A comparative study on biogas production from food waste using Aspen Plus and Artificial Neural Networks (ANN)

The goal of this research was to simulate and make a comparative study between Aspen Plus and Artificial Neural Networks (ANN) for the anaerobic digestion of food waste at different temperatures, Organic Loading Rates (OLR) and Hydraulic Retentions Time (HRT) variations, using a two-stage digester setup. The Anaerobic Digestion Model 1 (ADM1) included 13 hydrolysis reactions and 33 acidogenesis, acetogenesis and methanogenesis reactions. In addition, the retention time was set at 7, 10, 20, 30 and 40 days and a Stoichiometric and a Continuous Stirred tank reactors were used at 37°C and 55°C respectively. Conversely, the ANN model used 140 data samples for training, testing and validation. The ANN model used 6 biogas input parameters (biomass type, pH, OLR, HRT, temperature, and reactor volume) in order to predict the methane content from the anaerobic digestion of food waste.