University of Oulu

Hämäläinen, H., & Ruusunen, M. (2022). Identification of a supercritical fluid extraction process for modelling the energy consumption. Energy, 252, 124033. https://doi.org/10.1016/j.energy.2022.124033

Identification of a supercritical fluid extraction process for modelling the energy consumption

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Author: Hämäläinen, Henri1; Ruusunen, Mika2
Organizations: 1Environmental and Chemical Engineering Unit, University of Oulu, P.O. Box 4300, FI-90014, Oulu, Finland
2Biorefinery Measurements, Control Engineering, Environmental and Chemical Engineering Unit, University of Oulu, P.O. Box 4300, FI-90014, Oulu, Finland
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 1.6 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe2022090957975
Language: English
Published: Elsevier, 2022
Publish Date: 2022-09-09
Description:

Abstract

Supercritical carbon dioxide extraction has been established as a promising and clean technology alternative to conventional separation techniques. Despite a high energy demand of extraction processes, their energy analysis has been scarcely considered. In this study, a supercritical carbon dioxide batch extraction process was modelled through system identification, forming a full simulator of its control loops affecting the energy consumption. The modelling was based on data acquired through systematic approach including experimental design and identification of dynamic process responses and energy consumption. Regression analysis and 12 identified models for subprocesses showed feasible performance during simulations with experimental data. The best local model for a subprocesses exhibited a Mean Absolute Percentage Error of 3% with independent test data. Regression model for steady-state electricity consumption showed a Mean Absolute Percentage Error of 7.6%, also suggesting the existence of nonlinearities between the response and other process variables. The identification approach reveals new information on energy consumption and dynamics of energy consumption of supercritical extraction in transient operating conditions. The models can be applied for further developments in real-time energy monitoring and optimization of supercritical extraction processes.

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Series: Energy
ISSN: 0360-5442
ISSN-E: 0360-5442
ISSN-L: 0360-5442
Volume: 252
Article number: 124033
DOI: 10.1016/j.energy.2022.124033
OADOI: https://oadoi.org/10.1016/j.energy.2022.124033
Type of Publication: A1 Journal article – refereed
Field of Science: 215 Chemical engineering
213 Electronic, automation and communications engineering, electronics
Subjects:
Copyright information: © 2022 The Author(s). This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
  https://creativecommons.org/licenses/by/4.0/