Model-based optimization of water resource recovery facilities

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An important change is happening to the wastewater industry: a paradigm shift is occurring from an industry that treats wastewater to an industry that brings a more positive message: it produces clean water, and recovers fertilizers and energy contained in ‘used’ water. The fact that WRRFs aim at delivering valued products that can partially replace those produced by other means (typically in the chemical industry) leads to a big change in specifications of the outputs of the facility: no longer treated wastewater and biosolids, but products that have to compete with what is already on the market. These tighter specifications will impose a challenge on the process control systems that will be required to guarantee the quality of the products of the WRRFs. Given the difficulties in collecting high quality data on which the control systems rely to act upon the system (recent practical studies using partially automated data validation report data losses of 5 to 60%), important research efforts have to be deployed to create the process monitoring and control systems that maintain these tight product specifications at all time. Over the next 5 years the research program of this Discovery grant will develop control systems that benefit from the ability of new algorithms to not only reliably detect faults in the measurement equipment but can also find out what is wrong with the sensors (fault diagnosis). With this knowledge the problem can of course be handled through proper maintenance or replacement of the sensor, but until that happens, the control system must be able to still perform adequately. Fault-accommodation is the methodology that is then put in place and methods will be developed to replace the faulty data by using either historical information or simple models. In case the fault is too disruptive, a different control strategy will have to be adopted that does not rely on these data. A so-called control reconfiguration based on a fall-back strategy has to occur. Finally, because the requirements imposed on resource recovery facilities are becoming so much more stringent, a control approach that seems particularly suited for this type of situations with multiple objectives and complex behavior, will be evaluated: Extermum seeking control. Its intuitive nature will make sure that the results of this research have a good chance to make it to practice and generate the anticipated advances in performance. The project will train 8 graduate students (4 PhD and 4 MSc), at least 3 undergraduates, a postdoctoral fellow and a technician responsible for the industry standard pilot plant on which the different methods will be developed and tested. These HQP will acquire a wide range of skills thanks to the involvement in the different aspects of the research project, the exposure to national and international research and to practice through the work on an industry standard pilot facility.