Smart-Plant Decision Support System (SP-DSS): Defining a multi-criteria decision-making framework for the selection of WWTP configurations with resource recovery

Živko Južnič-Zonta, Albert Guisasola, Juan Antonio Baeza*

*Autor correspondiente de este trabajo

Producción científica: Contribución a una revistaArtículoInvestigaciónrevisión exhaustiva

10 Citas (Scopus)
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Resumen

The development of the Smart-Plant Decision Support System (SP-DSS) is presented, which helps to find the optimal water resource recovery facility (WRRF) configuration for a specific case. A general plant superstructure is defined to allow the evaluation of different combinations among the available process unit options, considering technical, economic, and environmental impact criteria. The complete evaluation is based on a five-step framework: (i) design problem set-up, (ii) wastewater inflow generation, (iii) superstructure generation and plant-wide model simulation under dynamic conditions, (iv) estimation of multi-criteria objective values (greenhouse gas emissions, accumulation of effluent violations, effluent quality index, net present value, system readiness level and plant land area), and (v) design configuration multi-criteria sorting with the technique for order of preference by similarity to ideal solution (TOPSIS). SP-DSS application is shown comparing the mainstream shortcut enhanced phosphorus and polyhydroxyalkanoate (PHA) recovery (SCEPPHAR) technology with a conventional anaerobic/anoxic/aerobic (A2O) configuration for a medium size WWTP (Manresa, Spain). The comparison shows both configurations allow meeting discharge limits, and among other criteria, the SCEPPHAR novel configuration, with respect to A2O, shows higher pollutant contents in the effluent (3.30 vs 2.34 gPoll/m3), higher capital expenditures (CAPEX 0.191 vs 0.130 €/m3), lower operational expenditures (OPEX 0.397 vs 0.515 €/m3), lower required tariff (0.654 vs 0.674 €/m3) and higher greenhouse gas emissions (GHG 0.19 vs 0.14 kgCO2/m3). Overall, TOPSIS sorting indicates A2O is still the best configuration for this specific case.

Idioma originalInglés
Número de artículo132873
PublicaciónJournal of Cleaner Production
Volumen367
DOI
EstadoPublicada - 20 sept 2022

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