Renew. Energy Environ. Sustain.
Volume 6, 2021
Achieving Zero Carbon Emission by 2030
|Number of page(s)||7|
|Published online||16 August 2021|
Data-driven Modelling of Thermal Solid Sorption Storage Systems
University of Applied Sciences Upper Austria, Energy Research Group ASIC, Wels, Austria
* e-mail: firstname.lastname@example.org
Received in final form: 19 July 2021
Accepted: 19 July 2021
An approach fofsr data-driven modelling of open sorption storage systems using zeolite as storage material is presented. The overall dynamic simulation model has the inflow air stream mass flow and absolute humidity as inputs and computes the outflow air temperature. The model is sub-divided into several components, where dynamic state space and process model identification techniques are applied. A comparison of the proposed modelling technique with simulated data from a validated model based on first principles shows that a reasonable accuracy − for a model application in temperature control systems design − can be obtained. It was found that using the proposed strategy, only a limited number of experiments are required, thus saving experimental time. Moreover, the computational requirements for a simulation using the proposed model are greatly reduced compared to a simulation model where differential equations discretised in time and space must be solved.
© H. Kirchsteiger and N. Daborer-Prado, Published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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