An Identification and Control Framework for Optimizing the Energy Consumption of a Wastewater Treatment Plant

Wastewater treatment plants (WWTPs) play a key role in circular economies, as they are capable of recycling large volumes of polluted water. One of the biggest challenges, though when considering such large-scale plants, is the fact that they consume a great amount of power in order to operate properly. In this work, the problem of optimizing the energy efficiency of WWTPs is addressed by presenting an economic dynamic matrix control (EDMC) formulation for industrial-scale WWTPs. To derive predictive models that are accurate and at the same time suitable for integration in EDMC without the need to perform cumbersome tests on the real plant, we first make use of a cooperative particle swarm optimization solver in order to identify a number of important parameters included in a detailed first principles model of the process; the identified detailed model is then used to derive the much simpler step-response predictive models needed for designing the EDMC scheme. The proposed approach is shown to provide higher energy efficiency when compared against a standard DMC controller, while also satisfying environmental regulations.