TY - JOUR
T1 - On the derivation of a simple dynamic model of anaerobic digestion including the evolution of hydrogen
AU - Giovannini, Giannina
AU - Sbarciog, Mihaela
AU - Steyer, Jean Philippe
AU - Chamy, Rolando
AU - Vande Wouwer, Alain
N1 - Publisher Copyright:
© 2018 Elsevier Ltd
PY - 2018/5/1
Y1 - 2018/5/1
N2 - Hydrogen has been found to be an important intermediate during anaerobic digestion (AD) and a key variable for process monitoring as it gives valuable information about the stability of the reactor. However, simple dynamic models describing the evolution of hydrogen are not commonplace. In this work, such a dynamic model is derived using a systematic data driven-approach, which consists of a principal component analysis to deduce the dimension of the minimal reaction subspace explaining the data, followed by an identification of the kinetic parameters in the least-squares sense. The procedure requires the availability of informative data sets. When the available data does not fulfill this condition, the model can still be built from simulated data, obtained using a detailed model such as ADM1. This dynamic model could be exploited in monitoring and control applications after a re-identification of the parameters using actual process data. As an example, the model is used in the framework of a control strategy, and is also fitted to experimental data from raw industrial wine processing wastewater.
AB - Hydrogen has been found to be an important intermediate during anaerobic digestion (AD) and a key variable for process monitoring as it gives valuable information about the stability of the reactor. However, simple dynamic models describing the evolution of hydrogen are not commonplace. In this work, such a dynamic model is derived using a systematic data driven-approach, which consists of a principal component analysis to deduce the dimension of the minimal reaction subspace explaining the data, followed by an identification of the kinetic parameters in the least-squares sense. The procedure requires the availability of informative data sets. When the available data does not fulfill this condition, the model can still be built from simulated data, obtained using a detailed model such as ADM1. This dynamic model could be exploited in monitoring and control applications after a re-identification of the parameters using actual process data. As an example, the model is used in the framework of a control strategy, and is also fitted to experimental data from raw industrial wine processing wastewater.
KW - Mathematical modeling
KW - Parameter estimation
KW - Principal component analysis
KW - Sensitivity analysis
UR - http://www.scopus.com/inward/record.url?scp=85041417479&partnerID=8YFLogxK
U2 - 10.1016/j.watres.2018.01.036
DO - 10.1016/j.watres.2018.01.036
M3 - Article
C2 - 29427963
AN - SCOPUS:85041417479
SN - 0043-1354
VL - 134
SP - 209
EP - 225
JO - Water Research
JF - Water Research
ER -