in the repository
URN to cite this document: urn:nbn:de:bvb:703-epub-8848-1
Title data
Griesbach, Marco ; König-Haagen, Andreas ; Heberle, Florian ; Brüggemann, Dieter:
Assessment and optimal sizing of ice energy storage systems in various non-residential building types.
In: Energy.
Vol. 333
(2025)
.
- 137332.
ISSN 1873-6785
DOI der Verlagsversion: https://doi.org/10.1016/j.energy.2025.137332
![[thumbnail of 1-s2.0-S0360544225029743-main.pdf]](https://epub.uni-bayreuth.de/style/images/fileicons/application_pdf.png) |
|
||||||||
|
Download (4MB)
|
Project information
| Project title: |
Project's official title Project's id Entwicklung von Stellvertretermodellen für die Beschreibung von latenten thermischen Speichern mit makroverkapseltem Phasenwechselmaterial 444616738 Open Access Publizieren No information |
|---|---|
| Project financing: |
Deutsche Forschungsgemeinschaft |
Abstract
Efficient heating and cooling solutions are essential to address climate change and rising energy costs. In non-residential buildings, low-temperature waste heat remains unused due to the lack of technical solutions. A promising approach is to combine this waste heat for heating and cooling. However, the temporal mismatch between waste heat availability and demand requires high-capacity thermal storages. Ice-energy-storage-systems (ICES) provide a viable solution, though no standards exist for their evaluation, design and sizing due to complex interactions with other supply units. A detailed numerical evaluation of ICES for various building types is conducted via a novel two-stage screening and optimization approach. Different configurations, with/without a CHP are optimized. The evaluation covers economic, environmental and social costs under different technological and regional boundary conditions. The methodology from a case study is applied to twelve model buildings. Simplified simulations identify potential candidates, followed by detailed computations to determine the optimal system configuration. High gas-to-electricity price ratios and low CO2-emissions favor storage integration. ICES reduce CO2-emissions by up to 55 % and lower demand-related costs. Substantial heating and cooling demand, with at least 8 % simultaneity, is needed to offset the investment. The methodology can be extended to other buildings, such as data centers or mixed-use districts.
Download Statistics