Energy saving in the aeration process by fuzzy logic control

Ferrer, J.; Rodrigo, Manuel A.; Seco, A.; Penya-Roja, J. M.

doi:10.2166/wst.1998.0210

Cited by 40 publications

(30 citation statements)

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“…These tasks call for deeper investigation of the oxygen transfer process in the wastewater aeration tank. The actual problems and tasks on the subject of the development of the wastewater treatment technology, efficiency and process automatic control have been widely investigated and discussed [1,2,3,4].…”

Section: Introductionmentioning

confidence: 99%

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Adaptive Model of Wastewater Aeration Tank

Sniders¹,

Laizans²

2011

Scientific Journal of Riga Technical University. Environmental and Climate Technologies

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-The paper discusses the methodology of oxygen transfer virtual simulation in a wastewater biological treatment process, using the MATLAB/SIMULINK technology. A selftuning adaptive model of a wastewater aeration tank, as a nonstationary object, with variable time dependent sensitivity and inertia indexes, as the functions of input variable -air pneumatic supply capacity L g (t) (m 3 /min), output variable -dissolved oxygen concentration C(t) (g/m 3 ) and oxygen expenditure, as a load -q(t) (g/min), required for wastewater complete purification, is expounded. Virtual models, applying Laplace transforms and SIMULINK blocks library, are composed in order to compare the transient processes of dissolved oxygen concentration in the simplified stationary model with constant sensitivity and inertia coefficients, and in the non-stationary model with variable sensitivity and inertia indexes. The simulation block-diagram for non-stationary model adoption to the variable parameters is developed, using informative links from input variable L g (t), from variable load q(t) and feedback from output variable C(t) as inputs of calculation modulus, allowing to instantly re-calculate the variable indexes during simulation time. Comparison of the simplified stationary model and the non-stationary model shows that the simulation results of oxygen transfer differ up to 50%.

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Section: Introductionmentioning

confidence: 99%

“…The optimal regulation of air blowers capacity in order to reach the maximum efficiency is the major and most important activity on the way to increase the overall economic feasibility of municipal wastewater biological treatment [2,3,5].…”

Section: Introductionmentioning

confidence: 99%

Adaptive Model of Wastewater Aeration Tank

Sniders¹,

Laizans²

2011

Scientific Journal of Riga Technical University. Environmental and Climate Technologies

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“…The control objective and parameters ranged from aeration T. J. Ferrer, 1998. T. Kalker, 1999 Meyer et al (2003) for the control of aeration in wastewater treatment plants with pre-denitrfication.…”

Section: Introductionmentioning

confidence: 99%

A Fast Predicating of Nutrient Removal Efficiency in Five Steps Sequencing Batch Reactor System Using Fuzzy Logic Control Model

Abualhail¹

2010

Engineering

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Removal efficiency of COD, NH4-N and PO4-P and NO3-N in five step SBR processes is widely influenced by hydraulic retention time of Anaerobic/Anoxic/Aerobic/Anoxic/Aerobic step of this system where the hydraulic retention time in each step is influence directly on removal efficiency of this system therefore the operator of this system cannot control on this system without experience or a control model. The major objective of this paper is develop a control model (Fuzzy Logic Control Model) based on fuzzy logic rule to predict the maximum removal efficiency of COD,NH4-N,PO4-P and NO3-N and minimize hydraulic retention time in each step of SBR process where the controlled variables was the hydraulic retention times in the Anaerobic/Anoxic/Aerobic/Anoxic/Aerobic step respectively and the output variables was the COD, NH4-N, PO4-P and NO3-N removal efficiency at constant ratio of C/N/P and sludge age. As a results Fuzzy logic if-then rules were used and MIMO Model was built to control COD, NH4-Nand PO4-P and NO3-N removal efficiency based on hydraulic retention time in each tank of five step SBR process where the three dimension results show that the influence of hydraulic residence time at each step of SBR system on removal efficiency COD, NH4-N, PO4-P and NO3-N. Fuzzy control model provide a suitable tool for control and fast predict of Hydraulic residence time effects on biological nutrient removal efficiency in five-step sequencing batch reactor.

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“…una alta concentración de oxígeno puede causar problemas en la eficiencia del proceso de desnitrificación (el cual requiere condiciones anóxicas) y consumir cantidades excesivas de energía (Ferrer, 1998;Serralta et al, 2002). Diversos estudios se han enfocado en mejorar el control de las concentraciones de oxígeno disuelto en los sistemas de tratamiento (Ferrer, 1998;Ma et al, 2004).…”

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“…Diversos estudios se han enfocado en mejorar el control de las concentraciones de oxígeno disuelto en los sistemas de tratamiento (Ferrer, 1998;Ma et al, 2004).…”

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