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The decarbonisation of urban district heating (DH) systems requires increased heating grid flexibility. Therefore, this article examines the optimised operation of a tank thermal energy storage (TTES) on the secondary side of a new DH substation for an industrial site in a German city, in order to shave the peaks of the whole DH system and thus reduce the need for heat-only boilers (HOB). The accuracy of heat load and return temperature forecasts for both the industrial consumer and the DH grid is critical to the performance of the optimisation-based operating strategy of the TTES. Therefore, long short-term memory neural networks are used in combination with continuous model updates through incremental learning to create two forecasting scenarios, one using only preceding data for the forecasts and the other including future weather data. The results show that high forecasting accuracy is most relevant for reducing the annual maximum peak, with a reduction of 2.8% in the preceding data scenario, 4% with future weather data and 7% in a benchmark with perfect forecasts. The economic viability of the storage through HOB heat savings is primarily affected by lower forecasting accuracy when the additional cost of HOB heat is less than 60 €/MWh. • Optimised operation of thermal storage at large district heating substations can shift heat supply from HOB to CHP. • Incremental learning improves heat load forecasts generated by deep learning models. • Forecasting accuracy has a significant impact on district heating peak shaving. • Short optimisation intervals and weather forecasts are required to reduce annual maximum peaks. [ABSTRACT FROM AUTHOR]

Abstract: To increase the fractional energy savings achieved with solar thermal combisystems the store volume may be increased. Installation of large stores in single-family houses is, however, often limited by space constraints. In this article the influence of the store dimensions, as well as internal and external auxiliary volume configurations, are investigated for large solar water stores by annual dynamic TRNSYS simulations. The results show that store sizes up to 4m3 may be used in solar heating systems with 30m2 collector area. It is further shown that well-insulated stores are rather insensitive to the geometry. Stores deviating from the conventional dimensions still yield high fractional energy savings. Furthermore, the simulations show that the performance of an internal auxiliary volume configuration in most cases exceeds that of a solution with an external auxiliary unit. The practical limitations of very thin auxiliary volumes must, however, be further investigated. [Copyright &y& Elsevier]

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. • Dynamic simulations of different DHW preparation systems in TRNSYS. • Generation of DH load profiles for DHW for instantaneous and storage systems. • Instantaneous DHW systems yield lower return temperatures than storage systems. • Simultaneity factors were calculated for different systems and time scales. • Time scale and probability distributions for DHW draw-offs influence peak loads. [ABSTRACT FROM AUTHOR]