Evaluating the impact of the district heating resolution on renewable heat production in Germany: A sensitivity analysis

This paper evaluates the effects of varying spatial resolutions of district heating (DH) networks in energy system modeling. The analysis employs a hierarchical clustering algorithm to categorize 1228 DH areas in Germany in the year 2050 according to their renewable and excess heat potentials into DH types. These DH types are then integrated into the sectorcoupled energy system model Enertile, with each scenario representing DH in a different spatial resolution. The findings reveal a "pooling effect" in scenarios with highly aggregated DH types characterized by two primary model behaviors: Firstly, scenarios with lower spatial resolutions tend to overestimate local DH generation potentials. Secondly, lower spatial resolutions of DH lead to an underestimation of the necessary heat generation capacities, particularly the need for seasonal thermal storages. The sensitivity analysis indicates that representing DH networks with 12 DH types effectively reduces this pooling effect while maintaining acceptable computational times.