Predictive control of wastewater treatment plants as energy-autonomous water resource recovery facilities

This work proposes an automatic control solution for the operation of conventional wastewater treatment plants (WWTPs) as energy-autonomous water resource recovery facilities. We first conceptualize a classification of the quality of treated water for three resource recovery applications (environmental, industrial, and agricultural water reuse). We then present an output-feedback model predictive controller (Output MPC) that operates a plant to produce water of a specific quality class, while also producing sufficient biogas to ensure nonpositive energy costs. Using well-established simulation models, we analyze the controller performance on the long-term operation of a biological WWTP subjected to typical influent loads and periodically changing quality targets. Our experiments show that conventional WWTPs are flexible enough to transition from pollution abatement to resource recovery. The plant is also shown to have an energy-positive operating regime, that is, it can recover more energy than needed for its operation. Under closed-loop operation, the WWTP achieves the nutrient recovery targets while producing 83 GWh/year of surplus energy, with an average throughput of 2 385 kWh/day. The results provide a proof-of-concept for the energy-autonomous operation of existing wastewater treatment infrastructure with control strategies that are general enough to accommodate different resource recovery tasks.