optimal operation of alternating activated sludge … · · 2010-05-19optimal operation of...

Fourteenth International Water Technology Conference, IWTC 14 2010, Cairo, Egypt

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OPTIMAL OPERATION OF ALTERNATING ACTIVATED SLUDGE PROCESSES OF THE MUNICIPAL WASTEWATER

TREATMENT PLANT CASE OF SOUK-AHRAS (ALGERIA)

S. Dairi 1*, D. Mrad 1, M. Bensoltane 1, Y. Djebbar 1 and H. Abida 2

1 University of Souk-Ahras, Algeria

* E-mail: [email protected] 2 University of Sfax, Tunisia

ABSTRACT This research study using a software tool (GPS-X) looks at simulating biological and hydraulic processes at the Souk-Ahras WWTP in order to obtain an optimal solution from a purification performance view point and to provide essential operating rules to enable operation staff to better technically and scientifically base the management of the plants. It allows the operation staff to comply with the current regulations, and further optimize public investment. This approach may be seen as part of the diagnosis of the plant to ensure production of treated wastewater that can be used for the irrigation of a proposed 300 ha irrigation scheme. The study presents dynamic optimisation of a medium size wastewater treatment plant. We used the approach proposed by IAWQ activated sludge model No 1 (ASM1). The objectives are to determine an optimal sequence of aeration/non-aeration times so that for a typical diurnal pattern of disturbances, the effluent constraints are respected, the plant remains in periodical steady state, and energy consumption is minimised. Based on the optimal state trajectories results, two simple feedback rules are proposed. Simulation results with these rules show very satisfactory control performance. Keywords: Wastewater characterization; Wastewater treatment; Activated sludge

process; Dynamic optimisation; ASM1 model; GPS-X 1. INTRODUCTION A widely used system for biological wastewater treatment is the activated sludge process (ASP). The removal of nitrogen (N) requires two biological processes: nitrification and denitrification. The former takes place under aerobic conditions, whereas the latter requires anoxic environment. For small size plants, i.e. less than 20,000 p.e. (population equivalent), the two processes are very often carried out in a single basin using surface turbines. The nitrification process (respectively denitrification process) is realised by simply switching the turbines on (respectively off).

Fourteenth International Water Technology Conference, IWTC 14 2010, Cairo, Egypt 432

Among the issues to be addressed in order to improve the functioning of small size wastewater plants, the effluent quality and the total operation costs are important. Of course these issues are not independent since the pollution reduction generally involves additional costs (investment, operation ...). The choice of the aforementioned issues is motivated below: • Effluent quality: During the last decade, a stricter European Union (EU) directive

(91/271 “Urban wastewater”) came out and fixed the maximum pollutant concentrations allowed in the effluent of small size wastewater treatment plants. For example, for the most restrictive component, i.e. total nitrogen (TN), the maximum concentration is fixed at 10 mg/l.

• Operation costs: The main component of total operation costs of small size wastewater plants is constituted by the energy dissipated by the system of aeration (turbines) (Vasel, 1988). Oxygen control is therefore of great importance since the decrease of the total period of aeration reduces significantly the operation costs.

The main challenge of the control of activated sludge processes is disturbances rejection. The objective is to avoid excessive aeration and to maximise the conversion rates of the biological processes. The most important source of disturbances is the influent. Its characteristics are large diurnal variations both in flowrate and composition (the result of characteristic life patterns of households). Even if the large reactor volume dampens this diurnal cycle, just by dilution, there remains a significant task for active control. The other important sources of disturbances are rain/storm events that may cause serious overloading incidents or in winter time when the growth rate of biomass is severely inhibited by low temperature. Control of the ASP has been the subject of a large number of research studies. More control oriented are for example the works of Kim et al. (2000) that use simplified linearized model with aeration time as the manipulated variable, Qin et al. (1997) have employed interpolating Model Predictive Control, or Lindberg (1998) has used linear multivariable LQ control. The studies that investigate the problem from the process point of view include for example the works of Isaacs (Isaacs, 1997, 1996; Zhao et al., 1995, 1994b). A comparison of several control strategies has been investigated in Lukasse et al. (1999); Potter et al. (1996); Debusscher et al. (1999). The aim of this work is to determine an optimal duration of the aeration and non aeration sequences which will minimise the operation costs as well as satisfy the constraints specified by the EU directives. Based on the analysis of the optimal operational policy, simple feedback rules will be formulated. The rest of the paper is organised as follows. Section 2 introduces the dynamic model considered. Section 3 defines the optimisation problem, discusses the choice of the control variables, and specifies control and state constraints. Main results are presented in Section 4 where a periodic stationary regime is found. Finally, Section 5 concludes the paper.


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2. WASTEWATER TREATMENT PLANT MODEL 2.1. Process With aim of respecting the provisions of the law water, to get a better management for public investments, to ensure a production of water purified agricultural ends, and in order to help the operators with better operating the purification plants of waste water (WWTP) the computer tools of modelling became essential. This last is necessary for the knowledge of purification mechanisms of the WWTP. This research aims at carrying out biological and hydraulic simulations various processes of WWTP in Souk-Ahras (Algeria) to obtain an optimal solution from the point of view purification performances and to offer essential elements to make it possible to the persons in charge of the communities better to technically be based scientifically and their management of the purification plants, because the effectiveness and the reliability of biological purification, management of mud’s remain narrowly dependent with various physical measurements presenting l' d' favours; to be quickly accessible and thus to lend itself to a regulation on line. These physical measurements carry according to our study on:

• Concentration of Oxygen dissolved in the basin of ventilation. • Concentration of activated sludge mixed liquor contained in this basin

ventilation. • Crossing of flow effluent in basin ventilation, (Qt + Qr). • Residence time of the biomass.

Figure 1: Process of waste water treatment by activated sludge From these measurements, this step provided with one equips simulation GPS-X allows to reach a whole series of fundamental information scenarios on state of the station in Souk Ahras to try a better include, understand the influence of these variations (quantitative but also qualitative) on the performances of the WWTP. One used model ASM1 of IWQ they introducing a modifications necessary nature sight of the data put to our provision. In this approach, carbonaceous pollution is approached in particular, by a decomposition of the substrate in several fractions according to the various reactions with micro-organisms (fractions quickly or slowly biodegradable, fractions refractory or inert, etc).

Q.X Qe.Xe

Qw.Xr

Qr.Xr


2.2. Model ASM 1 The model used in this the work is based on the Activated Sludge Model No.1 (ASM1) by Henze et al. (1987). This is the most popular mathematical description of the biochemical processes in the reactors for nitrogen and chemical oxygen demand (COD) removal. It was adopted with two modifications: (i) the state variable describing the total alkalinity is not included, and (ii) inert particulate material from influent and from biomass decay are combined into a single variable (XI) since they are of minor interest. The resulting biodegradation model consists of 11 state variables (Table 2) and 20 parameters. The kinetic and stoichiometric parameter values considered are those defined for the simulation benchmark (Alex et al., 1999). The complete set of equations, parameters values, and influent conditions can be found on the European COST action 624 website.

Table 1: Model state variables

1. Inert soluble organic matter, SI (g COD m-3) 2. Readily biodegradable substrate, SS (g COD m-3) 3. Inert particulate organic matter and products, XI (g COD m-3) 4. Slowly biodegradable substrate, XS (g COD m-3) 5. Active heterotrophic biomass, XB,H (g COD m-3) 6. Active autotrophic biomass, XB,A (g COD m-3) 7. Nitrate and nitrite nitrogen, SNO (g N m-3) 8. Ammonium nitrogen, SNH (g N m-3) 9. Soluble biodegradable organic nitrogen, SND (g N m-3) 10. Particulate biodegradable organic nitrogen, XND (g N m-3) 11. Dissolved oxygen, SO (g N O2 m-3)

The model assumptions are as follows: The reactor is well mixed,

• Perfect separation of liquid and solid phases in the settler, • The sum of all settler flowrates equals the settler influent flowrate

The model of the system involves 11 state variables (SI. SS. XI. XS. XB, H. XB, A. SNO. SNH. SND. XND. SO)T with the associated initial conditions given in Table 3. The model differential equations can be stated as

(1) where f are right hand sides of the differential equations given by:

• For soluble components


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(2)

• For Particulate components

(3)

• For dissolved oxygen concentration

(4) where ri(x); i = 1;……; 11 represents the apparent reaction rate depending on the kinetic rates of degradation of the components, kLa is the oxygen transfer coefficient, and max

oS is the dissolved oxygen saturation concentration The input ub is a binary sequence switching between 1 and 0 and represents the state of turbines (on/off) that aerate the plant. Without loss of generality, it is assumed that at time t = 0 the turbines are on. 2.3. Control Variables There are several possible variables that can serve for control: recycle flow rate, sludge extraction flow rate, electrical power of turbines in aerobic mode, etc. Sometimes also influent flow rate can be used - mainly during rainstorm conditions if the sewage system volume can be used to accommodate some extra wastewater. The real manipulated variable that influences the operation of wastewater treatment plants (WWTP) is the sequence of switching times, i.e. times when the turbines switch on/off. Unfortunately, this control variable does not occur explicitly in the model equations. However, it is possible to normalise the model with respect to time in order to obtain an alternative description where the true manipulated variables occur in the system equations. Let us assume that there are Nc cycles within one day consisting of a period of aeration. Followed by a period of non-aeration and let us denote the lengths of the finite time elements by �t1; …… ; �t2Nc. The final time of the simulation/optimisation T is given as:

(5)


The aim of the normalisation is to change the time intervals �t1, �t1 + �t2… ; T into evenly spaced fixed time intervals � = 1=2/Nc; 2=2/2Nc; …… ; 1. This results in the modified system equations

(6) Where u (�) is a piece-wise constant sequence of the length 2Nc containing the switching times �t1; ….. ; �t2Nc.

Figure 2: Principle of the fractionation pollution and simulation dynamics (Model ASM1)

2.4. Performance index There are several possible choices of the performance index. One of the simplest ways is to minimise the overall nitrogen concentration during the day as:

(7) With such a choice, the nitrogen constraint is automatically satisfied, whenever the plant design and operating conditions make it possible. In this study, economic cost has been chosen as the most realistic. About 3=4 of the total cost is related to energy consumption of the aeration turbines (Vasel, 1988). As


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these operate in on/off mode, minimising the time of aeration will decrease the operating costs. Therefore, the dimensionless cost function is defined as

(8) 2.5. GPS-X GPS-X is a software program specifically designed for the modeling and simulation of municipal and industrial wastewater treatment plants. Whether you are designing a new facility, or simulating an existing plant, GPS-X will help improve your design quality and operating efficiency. GPS-X has an easy-to-use interface connected to an extensive library of simulation models. This greatly reduces the effort of carrying out simulation studies, making it a valuable engineering tool. With GPS-X you can improve capacity, operating efficiency and effluent quality by properly optimizing your existing facilities. This can result in capital savings and lower operating costs. Getting started is easy. Open one of our preconfigured layouts that come with GPS-X, or build a model of a plant by dragging-and-dropping unit processes onto the drawing board. GPS-X is a sophisticated simulator with on-screen sliders, switches, and controls that mimic the operation of any plant. The calibration tools help you fine-tune any plant model to accurately depict actual plant performance. 3. MATERIALS AND METHODS 3.1. Presentation of “WWTP Souk-Ahras” The purification plant of the town of Souk Ahras is intended to treat domestic waste water before their rejection with the Medjerda Oued, the first phase makes it possible to treat pollution resulting from a population of 150.000 EH and the second phase will carry its capacity to 225.000 EH.


Photo 1: Air photograph of the WWTP of Souk-Ahras 3.2. Data input To model the operation of a purification plant, it is imperative to have precise and specific data: physical description (die, volume of the works, flows of the pumps…), management (controls and automations, food, ventilation, extractions of mud…), quantity and water quality to be treated. On this last point, the models often require data which are not directly accessible and for which there does not exist simple and standardized protocol of measurement. For example, the total concentration in DCO of the effluents is not sufficient, it must be broken up into 4 or 5 fractions according to their behavior in the station (quickly and slowly biodegradable, soluble and particulate inert, biomasses).

Figure 3: Configuration of the WWTP


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3.3. Stages of chock and validation of the model Any modeling requires phases of parameter setting and checking of the model. The phase of chock aims at optimizing manually or automatically the adjustment of certain variables simulated with their measured values. The stage of validation, as for it, aims to check the quality of the model fixed on other series of measure not used during the chock. The successive realization of the chock/validation constitutes the stage of development of the model on a given site. Table (2) illustrates the parameters of chock of the model suitable for the WWTP and Table (3) presents a comparison between the median values observed with those simulated.

Table2: Parameters of the chock of the model

Parameter stochiometric Values Parameter

kinetics Values

Heterotrophic yield 0.88 g COD/gCOD Maximum specific growth rate HET 1.7 1/d

Heterotrophic endogenous fraction 0.15 gCOD /gCOD Readily biodegradable substrate

half saturation 5 gCOD/m3

Autotrophic yield 0.15 gCOD /gN Aerobic O2 half saturation 0.2 gO2/m3

Autotrophic endogenous fraction 0.08 Anoxic O2 half saturation 0.2 gO2/m3

Anoxic growth factor 1

Nitrate half saturation coefficient 1 gN/m3

Heterotrophic decay rate 0.62 1/d

Autotrophic maximum specific growth rate 0.75 1/d

Autotrophic decay rate 0.04 1/d

Maximum specific hydrolyse rate 0.5 1/d

Anoxic hydrolysis factor 0.37

Ammonification rate 0.016 m3/gCOD/d

Temperature coefficient for HET “Kh” 1.072

Temperature coefficient for HET “Ka” 1.029


Table 3: Checking of the adequacy: reality-simulation

Simulation GPS-X Assessment WWTP (2009)

Parameters Computed values Observed Values

DCO at exit (mg/l) 40 46

DBO5 at exit (mg/l) 6 10

MES at exit (mg/l) 38 42

[8] FNDAE.·(2002).·Ministère·de·l'Agriculture·de·la·Pêche·et·de·l'Alimentation·

Figure 4: DBO5 and its fractions at exit of clarifier Figure 5: DCO at exit of the clarifier 3.4. Optimization of the operation of the STEP 3.4.1. Reduction of sludge Various scenarios of simulation by the GPS-X, will be discussed in the following parts in order to envisage systematic approaches related to the various conditions. In a first scenario one studied the influence of the increase in flow of extraction (Qw) in the mass balance starting from the flow of reference of the model. Figures 6 and 7 illustrate an appreciable reduction of 37% of the production of sludge when one increases the flow of extraction of 710 m3/day with 900 m3/day, with an increase in oxygen dissolves 2 mg/l with 6 mg/l.


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y = 3E-06x4 - 0,011x3 + 14,82x2 - 8586x + 2E+06R² = 0,999

0

2000

4000

6000

8000

600 700 800 900 1000

Boue

prod

uite

, kg

Débit d'extraction, m3/ j

Figure 6: Reduction of sludge according to the flow of extraction

Figure 7: Reduction of sludge according to oxygen dissolves and the flow of extraction 3.4.2. Influence hydraulic residence time (HRT) This graph emphasizes two information. The values of the conversion rate of ammonium (TCA) decrease slightly, from 100 to 95%, when the HRT is decreased by 12.5 with 6:00 the rate accumulation of nitrites grows between 0.1 - 20%. These results indicate that for high values of the hydraulic residence time, the accumulation of nitrites is practically negligible. This can be justified by the fact that, longer the nutritive medium remains in the engine, more the compounds nitrites are converted into nitrates by the nitrating micro-organisms.


Figure 8: Histogram of the rate of conversion of the ammonium (TCA) and the accumulated nitrites, according to the hydraulic residence time (HRT)

4. CONCLUSIONS AND PROSPECTS The Algerian regulation in terms of rejection in the WWTP became increasing severe, following a complexity of the problems relative to dysfonctionnement biological and the diversity of the choices technical options which can be used, whose results are very encouraging. With the growth of waste water in the next years, a pragmatic WWTP is necessary must be based on the technical data collected within the framework of a prior study, of which an improvement of the operation systems purification will pass by use of measurement uninterrupted in control, automation and the supervision of the stations. In addition, a special attention will be paid to becoming rejections of time of rain. If necessary, part of additional volume of waste water will have to be treated in the stations purification.

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optimal operation of alternating activated sludge … · · 2010-05-19optimal operation of...

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