Electricity Generation Performance of Microbial Fuel Cell Embedded in Anaerobic-Anoxic-Oxic Wastewater Treatment Process

Microbial fuel cell (MFC) embedded in anaerobic-anoxic-oxic (A2/O) process has positive effects on wastewater treatment, which can enhance the efficiencies of pollutants’ removal, along with electricity production. But the electricity generation performance and its optimization of MFC embedded in A2O process still needs to be further investigated. In this study, in order to optimize the contaminants removal and electricity production of the MFC-A2/O reactor, a lab-scale corridor-style MFC-A2/O reactor, which could simulate the practical A2/O biological reactor better, was designed and operated. The removal efficiencies of chemical oxygen demand, total nitrogen and total phosphorus were continuously monitored so as the electricity generation. In addition, the influences of the structural parameters’ changes of MFC on the output voltage, including electrode material, the directly connected area and the distance between electrodes, were also studied. The results elucidated that the effluent quality of A2/O reactor could be improved when MFC was embedded, and all the investigated structural factors were closely related to the electricity generation performance of MFC to some extent.

Robust optimal control for anaerobic-anoxic-oxic reactors

Anaerobic-anoxic-oxic(A_2O) reactors, as the core parts of wastewater treatment process(WWTP), have attracted considerable attention to achieve the reliability of denitrification and dephosphorization. However, it is difficult to realize the optimal operation of A_2O reactors due to the existence of nonlinear dynamics and large uncertainties. To solve this problem, a robust optimal control(ROC) strategy is developed to improve the operation performance of A_2O reactors. First, data-driven systematic evaluation criteria are developed to describe the operational indicators of changeable conditions. Second, a robust optimization algorithm is designed to select the optimal solution. Third, a fuzzy neural network(FNN) is used to track the optimal solution in the control process. Finally, this proposed ROC strategy is applied to the phosphorus removal benchmark simulation model(BSM1-P) and the real A_2O reactors. The results demonstrate that the strategy developed in this paper has great potential for application in real A_2O reactors.

Feedforward control for nitrogen removal in a pilot-scale anaerobic-anoxic-oxic plant for municipal wastewater treatment

To improve the efficiency of nitrogen removalwith lower energy consumption,the study of feedforwardcontrol was carried out on a pilot-scale anaerobic-anoxicoxic(AAO)plant for the treatment of municipal wastewater.The effluent qualities of the pilot plant underdifferent control strategies were investigated.The resultsindicated that the change of external recycle was not asuitable approach to regulate the sludge concentration ofplug-flow reactors;adjusting the aeration valve anddissolved oxygen set-point according to ammonia loadcould overcome the impact of influent fluctuation;and thedenitrification potential could be estimated based on thetransit time of anoxic zone and the relative content ofcarbon resource entering the anoxic zone.Simple feedforwardcontrol strategies for aeration and internal recyclewere subsequently proposed and validated.The nitrogenremoval was successfully improved in the pilot plant.Theeffluent total nitrogen had decreased by 29.9%and wassteadily controlled below 15 mg·L^(-1).Furthermore,approximately 38%of the energy for aeration had beensaved.