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Application of unsupervised learning and process simulation for energy optimization of a WWTP under various weather conditions

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Sina Borzooei, Sina, Miranda, Gisele H. B., Abolfathi, Soroush, Scibilia, Gerardo, Meucci, Lorenza and Zanetti, Maria Chiara (2020) Application of unsupervised learning and process simulation for energy optimization of a WWTP under various weather conditions. Water Science & Technology . wst2020220. doi:10.2166/wst.2020.220

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Official URL: https://doi.org/10.2166/wst.2020.220

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Abstract

This paper outlines a hybrid modeling approach to facilitate weather-based operation and energy optimization for the largest Italian wastewater treatment plant (WWTP). Two clustering methods, K-means algorithm and Gaussian mixture model (GMM) based on the expectation-maximization (EM) algorithm, were applied to an extensive data set of historical and meteorological records. This study addresses the problem of determining the intrinsic structure of clustered data when no information other than the observed values is available. Two quantitative indexes, namely the Bayesian Information Criterion (BIC) and the Silhouette coefficient using Euclidean distance, as well as two
general criteria, were implemented to assess the clustering quality. Furthermore, seven weather based influent scenarios were introduced to the process simulation model, and sets of aeration strategies are proposed. The results indicate that incorporating weather-based aeration strategies in the operation of WWTP improves plant energy efficiency.

Item Type: Journal Article
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
T Technology > TC Hydraulic engineering. Ocean engineering
T Technology > TD Environmental technology. Sanitary engineering
Divisions: Faculty of Science > Engineering
Library of Congress Subject Headings (LCSH): Sewage -- Purification -- Mathematical models, Sewage -- Purification -- Simulation methods, Sewage disposal plants, Sewage -- Purification -- Nutrient removal, Water treatment plants -- Simulation methods, Water -- Purification -- Simulation methods, Water-supply engineering -- Technological innovations, Sewage disposal -- Technological innovations
Journal or Publication Title: Water Science & Technology
Publisher: IWA Publishing
ISSN: 0273-1223
Official Date: 2020
Dates:
DateEvent
2020Published
9 May 2020Available
27 April 2020Accepted
Article Number: wst2020220
DOI: 10.2166/wst.2020.220
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Open Access
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