Modeling and optimization of anaerobic digestion technology: Current status and future outlook

Abstract

Anaerobic digestion (AD) is an important technology that can be engaged to produce renewable energy and valuable products from organic waste while reducing the net greenhouse gas emissions. Due to the AD process complexity, further development of AD technology goes hand in hand with the advancement of underlying mathematical models and optimization techniques. This paper presents a comprehensive and critical review of current AD process modeling and optimization techniques as well as various aspects of further processing of AD products. The most important mechanistically inspired, kinetic, and phenomenological AD models and the most frequently used deterministic and stochastic methods for AD process optimization are addressed. The foundations, properties, and features of these models and methods are highlighted, discussed, and compared with respect to advantages, disadvantages, and various performance metrics; the models are also ranked with respect to adequately introduced criteria. Since AD process optimization affects heavily the required treatment and utilization of AD products, biogas and digestate utilization in the production of renewable energy and other valuable products is also addressed. Furthermore, special attention is devoted to the challenges and future research needs related to AD modeling and optimization, such are modeling issues related to foaming and microbial activities, AD model parameters calibration, CFD simulation challenges, availability of experimental data, and optimization of the AD process with respect to further biogas and digestate utilizations. As current research results indicate, further progress in these areas could notably improve AD modeling robustness and accuracy as well as AD optimization performance.