Towards maximization of parameters identifiability: Development of the CalOpt tool and its application to the anaerobic digestion model

This work addresses the need for robust approaches to estimate kinetic parameters in continuous anaerobic co-digestion plants. Specifically, it outlines a procedure for including data from batch activity tests on digestate samples, in addition to the poorly informative dataset from conventional monitoring of biogas facilities. To profitably make use of activity tests, the estimation of the biomass composition in digestate samples is required to improve parameter identifiability. To this purpose, an open-source tool (CalOpt) was developed and tested on a pilot-scale co-digester, simultaneously using data from both conventional monitoring and lab-scale activity tests. Targeting the prediction of volatile fatty acids (VFAs) concentrations in the digestate of the continuous co-digester, the kinetic parameters of different microbial groups were selected for calibration based on parameters importance ranking and collinearity index. The results demonstrate that the CalOpt tool significantly improved the fitting of acetic, propionic, and butyric acid concentrations in digestate as well as the methane flowrate from the digester. Furthermore, the study assessed the necessity of modifying the Monod kinetics to account for substrate inhibition by incorporating the Haldane term in the VFAs uptake kinetic model, which proved to be essential for better interpreting batch activity tests.