Integrated process design and control via global optimization: A wastewater treatment plant case study

Moles, Carmen G.; Gutierrez, G.; Alonso, Antonio A.; Banga, Julio R.

doi:10.23919/ecc.2001.7076389

Cited by 19 publications

(35 citation statements)

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“…However, some studies [6,28,51] reported that, starting from different sets of initial conditions, their local-deterministic algorithm returned the same solution, whence the possibility that it might correspond to a global optimum. On the other hand, numerous studies adopting a multi-start procedure reported that the achieved results corresponded to a large number of local solutions [8,12,38,39,52,53].…”

Section: Effectiveness Of Various Optimization Techniquesmentioning

confidence: 99%

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

Hreiz

Latifi

Roche

2015

Chemical Engineering Journal

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: Effectiveness Of Various Optimization Techniquesmentioning

confidence: 99%

“…However, as discussed in [8], to guarantee global optimality, most of these methods have a number of requirements (e.g. twice differentiability of the model) that are not met in many realistic dynamic problems.…”

Section: Optimization Algorithmsmentioning

confidence: 99%

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

Hreiz

Latifi

Roche

2015

Chemical Engineering Journal

171

View full text Add to dashboard Cite

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“…The aim is to simultaneously find the static variables of the process design, the operating conditions and the controllers' parameters which optimize a combined measure of the plant economics and its controllability, subject to a set of constraints which ensure appropriate 0-7803-9568-9/05/$20.00 ©2005 IEEE [15], often based on simplified or linearized models. 3. global optimization methods for simultaneously optimizing operation and design [4]. 4.…”

Section: Integrated Design: Problem Statementmentioning

confidence: 99%

“…3. global optimization methods for simultaneously optimizing operation and design [4]. 4. an integrated approach for the optimization of control strategies, where a small selection of global and local optimization methods was used [16].…”

Section: Integrated Design: Problem Statementmentioning

confidence: 99%

“…Thus, several authors [3] have recently proposed the use of so-called surrogate models which are (computationally) cheaper to evaluate. In the area of process systems engineering, Moles et al [4] showed how stochastic global optimization methods can be applied for simultaneous design and control of process plants of low complexity. In this contribution, our aim is to apply a similar approach to more complex (and costly) models.…”

Section: Introductionmentioning

confidence: 99%

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Global Optimization for Integrated Design and Control of Computationally Expensive Process Models

Egea

Vries

Alonso³

et al.

Proceedings of the 44th IEEE Conference on Decision and Control

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Abstract-The problem of integrated design and control optimization of process plants is discussed in this paper. We consider it as a nonlinear programming problem subject to differential-algebraic constraints. This class of problems is frequently (i) non-convex and (ii) "costly" (i.e. computationally expensive to evaluate). Thus, on the one hand, local optimization techniques usually fail to locate the global solution and, on the second hand, most global optimization methods require many simulations of the model, resulting in unaffordable computation times. As an alternative, one may consider global optimization methods which employ surrogate-based approaches to reduce computation times, and which require no knowledge of the problem structure. A challenging Wastewater Treatment Plant benchmark model (see [1] and references therein) is used to evaluate the performance of these techniques. Numerical experiments with different optimization solvers indicate that the proposed benchmark optimization problem is indeed non-convex, and that we can achieve an improvement of the controller performance compared to the best tuned controller settings available in the literature. Moreover, these results show that surrogate-based methods may indeed reduce computation times while, at the same time ensuring convergence to the best known solutions.

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Integrated nonlinear optimization of bioprocesses via linear programming

et al. 2003

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The problem of integrated design and control of bioprocess plants is considered. A pre®iously presented optimization approach for biochemical systems based on linear ( programming and modeling using the power law formalism the Indirect Optimization ) Method, IOM is extended. This method is enhanced in order to take into account both static and dynamic measures, and its use for the optimization of the integrated design of a bioprocess is illustrated. The chosen case study is a wastewater treatment plant, a bioprocess which typically presents controllability problems in real practice due to bad design methodologies. After defining an objecti®e function reflecting both in®estment ( ) costs and '' paracosts'' such as stability, flexibility, and controllability , a set of constraints determined by the system components and technical and economical factors is defined. A comparison of the results obtained with this new method and with a global optimization method re®eals that, in both cases, significant impro®ements in both controllability and cost reduction are achie®ed, although the global method yields somewhat better impro®ements. The ad®antages and limitations of both methods are e®aluated, concluding that the IOM, through its incorporation to a dynamic process simulator, can be successfully used to obtain, in a quick, inexpensi®e and interacti®e way, near-optimal integrated designs for bioprocess plants. IntroductionThe proper design and operation of any microbial-based biotechnological process requires the quantitative description of the variables relevant for the system's kinetics. Once this information is available, it will be possible to derive an optimal process design and to attain its optimal operation. However, the nonlinear nature of these processes has impaired Ž such optimizations Vagners, 1983;Heinrich and Schuster, . 1996 . In order to circumvent these difficulties chemical and biochemical engineers have developed strategies to minimize or even avoid nonlinearities. Focusing on specific properties of chemical networks and by using prudent approximations, different techniques and approaches have been developed within the field of process engineering, which permits the process improvement through the right choice of operating Ž parameters Stephanopoulos, 1998;Stephanopoulos et al., . 1998 . Correspondence concerning this article should be addressed to N. V. Torres.One approach that fully acknowledges the nonlinearities, yet ultimately leads to linear optimization tasks, is based on a modeling framework called Biochemical Systems Theory Ž . Savageau 1969a,b; Voit, 2000 . The hallmark of this theory is the approximation of rate laws and other processes with products of power-law functions. Mathematically, this type of representation is very convenient and solidly grounded in Taylor's theory of approximating functions with polynomials. The Biochemical System Theory framework offers some choices for the formulation of biochemical systems, among which the most relevant for our present purposes is the S-sys-Ž...

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Integrated process design and control via global optimization: A wastewater treatment plant case study

Cited by 19 publications

References 0 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

Global Optimization for Integrated Design and Control of Computationally Expensive Process Models

Integrated nonlinear optimization of bioprocesses via linear programming

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