Optimal Synthesis and Operation of Wastewater Treatment Process with Dynamic Influent

Abstract

This work addresses the problem of optimal synthesis and operation of wastewater treatment processes considering multiscenario influent streams under different discharge standards and penalty rates of noncompliant emissions. We develop a general disjunctive programming model to address this problem, which is then reformulated as a multiperiod mixed-integer nonlinear programming model using hull reformulation for the disjunctions. To solve the resulting model to global optimality, we propose a Lagrangeanbased decomposition algorithm. Numerical studies verify the effectiveness of the algorithm, and comparison studies provide useful management insights for policy makers.

Systematic Design, Optimization, and Sustainability Assessment for Generation of Efficient Wastewater Treatment Networks

“…Since there are no substitutes for water, there is the need to treat WW for reuse, proper disposal, or recycling. Scientists in the past two decades have explored the systematic design and optimization of wastewater treatment (WWT) plants or networks [1][2][3][4][5][6][7]. However, there is still a lack of a holistic approach for designing efficient WWT networks [8].…”

The SPPD-WRF Framework: A Novel and Holistic Methodology for Strategical Planning and Process Design of Water Resource Factories

“…Due to increasing available treatment technologies, WWTP design has become more and more complex in recent years. The resulting multi-criteria process design problem for an optimal treatment process has successfully been tackled by mathematical problem optimisation in superstructure methods using stoichiometric coefficients and kinetic constants [12][13][14], or by applying computational environmental decision support systems in the process design procedure [15]. Software to choose between alternative treatment process designs on the basis of their techno-economic performance has been developed including also environmental impact assessment criteria [16].…”

Intelligent Control/Operational Strategies in WWTPs through an Integrated Q-Learning Algorithm with ASM2d-Guided Reward

“…By the end of 2013, 3508 WWTPs had been built in 31 provinces in China; however, almost 90% of them have inescapable problems with nutrient removal, and roughly 50% of WWTPs could not meet the nitrogen discharge standard [6]. Since the quality of the discharged effluent is one of the most serious environmental problems today, the ever increasingly stringent standards and regulations for the operation of WWTPs have been imposed by authorities and legislation [7,8]. Therefore, the implementation of effluent standards requires refined and sophisticated control strategies able to deal with this nonlinear and multivariable system with complex dynamics [9,10].…”

“…The conventional control parameters optimization for the wastewater treatment process has traditionally relied on the common expert knowledge and previous experience, which require specific technical know-how and often involve laboratory and pilot trials [7]. However, these approaches resulted in reduced responsiveness in taking corrective action and a high possibility of missing major events negatively impacting water quality and process management [17].…”

“…In addition, the commonly used proportional-integral and proportional-integral-derivative controllers in the context of control in WWTPs cannot predict the problematic situations nor lead back the control process toward optimal conditions [20,[22][23][24]. Therefore, given the strengthening of stringent discharge standards and highly dynamic influent loadings with variable concentration of pollutants, it is very challenging to design, and then effectively implement, real-time optimal control strategies for the existing wastewater treatment processes [7].…”