Soft sensor for substrate characterization through the reverse application of the ADM1 model for anaerobic digestion plant operations

Abstract

Accurately characterizing the substrate used in anaerobic digestion is crucial for predicting the biogas plant's performance. This issue makes particularly challenging the application of modeling in codigestion plants. In this work, a novel methodology called substrate prediction module (SPM) has been developed and tested, using virtual codigestion data. The SPM aims to estimate the inlet properties of the substrate based on the reverse application of the anaerobic digestion model n1 (ADM1). The results show that, while the SPM can estimate some properties of the substrate based on certain output parameters, there are limitations in accurately determining all required variables. HIGHLIGHTS Extensive substrate characterization is challenging, especially for codigestion.; A reverse modeling approach is proposed to estimate unknown substrate properties.; The substrate prediction module processes measured AD data based on the ADM1.; Two data processing strategies are assessed: 7-day moving block and daily data.; The SPM could estimate some substrate properties but there are limitations.;

Keywords

• adm1
• biogas plants
• modeling and simulation
• subrogated model
• substrate prediction module
• virtual digester