Control of Nitrogen Removal in Activated Sludge Processes

Samuelsson, P. 2005. Control of Nitrogen Removal in Activated Sludge Processes. Written in English. Acta Universitatis Upsaliensis. Uppsala Dissertations from the Faculty of Science and Technology 64. 156 pp. Uppsala, Sweden. ISBN 91-5546311-8. More stringent requirements on nitrogen removal from wastewater are the motivation for this thesis. In order to improve treatment results and enhance cost-efficient operation of wastewater treatment plants, model based control strategies are presented. A Java based simulator for activated sludge processes (JASS) is presented. The graphical user interface, educational experiences and implemented control strategies are discussed. Controlling the addition of an external carbon source is the next topic discussed. A simple model based feedforward controller is derived and evaluated in a simulation study. The controller attenuates process disturbances quickly. Further, two feedforward controllers for adjusting the aeration volume in activated sludge processes are derived. The aim of the volume control strategies was to efficiently dampen the impact of process disturbances without using an excessively high dissolved oxygen concentration. The simulation results are promising and show that the aeration volume may be a feasible control variable. A linearisation method for static input non-linearities is presented. The method gives essentially the same result as the existing standard method, but possesses some implementational advantages. The method is used to linearise the non-linear oxygen transfer function of an activated sludge process in an application study. Multivariable interactions in a process model describing nitrate removal in an activated sludge process are studied using the well known RGA method as well as a relatively novel tool based on Hankel norms. The results of the analysis are compared to conclusions drawn from common process knowledge and are used to design a multivariable control strategy. It was found that process disturbances may be rejected faster using multivariable control. Finally, the operational costs of the denitrification process are investigated and visualised graphically. Cost optimal regions are found by a numerical grid search. Procedures for controlling the denitrification process in a cost-efficient way are described.