@phdthesis{Sporleder2024, author = {Sporleder, Maximilian}, title = {Design optimization of decarbonized district heating systems}, doi = {10.26127/BTUOpen-6852}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:co1-opus4-68526}, school = {BTU Cottbus - Senftenberg}, year = {2024}, abstract = {Reducing CO₂ emissions is crucial to combat global warming, especially as district heating sector emissions have increased by 25 \% since 2010. This dissertation addresses the need for decarbonizing district heating systems through a Python package designed for optimizing sustainable heat solutions. It explores three main research questions: integrating renewable heat sources, modeling pit thermal energy storage systems, and comparing central supply networks with those incorporating booster heat pumps. The research includes a systematic literature review focused on optimizing district heating, identifying gaps in integrating renewable energy and storage capacities. A modeling approach to assess storage capacity within optimization problems is developed, along with a mixed-integer linear programming model for designing supply systems. The model considers network topology, demand, weather, and component data, optimizing mass flows and minimizing costs. Key findings indicate that integrating large-scale heat pumps and waste heat can compete economically with traditional systems. Pit thermal energy storage systems, particularly in high-temperature networks (>70 °C), can be designed effectively using mixed-integer linear programming combined with simulations. Charging strategies, such as solar thermal energy for low-density areas or Power-to-Heat technologies for urban settings, enhance economic performance. The study suggests that a combination of central and decentralized units, like booster heat pumps, can optimize performance and reduce investment costs. Overall, the research emphasizes the importance of integrating waste heat and thermal storage in creating decarbonized district heating systems that can supply heat for 15 ct/kWh by 2030.}, subject = {Design optimization; District heating; Mixed-integer linear programming; Auslegungsoptimierung; Gemischt-ganzzahlige lineare Optimierung; Fernw{\"a}rmesysteme; Fernw{\"a}rmeversorgung; Abw{\"a}rme; Großw{\"a}rmepumpe; W{\"a}rmespeicher; Ganzzahlige lineare Optimierung}, language = {en} }