Data Driven Modelling and Control Strategies to Improve Biogas Quality and Production from High Solids Anaerobic Digestion: A Mini Review
Ombretta Paladino ()
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Ombretta Paladino: Department of Civil, Chemical and Environmental Engineering, University of Genoa, Via Opera Pia 15, 16145 Genova, Italy
Sustainability, 2022, vol. 14, issue 24, 1-21
Abstract:
Anaerobic Digestion (AD) is one of the oldest processes for producing biofuels from organic waste. Approximately 180 years have passed since the construction of the first modern plant, however, large prospects for improvement are still feasible, especially in regards to the quality and uniformity of the biogas produced. This work focalizes on the main quality issues and the available post-production treatment processes for biogas; subsequently, a mini-review on data-driven models and control strategies for biogas and bio-methane production plants is presented. Attention is focused on High Solids Anaerobic Digesters (HSADs), since these reactors present many interesting advantages, including a high number of operating variables which enable process optimization, high methane concentration in exit, reduced reactor volume and low water requirements. HSADs are the reactors with which Europe is aiming to rapidly increase the production of biogas and bio-methane, in order to carry out de-carbonization and reduce dependence on external methane imports. Crucial points for achieving these objectives include qualitative leaps in process operation and management, which, contrary to current practice in existing plants, require a significant increase in process automation, with control of product quality and reduction of stops due to death of bacteria at changing process parameters (such as temperature and pH). The most significant papers related to biogas quality, data-driven models and control strategies are briefly analyzed.
Keywords: High Solids Anaerobic Digesters; biogas quality; operating modes; data-driven models; control strategies (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (3)
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:14:y:2022:i:24:p:16467-:d:997959
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