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Title:Modeling and optimization of anaerobic digestion technology : current status and future outlook
Authors:ID Kegl, Tina (Author)
ID Torres Jiménez, Eloisa (Author)
ID Kegl, Breda (Author)
ID Kovač Kralj, Anita (Author)
ID Kegl, Marko (Author)
Files:.pdf 1-s2.0-S0360128524000571-main.pdf (19,46 MB)
MD5: D55741C18FB9D1FA5CA004E6A180D6B5
 
URL https://www.sciencedirect.com/science/article/pii/S0360128524000571?via%3Dihub
 
Language:English
Work type:Article
Typology:1.02 - Review Article
Organization:FKKT - Faculty of Chemistry and Chemical Engineering
FS - Faculty of Mechanical Engineering
Abstract:Anaerobic digestion (AD) is an important technology that can be engaged to produce renewable energy and valuable products from organic waste while reducing the net greenhouse gas emissions. Due to the AD process complexity, further development of AD technology goes hand in hand with the advancement of underlying mathematical models and optimization techniques. This paper presents a comprehensive and critical review of current AD process modeling and optimization techniques as well as various aspects of further processing of AD products. The most important mechanistically inspired, kinetic, and phenomenological AD models and the most frequently used deterministic and stochastic methods for AD process optimization are addressed. The foundations, properties, and features of these models and methods are highlighted, discussed, and compared with respect to advantages, disadvantages, and various performance metrics; the models are also ranked with respect to adequately introduced criteria. Since AD process optimization affects heavily the required treatment and utilization of AD products, biogas and digestate utilization in the production of renewable energy and other valuable products is also addressed. Furthermore, special attention is devoted to the challenges and future research needs related to AD modeling and optimization, such are modeling issues related to foaming and microbial activities, AD model parameters calibration, CFD simulation challenges, availability of experimental data, and optimization of the AD process with respect to further biogas and digestate utilizations. As current research results indicate, further progress in these areas could notably improve AD modeling robustness and accuracy as well as AD optimization performance.
Keywords:renewable energy, anaerobic digestion, biogas plant, mathematical models, optimization algorithms, products utilization
Publication status:Published
Publication version:Version of Record
Submitted for review:08.03.2024
Article acceptance date:22.09.2024
Publication date:18.10.2025
Publisher:Elsevier
Year of publishing:2025
Number of pages:48 str.
Numbering:Vol. 106
PID:20.500.12556/DKUM-91746 New window
UDC:620.92/.98
ISSN on article:1873-216X
COBISS.SI-ID:213047555 New window
DOI:10.1016/j.pecs.2024.101199 New window
Copyright:© 2024 The Authors
Publication date in DKUM:31.01.2025
Views:203
Downloads:25
Metadata:XML DC-XML DC-RDF
Categories:Misc.
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Record is a part of a journal

Title:Progress in energy and combustion science
Publisher:Elsevier Science
ISSN:1873-216X
COBISS.SI-ID:175330307 New window

Document is financed by a project

Funder:ARIS - Slovenian Research and Innovation Agency
Project number:P2-0414-2022
Name:Procesna sistemska tehnika in trajnostni razvoj

Funder:ARIS - Slovenian Research and Innovation Agency
Project number:P2-0032-2020
Name:Procesna sistemska tehnika in trajnostni razvoj

Funder:ARIS - Slovenian Research and Innovation Agency
Project number:P2-0196-2020
Name:Raziskave v energetskem, procesnem in okoljskem inženirstvu

Funder:ARIS - Slovenian Research and Innovation Agency
Project number:P2-0137-2022
Name:Numerična in eksperimentalna analiza nelinearnih mehanskih sistemov

Funder:Consejería de Universidad, Investigación e Innovación de la Junta de Andalucía
Funding programme:the FEDER-Andalucía 2014–2020 program
Project number:grant number ProyExcel00662

Funder:L'Oréal-UNESCO, Slovenia
Funding programme:For Women in Science 2022

Funder:World Federation of Scientists
Project number:SZF-T.Kegl-01/2023

Licences

License:CC BY 4.0, Creative Commons Attribution 4.0 International
Link:http://creativecommons.org/licenses/by/4.0/
Description:This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.

Secondary language

Language:Slovenian
Keywords:ponovna uporaba energije, anaerobna digestija, rastlinski bioplin, matematični modeli, optimizacijski algoritmi


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