Modeling of an Industrial Wastewater Treatment System Using Historical Process Data

In this paper, the predictive capacity of a wastewater treatment process model was studied to find out how well the model works and to propose its use as a tool to help improve control of effluent BOD (biochemical oxygen demand) for the wastewater treatment facility being studied. The mathematical process model for the existing facility was obtained from literature with few added modifications to accommodate certain requirements of the actual setup. A Complete Mix Flow Reactor with recycle was assumed together with Manod and Contois growth models for the microbial growth kinetics assumptions. Using historical process data from the daily operations of the plant, model parameters were estimated and then verified using linear regression. The results of the study show that the user of historical process data posed some limitations to modeling that resulted to moderate correlations between observed and predicted values for effluent BOD except for the prediction of average MLSS. Despite these observations, it was found out that Monod-based model works better than the Contois-based model for the wastewater treatment system studied.