heat producers in existing networks offers significant potential for decarbonization. This paper presents an automated design approach, to decarbonize existing heating networks through optimal producer retrofit and ultimately enabling 4th generation operation. Using multi-objective, mathematical optimization, it balances CO 2 emissions and costs by assessing different CO 2 prices. The optimization selects producer types, capacities, and for each period their heat supply and supply temperature. The considered heat producers are a natural gas boiler, an air-source heat pump, a solar thermal collector, and an electric boiler. A non-linear heat transport model ensures accurate accounting of heat and momentum losses throughout the network, and operational feasibility. The multi-period formulation incorporates temporal changes in heat demand and environmental conditions throughout the year. By formulating a continuous problem and using adjoint-based optimization, the automated approach remains scalable towards large scale applications. The design approach was assessed on a medium-sized 3rd generation district heating network case and was able to optimally retrofit the heat producers. The retrofit study highlights a strong influence of the CO 2 price on the optimal heat producer design and operation. Increasing CO 2 prices shift the design towards a heat supply dominated by an energy-efficient and low-emission heat pump. Furthermore, it was observed that even for the highest explored CO 2 price of 0.3 € kg − 1 , the low-emission heat pump, electric boiler and solar thermal collector cannot fully replace the natural gas boiler in an economic way. • Automated, physics-based heat producer retrofit for district heating networks. • Multi-objective optimization enables cost-efficient decarbonization. • The optimal heat producer design and operation depends strongly on the CO 2 price. • Choosing multiple heat producers allows low-carbon and cost-efficient heat supply. • The optimization exploits temperature-dependent heat producer efficiencies. [ABSTRACT FROM AUTHOR]