Evaluation and Optimal Dimensioning of Ice Energy Storage Systems in Different Types of Non-Residential Buildings

Titelangaben

Griesbach, Marco ; König-Haagen, Andreas ; Heberle, Florian ; Brüggemann, Dieter:
Evaluation and Optimal Dimensioning of Ice Energy Storage Systems in Different Types of Non-Residential Buildings.
2024
Veranstaltung: 37th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems (ECOS 2024) , 30.06.-05.07.2024 , Rhodes, Greece.
(Veranstaltungsbeitrag: Kongress/Konferenz/Symposium/Tagung , Paper )
DOI: https://doi.org/10.52202/077185-0079

Volltext

Link zum Volltext (externe URL):

Abstract

The search for efficient heating and cooling solutions for buildings is becoming increasingly important
to counteract the ongoing climate change and rising energy prices. Particularly in non-residential
buildings (NRBs), growing amounts of low-temperature waste heat are available but cannot be
exploited due to a lack of technical solutions at present. A promising solution is the combined supply
of heating and cooling by using this waste heat. However, the time lag between the occurrence of waste
heat and demand is an impediment. To balance this mismatch, high capacity thermal storage is required.
Ice energy storage systems (ICES) in the absence of solar support are a viable option to utilize this
previously unused waste heat in NRBs. Such implementations must be evaluated in the overall context
with the remaining generators in the building due to the complex interactions. Moreover, there are
currently no standards for the assessment, design and optimized sizing of ICES in NRBs.
For this reason, a detailed numerical evaluation and analysis of an ICES for different building types is
carried out in this work. A downhill simplex algorithm is used to optimize plant sizing for various plant
configurations with and without a combined heat and power unit (CHP). The evaluation is conducted
on a multi-criteria basis, including economic as well as environmental parameters and a combination of
both including social costs, under different boundary conditions. In order to systematically consider a
wide range of different buildings, the methodology which was carefully tested in an earlier case study
is applied to twelve model buildings from eight different use classes. Using simplified preliminary
simulations, possibly appropriate candidates of model buildings are determined. Subsequently, detailed
variation computations are used to determine an ideal plant and storage configuration.
The optimal configuration of an implementation strongly depends on the prevailing boundary
conditions. High gas-to-electricity price ratios and low CO2 emissions from the electricity mix are
generally advantageous for the integration of a storage system. In all investigated regions, the
application of an ICES can lead to an environmental improvement of the CO2 emissions of up to 55 %
compared to a conventional system and a reduction of demand-related costs. However, the additional
capital investment to integrate an ICES requires rather a high demand for heating and cooling, so the
savings in demand-related costs compensate for it. Moreover, at least 8 % of the heating and cooling
must occur simultaneously, so the cooling circuit can be used as a straight energy source of the heat
pump, allowing the storage tank to be regenerated often. In most cases, pure air-conditioning cannot
provide the needed degree of simultaneity, so types of process cooling are essential.
The proposed methodology was tested for twelve building types but can be applied to more building
types, like data centers, or to districts with various building types. Especially the combination of the
waste heat from NRBs with the heating requirements of residential buildings can decrease the necessary
storage capacities and improve the efficiency.