Integrating renewable energy and thermal storage in district heating networks: A design optimization approach

District heating networks (DHNs) can efficiently supply renewable energy to urban districts. However, weather dependent energy sources and the mismatch between energy availability and heating demand make the design of DHNs challenging. This work formulates a mixed-integer linear programming (MILP) optimization for multiple time steps and integrates thermal storage and renewable energy into DHN design. The proposed model optimizes the piping layout, investment decisions, and operating strategies regarding the supply and thermal storage technologies in full spatial resolution. The model is applied to two synthetic and an actual district network of increasing sizes. A sensitivity analysis assesses the impact of temporal aggregation levels on the design outcome, finding that a minimal number of three time periods and five-time segments are necessary for sufficient accuracy. Compared to models based solely on peak heating loads, the proposed approach delivers more cost-effective network designs, differing significantly in supply configurations and network topology. The findings underscore the importance of temporally resolved design methodologies for systems integrating multiple renewable energy sources. While variable electricity prices have minimal impact on network topology, they significantly enhance the economic viability of large-scale heat pumps when combined with thermal energy storage.      «

District heating networks (DHNs) can efficiently supply renewable energy to urban districts. However, weather dependent energy sources and the mismatch between energy availability and heating demand make the design of DHNs challenging. This work formulates a mixed-integer linear programming (MILP) optimization for multiple time steps and integrates thermal storage and renewable energy into DHN design. The proposed model optimizes the piping layout, investment decisions, and operating strategi...     »