Modeling of a UASB Reactor by NARX Networks for Biogas Production

Abstract

Abstract An Artificial Neural Network model of a UASB Reactor has been developed. The reactor treats bagasse wash water (containing organics), generated after washing of stored bagasse prior to its use in paper manufacture. In the process, biogas, a renewable source of energy is produced. As the UASB reactors (2×5,000 m3 volume) operate mostly with feed having varying characteristics, therefore a special type of dynamic networks, called NARX networks have been used to model it for predicting biogas production rate. The input to the model is influent flow rate, inlet and outlet COD. Model is based upon 576 days plant data. NARX model architecture consists of input, output, and 2 hidden layers each having 10 neurons and utilizes 4 days delay. The developed ANN model represents the dynamic behavior of UASB reactor and recursively predicts and forecasts the biogas production rate with acceptable deviation with respect to actual production rate.