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A simulation benchmark to evaluate the performance of advanced control techniques in biological wastewater treatment plants

Wastewater treatment plants (WWTP) are complex systems that incorporate a large number of biological, physicochemical and biochemical processes. They are large and nonlinear systems subject to great disturbances in incoming loads. The primary goal of a WWTP is to reduce pollutants and the second goal is disturbance rejection, in order to obtain good effluent quality. Modeling and computer simulations are key tools in the achievement of these two goals. They are essential to describe, predict and control the complicated interactions of the processes. Numerous control techniques (algorithms) and control strategies (structures) have been suggested to regulate WWTP; however, it is difficult to make a discerning performance evaluation due to the nonuniformity of the simulated plants used. The main objective of this paper is to present a benchmark of an entire biological wastewater treatment plant in order to evaluate, through simulations, different control techniques. This benchmark plays the role of an activated sludge process used for removal of organic matter and nitrogen from domestic effluents. The development of this simulator is based on models widely accepted by the international community and is implemented in Matlab/Simulink (The MathWorks, Inc.) platform. The benchmark considers plant layout and the effects of influent characteristics. It also includes a test protocol for analyzing the open and closed-loop responses of the plant. Examples of control applications in the benchmark are implemented employing conventional PI controllers. The following common control strategies are tested: dissolved oxygen (DO) concentration-based control, respirometry-based control and nitrate concentration-based control.

simulation benchmark; activated sludge processes; wastewater treatment plants; organic matter removal; nitrogen removal; DO concentration-based control; nitrate concentration-based control; respirometry-based control; process control


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