guest ::
| Home > Online First > Data-driven approach on estimating the minimum required supply temperature for building heating systems: method development, extended application evaluation and sensitivity analysis |
| Home > Online First > Data-driven approach on estimating the minimum required supply temperature for building heating systems: method development, extended application evaluation and sensitivity analysis |
| Journal Article | FZJ-2026-01365 |
; ; ; ;
2025
Taylor and Francis
London [u.a.]
This record in other databases:
Please use a persistent id in citations: doi:10.1080/19401493.2025.2493868
Abstract: This paper presents a data-driven method to identify possible heating supply temperature reductions in existing buildings, which can improve the efficiency of heat supply systems such as heat pumps or district heating. Traditional analysis for supply temperature reduction is often associated with high efforts, limiting widespread applications. The proposed method identifies minimum required heat curves based on historical demand data and static information. The building demand is modelled relative to outdoor temperatures for different clusters by time. The demand of individual heaters is subsequently derived. Applying the logarithmic mean temperature difference (LMTD) approach, the minimum required supply temperatures is calculated, creating a heat curve for each identified demand cluster. The results obtained using this method on real office buildings reflect time-dependent demand and achieve temperature reductions in existing buildings. The proposed method thus offers a simplified and scalable approach to identifying potential supply temperature reductions in building heating systems.
; Clarivate Analytics Master Journal List ; Current Contents - Engineering, Computing and Technology ; Essential Science Indicators ; IF < 5 ; JCR ; SCOPUS ; Science Citation Index Expanded ; Web of Science Core Collection
|
PDF