Tag Archives: artificial intelligence

[EN] WDOxy/Fuzzy-control for improved Nitrogen Removal and Energy Saving in WWTP with predenitrification


Application of fuzzy-logic to improve the control of the activated sludge process. WDOxy-Controller is a dynamic (non-deterministic/fuzzy) approach model to “Dissolved Oxygen Control Strategy” in wastewater nutrient removing, basically based on using of Ione Selective (NH4+, NO3-) on-line analyzers, but in option it is possible to use on-line ORP/pH (Redox potential) low-cost sensors too. Fuzzy-logic based control strategies for wastewater treatment plants with pre-denitrification should lead to better effluent quality and, in parallel, to a reduction of energy consumption. The WDOxy goal is to develop a “dynamic DO set-up on need” calculation able to provide a continuous nutrient removal process control, under legal outlet limits and within a sustainable energy saving control. Compared to the operation with fixed nitrification/denitrification zones and constant DO concentrations, the required air-flow could be reduced up to 24% by using fuzzy-logic based control strategies. In fact, Traditional “DO Closed Loop Control” (aeration control) is a well-known automation procedure that does not allows to timely face the real need of oxidation that biological process dynamically requires from time to time. On the contrary, WDOxy control is able to face DO requirement, in all nutrient removal biological processes (N and P), in a cost efficient way, that means, by dosing energy on the base of a real-time evaluation of biomass metabolism.


The WDOxy fuzzy-controller procedure can be easily implemented in modern control and supervision systems and  the control characteristics can be followed and modified during operation.


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