Energy optimization of a wastewater treatment plant based on energy audit data: small investment with high return.

Activated sludge model Calibration Data scarcity Energy audit Energy efficiency Energy optimization Process optimization Wastewater treatment plant

Journal

Environmental science and pollution research international
ISSN: 1614-7499
Titre abrégé: Environ Sci Pollut Res Int
Pays: Germany
ID NLM: 9441769

Informations de publication

Date de publication:
May 2020
Historique:
received: 04 12 2019
accepted: 28 02 2020
pubmed: 15 3 2020
medline: 11 7 2020
entrez: 15 3 2020
Statut: ppublish

Résumé

Ambitious energy targets in the 2020 European climate and energy package have encouraged many stakeholders to explore and implement measures improving the energy efficiency of water and wastewater treatment facilities. Model-based process optimization can improve the energy efficiency of wastewater treatment plants (WWTP) with modest investment and a short payback period. However, such methods are not widely practiced due to the labor-intensive workload required for monitoring and data collection processes. This study offers a multi-step simulation-based methodology to evaluate and optimize the energy consumption of the largest Italian WWTP using limited, preliminary energy audit data. An integrated modeling platform linking wastewater treatment processes, energy demand, and production sub-models is developed. The model is calibrated using a stepwise procedure based on available data. Further, a scenario-based optimization approach is proposed to obtain the non-dominated and optimized performance of the WWTP. The results confirmed that up to 5000 MWh annual energy saving in addition to improved effluent quality could be achieved in the studied case through operational changes only.

Identifiants

pubmed: 32170609
doi: 10.1007/s11356-020-08277-3
pii: 10.1007/s11356-020-08277-3
doi:

Substances chimiques

Sewage 0
Waste Water 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

17972-17985

Auteurs

Sina Borzooei (S)

Department of Civil and Environmental Engineering, Politecnico di Torino, Corso Duca degli Abruzzi, 10129, Torino, Italy. sina.borzooei@polito.it.

Youri Amerlinck (Y)

Department of Data Analysis and Mathematical Modelling, BIOMATH, Faculty of Bioscience Engineering, Ghent University, Coupure Links 653, 9000, Ghent, Belgium.

Deborah Panepinto (D)

Department of Civil and Environmental Engineering, Politecnico di Torino, Corso Duca degli Abruzzi, 10129, Torino, Italy.

Soroush Abolfathi (S)

Warwick Water Research Group, School of Engineering, The University of Warwick, Coventry, CV4 7AL, UK.

Ingmar Nopens (I)

Department of Data Analysis and Mathematical Modelling, BIOMATH, Faculty of Bioscience Engineering, Ghent University, Coupure Links 653, 9000, Ghent, Belgium.

Gerardo Scibilia (G)

SMAT (Società Metropolitana Acque Torino) Research Center, Corso Unità d'Italia 235/3, 10127, Torino, Italy.

Lorenza Meucci (L)

SMAT (Società Metropolitana Acque Torino) Research Center, Corso Unità d'Italia 235/3, 10127, Torino, Italy.

Maria Chiara Zanetti (MC)

Department of Civil and Environmental Engineering, Politecnico di Torino, Corso Duca degli Abruzzi, 10129, Torino, Italy.

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Classifications MeSH