Abstract
The majority of district heating networks (DHNs) in Germany and other European countries are still supplied by fossil fuels. While several possible technical solutions exist to decarbonize DHNs, the problem is the availability of solar energy – thermal and electric – or other renewable electric sources during winter. A solution is to shift the available energy from the summer to the winter by using seasonal thermal energy storage systems. Especially pit thermal energy storage systems (PTES) have shown an economic advantage compared to other storage types. Therefore, we would like further to investigate the design of PTES under different techno-economic conditions.In this study, different charging options for the PTES were examined. Solar thermal energy was compared to photovoltaic (PV), supplying an air-source heat pump (ASHP). We developed an open-source Python package based on mixed-integer linear programming, minimizing the total system cost, i.e., the annuity, including opex and capex. The tool selects, operates, and designs energy converters and storages. Furthermore, it optimizes the network’s storage capacity during the operation. The optimization takes the characteristics of an existing DHN as input and designs the supply systems across different locations (LOCs). The model separates the hydraulic and thermal calculation and builds up a multi-stage process to consider temperatures inside the network and the PTES.The tool was applied to a DHN in Eastern Germany. The results show a low sensitivity to the electricity price in all concepts. Operating the PTES at low temperatures negatively affects the heat capacity, and therefore, it is best suited for high-temperature networks. The concept of PV with an ASHP is better suited for densely populated regions. However, both concepts have a total system cost above 20ct/kWh for an area price of over 120€/m2. For an electricity price of ca. 19ct/kWh, the total system cost is below 17ct/kWh for both concepts.
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