(569dk) Aspen Based Simulation and Optimization of Biogas Production from Anaerobic Digestion of Cow Dung

Biogas production from anaerobic digestion (AD) of cow dung enhances access to safe and clean energy. Hence, the need to optimize the process for improve access to sustainable renewable energy. This study presents simulation, predictive modelling and optimization of biogas production from AD of cow dung. Input-output data generated via process simulation model (PSM) were used for response surface methodology (RSM) and artificial neural network (ANN) models. The input variables to the models include temperature, hydraulic retention time (HRT) and operating pressure, while biogas yield is the response. The adequacy of the developed models for predicting biogas production was determined by coefficient of determination (R²). The most influential operating parameter for biogas production from cow dung was identified via sensitivity analysis. The results obtained showed that simulation result (447.19 mL/kg VS) mimics experimental result (451.70 mL/kg VS) adequately. The R² values for RSM- and ANN-based models are 0.992 and 0.998, respectively. Though, ANN-based model marginally performed better than RSM-based model, both developed models performed adequately for biogas prediction. The optimal biogas yield (326.22 mL/kg VS) was obtained at temperature (34.74^oC), HRT (21.67 days) and pressure (1.01 bar). Sensitivity analysis showed pressure has the most influential operating parameter. It concluded from the study that the models developed can serve as template for future study on access to sustainable renewable energy.