A novel mathematical model for predicting performance of the sequential batch anaerobic digestion process: Part I

Anaerobic digestion (AD) is a promising technology to produce renewable energy from organic wastes and achieve desirable solids reduction. One critical step for successful and continuous operation of an AD system is the startup phase, when fresh feedstock is added periodically to the digester after a portion of finished material is discharged, until reaching a pseudo-steady state. This process, identified as a sequential batch AD process, describes how many solid-state and liquid AD systems are managed. Currently, the startup and optimization of such a digester is largely determined by trial and error based on several months of continuous monitoring and adjustment by experienced operators. This research proposes a novel mathematical model to predict outputs per unit volume of a sequential batch AD process during the startup phase as well as at steady state. Important model inputs include the feedstock’s total solids (TS) content, degradable solids content (), digestion rate (k), batch time (∆t), digestate recycle rate (r), and water supplementation (X2). The model predicts the total methane yield (U), final end product TS and, and mass quantity (X₁, Q_in, Q_CH4) at steady state. The model provides useful information for the design, operation, and optimization of large-scale AD digesters. Equations are used to identify r values for stable reactor performance given k and ∆t, assuming ratios of feedstock to digestate between 1 and 6.