District heating load profiles for domestic hot water preparation with realistic simultaneity using DHWcalc and TRNSYS

To reach the goal of decarbonizing energy systems, newly constructed buildings must adhere to higher efficiency standards. In new residential developments, this results in a higher share and significance of the energy demand for domestic hot water preparation. In order to generate realistic load profiles for domestic hot water preparation, which can help with dimensioning district heating systems, four substation types were modeled in TRNSYS. Two instantaneous and two storage systems were considered for single family and multi family houses. 11 fictitious buildings were defined, for which the systems were dimensioned. Yearly simulations were conducted, using DHWcalc draw-off profiles as input. The impact of domestic hot water preparation system design on energy balances, return temperatures and simultaneity factors was investigated. Distribution heat losses amount to approximately the same energy demand as the useful energy demand for domestic hot water. In single family houses, storage heat losses also account for a significant energy demand, but in larger multi family houses the storage heat losses are negligible. The yearly weighted average return temperatures of the investigated buildings vary from 25 to 54 °C. Instantaneous DHW preparation result in 8–9 K lower return temperatures for the district heating system than storage systems. An important influencing factor on the return temperature is the relation of energy used by the circulation system to the useful energy demand, resulting in lower return temperatures in more densely inhabited buildings. Load duration curves for superposed profiles were calculated and compared to literature values. The results show, that DHWcalc draw-off profiles provide a suitable basis with realistic simultaneity for district heating load profiles. It is shown, that the time interval for which simultaneity factors are calculated must always be considered. Also, the importance of the underlying probability distributions for draw-off profiles was shown by comparing different approaches.