A process synthesis tool for WWTP – An application to design sustainable energy recovery facilities

Behera, Chitta Ranjan; Al, Resul; Gernaey, Krist V.; Sin, Gürkan

doi:10.1016/j.cherd.2020.02.014

Cited by 11 publications

(4 citation statements)

References 63 publications

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“…Finally, the existence of different DSS-optimisation methods allowing to avoid exhaustive manual analyses of different combinations of technologies and propose an optimal solution according to certain optimisation criteria should be mentioned; see, e.g., [18,[27][28][29][30][31][32]. The tool presented here is not focused on this feature; however, its simulation-based nature and its design will allow the implementation of such optimisation techniques in future stages, providing an automated optimal outcome for the design process.…”

Section: Discussionmentioning

confidence: 99%

Implementation of a Decision Support System for Sewage Sludge Management

2020

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In this work, a decision support system (DSS) coupled with wastewater treatment plant (WWTP) simulator tool that uses a hierarchical set of key performance indicators (KPIs) to provide an assessment of the performance of WWTP systems is presented. An assessment of different Scenarios in a real WWTP case study, each consisting of a different set of sludge line technologies and derived combinations, was successfully conducted with the developed DSS–WWTP simulator, based on Scenario simulation and hierarchical KPI analysis. The test carried out on the selected WWTP showed that although thermal valorisation and thermal hydrolysis showed similar (the best) economic viability, the latter showed additional benefits, including synergies related to improving the thermal balance of the overall WWTP even when considering other technologies. On the other hand, biogas-upgrading technologies allowed reduction of emissions, but with higher costs and thermal demands. The usage of this tool may allow the development of proposals for technological priorities as a pathway to the transition to circular economy based on the management criteria of the correspondent sanitation system.

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Section: Discussionmentioning

confidence: 99%

Implementation of a Decision Support System for Sewage Sludge Management

2020

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“…The integrated fixedfilm activated sludge (IFAS) system is a carrier-based mainstream Anammox process, where the aerobic tank is filled with carriers (i.e., Kaldnes K1 type) in order to enhance the nitrogen loading rate. A multi-scale modeling approach is adopted to model the IFAS system, more details of which can be found in (Behera et al, 2020). The anaerobic digestion process is modeled with the ADM1 model (Batstone et al, 2002).…”

Section: Generation Of Alternative Plant Layouts With Superstructuresmentioning

confidence: 99%

“…Following the simulation procedure for the BSM2 plant, as described in (Gernaey et al, 2014), these operational costs are calculated separately for each specific sub-unit and a plant-wide sum averaged per day is returned. Under these settings, an optimum design with minimum OCI will be sought after under varying influent characteristics, which are represented with four key influent fractionation variables, as shown in Table 5, of the BSM2 influent, similar to other studies (Behera et al, 2020;Sin et al, 2009). In order to quantify and model the uncertainty in optimization objectives and constraints, the previously described Monte Carlo-based uncertainty analysis has been performed for each of the initialization samples of the optimization.…”

Section: Problem Formulation For Optimization Under Uncertaintymentioning

confidence: 99%

Stochastic simulation-based superstructure optimization framework for process synthesis and design under uncertainty

Behera

Gernaey

et al. 2020

Computers & Chemical Engineering

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“…Many stakeholders have been exploring solutions to reduce the energy consumption of WWTPs, such as equipment renewal and maintenance, energy recovery, and technical process improvements . Previous studies have mostly focused on technical processes.…”

Section: Introductionmentioning

confidence: 99%

Novel Machine Learning-Based Energy Consumption Model of Wastewater Treatment Plants

2021

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Wastewater treatment plants (WWTPs) can account for up to 1% of a country’s energy consumption. Meanwhile, WWTPs have high energy-saving potential. To achieve this, it is necessary to establish appropriate energy consumption models for WWTPs. Several recent models have been developed using logarithmic, exponential, or linear functions. However, the behavior of WWTPs is non-linear and difficult to fit with simple functions, particularly for non-numerical variables. Thus, traditional modeling methods cannot effectively describe the relationship between water and energy in WWTPs. Therefore, a machine learning method was adopted in this study to investigate the energy consumption in WWTPs; a novel energy consumption model with a non-numerical variable (discharge standard) for WWTPs was developed using the random forest algorithm. The model can also predict the energy consumption of WWTPs after upgrading discharge standards. We found that the unit electricity consumption of WWTPs exhibited an average increase of 17% after the effluent discharge standard was increased from class I B to class I A (as per China’s classification). The correlation coefficient of the model was 0.702. Thus, the developed model can provide a better understanding of energy efficiency in WWTPs.

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A process synthesis tool for WWTP – An application to design sustainable energy recovery facilities

Cited by 11 publications

References 63 publications

Implementation of a Decision Support System for Sewage Sludge Management

Implementation of a Decision Support System for Sewage Sludge Management

Stochastic simulation-based superstructure optimization framework for process synthesis and design under uncertainty

Novel Machine Learning-Based Energy Consumption Model of Wastewater Treatment Plants

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