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Modelling, identification and control of the activated sludge process

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Lignocellulosic Materials

Part of the book series: Advances in Biochemical Engineering/Biotechnology ((ABE,volume 38))

Abstract

Practical experience shows that the efficiency and reliability of the activated sludge wastewater treatment process can be significantly improved if its time-varying nature is taken into account in the design of automatic control systems. This paper focuses on the dynamic aspects of the activated sludge treatment process and assesses the operational improvements brought about by automatic control. The three aspects of modelling, identification and control are reviewed and their interdependence is stressed. After introducing a simplified model for the pollutant/biomass interaction, the estimation and control problems are addressed and practical algorithms are discussed. The improvements brought about by such algorithms are clearly demonstrated.

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Abbreviations

A:

secondary settler cross section [m2]

C:

dissolved oxygen concentration [mg l−1]

Ci :

input dissolved oxygen concentration [mg l−1]

Csp :

dissolved oxygen set-point [mg l−1]

Csat :

dissolved oxygen saturation value [mg l−1]

D:

dissolved oxygen deficit [mg l−1]

F:

total setting flux [kg m−2 h−1]

Fm :

food-to-mass ratio [kg g−1 d−1] (BOD per MLSS per time)

h:

sampling interval [h]

hb :

sludge blanket height [m]

Ka :

air transfer coefficient [Nm−3]

Kb :

substrate decay rate (SML) [mg−1 l h−1]

Kc :

biomass specific growth rate (SML) [mg−1 l h−1]

Kd :

microbial decay rate (Monod) [h−1]

Km :

biomass endogeneous metabolism rate (SML) [h−1]

Kn :

nitrifiers decay rate [h−1]

Ko :

dissolved oxygen half-velocity constant [mg l−1]

Ks :

half-velocity constant (Monod) [mg l−1]

Kam :

ammonium-nitrogen half-velocity constant [mg l−1]

KLa:

oxygen diffusion rate coefficient [h−1]

M:

accumulated biomass in the settler [kg]

Na :

nitrate-nitrogen concentration [mg l−1]

n, a:

batch flux settling curve parameters [−]

Q:

process hydraulic flow rate [m3 h−1]

q:

dilution rate [h−1]

r, w:

recycle and waste flow fractions [−]

S:

substrate (BOD) concentration [mg L−1]

Si :

input substrate (BOD) concentration [mg l−1]

Sam :

ammonium-nitrogen concentration [mg l−1]

Sexp, Xexp, Cexp :

substrate, biomass, and DO measurements [mg l−1]

t, t1 :

time [h]

Ua :

air flow rate [Nm3 h−1]

u:

settling sludge bulk settling velocity [m h−1]

X:

biomass concentration [mg l−1]

Xa :

settler sludge density above sludge blanket [mg l−1]

Xb :

settler sludge density below sludge blanket [mg l−1]

Xe :

sludge concentration in the effluent [mg l−1]

Xn :

nitrifying bacteria concentration [mg l−1]

Xr :

recycle biomass concentration [mg l−1]

Xsp :

sludge set-point [g l−1]

Y:

yield factor (Monod) [−]

Ya :

nitrifiers yield factor [−]

θ:

hydraulic retention time [h]

θc :

solids retention time (sludge age) [d]

µ:

maximum specific growth rate (Monod) [h−1]

µn :

nitrifiers maximum specific growth rate [h−1]

γe :

oxygen utilization coefficient for endogenous metabolism [−]

γn :

oxygen utilization coefficient for nitrification [−]

γs :

oxygen utilization coefficient for synthetic activities [−]

ζ:

feed height above settle bottom [m]

BOD:

biochemical oxygen demand [mg l−1]

DO:

dissolved oxygen [mg l−1]

LS:

least squares estimation algorithm

MLSS:

mixed liquor suspended solids [mg l−1], as a global measure of biomass in the activated sludge plant

OUR:

oxygen uptake rate [mg l−1 h−1]

SCOUR:

specific oxygen uptake rate [mg g−1 h−1]

SML:

substrate/biomass reduced-order model, after the author's initials

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  1. Department of Systems and Computers Engineering, University of Florence, Via S. Marta, 3-50139, Firenze, Italy

    Stefano Marsili-Libelli

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  1. Stefano Marsili-Libelli
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Marsili-Libelli, S. (1989). Modelling, identification and control of the activated sludge process. In: Lignocellulosic Materials. Advances in Biochemical Engineering/Biotechnology, vol 38. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0007860

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  • DOI: https://doi.org/10.1007/BFb0007860

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