An Economic-Oriented Model Predictive Control Framework for the Efficient Energy Operation of Wastewater Treatment Plants

Wastewater treatment plants (WWTPs) are highly complex large-scale plants that require substantial electrical power to operate properly; thus, the task of optimizing their operation by controlling them efficiently is a significant challenge, necessitating the use of advanced control schemes. However, the mathematical models used to simulate their dynamic behavior with high accuracy are extremely complex and cannot be utilized in the design of advanced closed-loop controllers. To this end, in this work, an economic-oriented nonlinear model predictive controller is developed by employing a reduced-order model of WWTPs, which is suitable for integration into predictive control schemes. The presented methodology aims to optimize the energy consumption during full scale operation of WWTPs, while simultaneously satisfying the strict limitations posed by specific environmental criteria. The proposed approach is compared against an alternative control scheme and the results validate its superiority in terms of reducing the energy consumption and total operational costs.