(689f) Modeling of Anaerobic Digester Using Anaerobic Digestion Model No. 1 (ADM1) in Idaes/Pyomo

Anaerobic Digestion (AD) is inarguably the most widely used industrial process (or green technology) for treating various forms of waste while simultaneously producing methane-rich biogas (bioenergy) and nutrient-rich digestate (organic fertilizer) [1,2,3]. However, AD is marred by process instability under certain operating conditions, which tends to cause the process to fail [3,4]. Model-based analysis, including reactor design and control, can help alleviate these issues, by studying AD design concepts and control architectures that support stability in operation. The need for such models and the complexity of the reactions involved in AD led to the development of a generic and dynamic model called Anaerobic Digestion Model No 1 (ADM1). ADM1 is a structured model developed by the International Water Association (IWA) task group for the mathematical modeling of anaerobic digestion processes. The model has been widely applied and implemented by engineers, operators, and process technology providers for full-scale plant design, operation, process optimization, and control [5].

In this work, the ADM1 model was applied to the anaerobic digestion process of a wastewater treatment plant, with the aim of assessing the life cycle and techno-economic benefits of advanced control architectures, while also predicting the process operating conditions and performance. The ADM1 equations were implemented as differential and algebraic equations (DAE) in the modeling language of Pyomo in the user-friendly environment of IDAES. Pyomo and IDAES are algebraic modeling languages developed as Python-based open-source software packages and are used for designing, formulating, solving, and analyzing diverse sets of optimization models. The ADM1 deployed consists of 32 dynamic state concentration variables and 19 biochemical rate processes [5]. An energy balance was introduced to study temperature disturbance effects and their impact on the dynamic behavior of the AD system. The model was applied to a single-tank digester and simulation results showed that the ADM1 model could predict with good accuracy the process operating conditions such as the pH, gas flows, concentrations of effluents, temperature, methane, and carbon-dioxide contents, at different hydraulic retention times (HRTs). The amount of biogas produced over different HRTs was also determined by the model. The results obtained were validated against literature and commercial data.

Acknowledgments

This study was supported by the U.S. Department of Energy’s Office of Energy Efficiency and Renewable Energy (EERE) under the Advanced Manufacturing Office, Award Number DE-EE0009497.

References

[1] F. Boubaker, and B. C. Ridha, “Modelling of the mesophilic anaerobic co-digestion of olive mill wastewater with olive mill solid waste using anaerobic digestion model No. 1 (ADM1),” Bioresource Technology, vol. 99, pp. 6565-6577, Jan. 2008, doi: 10.1016/j.biortech.2007.11.035.

[2] L. Yu, P. C. Wensel, J. Ma, and S. Chen, “Mathematical Modeling in Anaerobic Digestion (AD),” J Bioremed Biodeg, S4: 003, doi: 10.4172/2155-6199.S4-003.

[3] L. A. Cruz et al., “Application of machine learning in anaerobic digestion: Perspectives and challenges,” Bioresource Technology, vol. 345, Nov. 2021, doi: 10.1016/j.biortech.2021.126433.

[4] O. Bernard et. al, “Dynamical model development and parameter identification for an anaerobic wastewater treatment process,” Biotechnology and bioengineering, vol. 75, pp. 424-438, Jun. 2001, doi: 10.1002/bit.10036.

[5] D. J. Batstone et al., “The IWA Anaerobic Digestion Model No 1 (ADM1),” Water science and technology: a journal of the International Association on Water Pollution Research, vol. 45, 10, pp. 65-73, 2002.