Dynamic simulation and optimization of wastewater treatment plants

Nguyen, Dinh Huan; Latifi, M.A.; Lesage, François; Mulholland, M.

doi:10.1109/pc.2013.6581445

Cited by 4 publications

(4 citation statements)

References 7 publications

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“…Some studies dealing with large-size WWTPs have considered time-varying aeration rates [7,53,59]. Guerrero and coworkers [10,55] used time-varying setpoints for the manipulated variables, to allow identifying different optimal setpoints during weekdays and weekends.…”

Section: Continuous Time-varying Decision Variablesmentioning

confidence: 99%

Optimal design and operation of activated sludge processes: State-of-the-art

Hreiz

Latifi

Roche

2015

Chemical Engineering Journal

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171

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To cite this version:Rainier Hreiz, M A Latifi, Nicolas Roche. Optimal design and operation of activated sludge processes: State-of-the-art. Chemical Engineering Journal, Elsevier, 2015Elsevier, , 281, pp.900 -920. 10.1016Elsevier, /j.cej.2015 The paper deals with the optimal control and design of activated sludge processes. Studies on the topic are critically reviewed. Focus is set on the problem formulation that allows one getting reliable solutions. The selection of appropriate cost functions and constraints is discussed. Aspects related to dealing with model mismatch are presented. a r t i c l e i n f o t r a c tThe activated sludge process (ASP) is the most commonly used process for wastewater treatment. Improving its performance is necessary from economic and environmental point of views. In this context, dynamic optimization is a powerful tool for assisting engineers in determining optimal operations and designs for ASPs.However, the real optimality of the solution strongly depends on the optimization problem statement, for which unfortunately, there is no standard or commonly accepted formulation. In a hopeful attempt to provide a guideline for future works on the topic, this paper reviews the literature devoted to optimal control and design of ASPs. The main issues to be addressed in order to get reliable solutions are discussed, among which: (1) Managing the inevitable mismatch between the model predictions and the real ASP operation. (2) Dealing with the unpredictable variations in the wastewater characteristics. (3) Accounting for the slowest dynamic processes occurring in ASPs. (4) Appropriately selecting the decision variables and the flowsheet structure in order to simplify the problem formulation from a mathematical perspective. (5) Conveniently choosing the cost functions expressions/correlations. (6) Successfully selecting the mathematical constraints in order to guarantee physically relevant operations.

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Section: Continuous Time-varying Decision Variablesmentioning

confidence: 99%

Optimal design and operation of activated sludge processes: State-of-the-art

Hreiz

Latifi

Roche

2015

Chemical Engineering Journal

Self Cite

171

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“…BAHGAT [2000] in SOROUR and BAHGAT [2004] developed an expert system called "activated sludge expert" to help inexperienced operators exploiting their activated sludge wastewater treatment plants. Strategies of control of the WWTPs were presented by ARAUJO et al [2013]; HUANG and GOEL [2015] and NGUYEN et al [2013] based on the optimal economic operation. Founded on the techniques of optimization of activated sludge processes, several recent studies were developed to examine a compromise between processing costs and final quality of uncluttered waters.…”

Section: Introductionmentioning

confidence: 99%

Dynamic simulation for wastewater treatment plants management: Case of Souk-Ahras region, north-eastern Algeria

Dairi

Djebbar

Hammar

et al. 2017

Journal of Water and Land Development

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Treatment performances of two wastewater treatment plants (WWTPs), located in North-Eastern Algeria (Souk-Ahras and Sedrata) were tested using ASM1 model.The model, to be considered as a decision tool for the appropriate management of activated sludge systems, served for the prediction of both WWTP behaviours under different operating conditions. In Sedrata WWTP the first management scenarios is based on an increase of inflow rate, taking into account a new transfer volume from a nearby zone. In a second scenerio, the ultimate flow of 40 000 m 3 ·d -1 is estimated. Regarding Souk-Ahras WWTP, three scenarios were tested. The first tested the impact of an increase of the extraction flow rate and yielded a reduction by 37% of sludge production. The second dealt with the management of the mass budget of substrata and biomass. Finally, the third application was devoted to the estimation of the plant ultimate capacity, estimated to be 60 000 m 3 ·d -1.

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“…The primary objective of steady-state model calibration is to align the simulated values for each variable with the corresponding mean values obtained from plant data collected during measurements. This approach has been commonly employed in numerous studies to characterize the performance of ASSs in large-scale MCWWTPs [34,[55][56][57].…”

Section: Model Calibrationmentioning

confidence: 99%

Steady-State and Dynamic Simulation for Wastewater Treatment Plant Management: Case Study of Maghnia City, North-West Algeria

Tiar,

Bessedik,

Abdelbaki

et al. 2024

Water

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Given the critical importance of addressing effluent quality concerns, the present study was dedicated to developing a dynamic simulation model based on the Activated Sludge Model 1 (ASM1) of a wastewater treatment plant located in Maghnia City, Algeria. The model calibration process involved collecting and analyzing 56 samples from the plant over a period of 18 months (from July 2021 to January 2023). Thirteen physicochemical parameters were analyzed to identify the variations in their water quality over time. Stoichiometric and kinetic parameters were adjusted during the plant calibration process. These modifications resulted in a reasonable alignment with the investigated variables, enabling the accurate prediction of the wastewater treatment plants (WWTPs)’ steady-state behavior regarding the removal measurements of chemical oxygen demand (COD), total suspended solids (TSS), and ammonium (NH4-N). The model was validated using 14-day measurements spanning a 4-month duration, and the results indicated good agreement between the observed and simulated effluent variable of chemical oxygen demand (COD) with a root mean square error (RMSE) of 23%. These findings highlight the utility of the ASM1 Model in comprehending and managing the intricate dynamics of the activated sludge process in wastewater treatment plants.

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Dynamic simulation and optimization of wastewater treatment plants

Cited by 4 publications

References 7 publications

Optimal design and operation of activated sludge processes: State-of-the-art

Optimal design and operation of activated sludge processes: State-of-the-art

Dynamic simulation for wastewater treatment plants management: Case of Souk-Ahras region, north-eastern Algeria

Steady-State and Dynamic Simulation for Wastewater Treatment Plant Management: Case Study of Maghnia City, North-West Algeria

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