District heating systems offer the possibility of lowering emissions and support the goal of reaching a carbon-neutral energy system by integrating renewable heat sources. Therefore, this work provided a systematic literature review to identify potential research gaps and show the literature distribution over the relevant topics. The focus is on the design optimization with (non-)linear programming of district heating systems in the context of decarbonization. Furthermore, crucial energy balance equations were extracted from the literature for a potential optimization problem. The systematic literature review limited its search to two databases, 10 years timespan, a quality measure, and uses keywords regarding topic and method. Categories were derived based on the subject and literature to cluster the found publications and identify potential research gaps. The results showed potential research gaps in the depiction of different stakeholder decisions, reduction of computational efforts, and their resulting uncertainties. Additionally, they identified gaps in the integration of low-grade heat sources, thermal storage facilities, and energy converters, especially geothermal energy, large-scale heat pumps, and seasonal storages.

Germany has become one of the leading players in the transformation of the electricity sector, now having up to 42% of electricity coming from renewable sources. However, the transformation of the heating sector is still in its infancy, and especially the provision of industrial process heating is highly dependent on unsustainable fuels. One of the most promising heating technologies for renewable energies is power-to-heat, especially heat pump technology, as it can use renewable electricity to generate heat efficiently. This research explores the economic and technical boundary conditions regarding the integration of heat pumps into existing industrial thermohydraulic heating and cooling networks. To calculate the optimum design and control of heat pumps, a mixed-integer linear programming model (MILP) is developed. The model seeks the most cost-efficient configuration of heat pumps and stratified thermal storage tanks. Additionally, it optimizes the operation of all energy converters and stratified thermal storage tanks to meet a specified heating and cooling demand over one year. The objective function is modeled after the net present value (NPV) method and considers capital expenditures (costs for heat pumps and stratified thermal storage tanks) and operational expenditures (electricity costs and costs for conventional heating and cooling). The comparison of the results via a simulation model reveals an accuracy of more than 90%.

Global climate change has had devastating results in the last decades, and the fossil fuel-driven heating sector needs to transform into a sustainable system. Therefore, we examined the economics of different renewable and non-renewable technologies, suggesting possible transformation technologies that favour an economic system. We applied our method to a district heating system in Germany. The method is a mixed-integer linear programming model capable of optimizing the design and operation of energy converters and storage in dependency on an economic objective function. The results have shown that biomass heat plants and large-scale heat pumps can compete with gas-fired CHP plants. In 2022, gas is neither an economical nor a sustainable solution. Furthermore, it was shown that the optimizer strives towards a low-temperature system. Large-scale heat pumps, biomass plants and temperature lowering measures should be part of the design of sustainable economic district heating systems.