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Burkel, Chris ; Griesbach, Marco ; Heberle, Florian ; Brüggemann, Dieter ; Jess, Andreas:
Dynamic accounting model with integrated emission allocation methods for coupled energy systems with combined heat and power plants and hybrid heat pumps.
In: Energy Conversion and Management.
Bd. 342
(2025)
.
- 120132.
ISSN 0196-8904
DOI: https://doi.org/10.1016/j.enconman.2025.120132
Abstract
Detailed emission accounting methods are becoming increasingly important as a measurement tool for the decarbonization of energy systems. Conventional accounting methods use only annual demand values and the average grid electricity mix, thereby neglecting dynamic energy and emission flows across the accounting boundary. Moreover, in cases of interconnected supply grids there is a time-dependent exchange of energy and emissions. In this work, a coupled energy system is considered in a dynamic perspective, which connects an electricity, heating and cooling grid through a combined heat and power unit (CHP) and a heat pump (HP) that provides heating and cooling energy at the same time. In order to map the behavior of the emission flows, a dynamic emission balance model is developed using Python. The framework is based on the carbon emission flow theory which is implemented via a Quasi-Input-Output (QIO) node system and uses measured data in an hourly resolution. The dynamic interchange between the grids is enabled by diverse CHP allocation methods that are integrated and applied to the HP. In addition, a method specific for HPs is presented as the Bayreuth method (BaM). The cumulative accounting demonstrates that the allocation methods influence the distribution between the grids, while the resolution determines the absorbed emissions from the public electricity grid. In the case study under consideration, this has the greatest impact on the cooling grid. There is a difference of up to 69 % between the allocation methods and a resolution effect of up to 20 %. The system’s overall balance is enhanced by around 10 % due to a higher resolution in comparison with conventional methodologies. It is evident that dynamic balancing models offer a viable solution for accurately capturing the emissions of an energy system. The analysis of temporal emission flows enables seamless tracking and precise accounting results, even beyond the boundary limits. Furthermore, these models can be transferred to other existing systems and provide a framework for the optimization of energy management strategies, facilitating the temporal progression of the emission load.