Supporting Operational Decisions on Desalination Plants from Process Modelling and Simulation to Monitoring and Automated Control with Machine Learning

Dargam, F. and Perz, E. and Bergmann, S. and Rodionova, E. and Sousa, P. and Andrade de Souza, F.A. and Matias, T. and Ortiz, J.M. and Esteve-Núñez, A. and Ródenas, P. and Zamora, P. (2020) Supporting Operational Decisions on Desalination Plants from Process Modelling and Simulation to Monitoring and Automated Control with Machine Learning. In: Decision Support Systems X - Cognitive Decision Support System and Technologies”. Lecture Notes in Business Information Processing (LNBIP_DSS) (384). Springer International Publishing, Switzerland. ISBN 978-3-030-46223-9

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Abstract

This paper summarizes some of the work carried out within the Horizon 2020 project MIDES (MIcrobial DESalination for low energy drinking water)1, which is developing the world’s largest demonstration of a low-energy system to pro-duce safe drinking water. The work in focus concerns the support for operational decisions on desalination plants, specifically applied to a microbial-powered ap-proach for water treatment and desalination, starting from the stages of process modelling, process simulation, optimization and lab-validation, through the stages of plant monitoring and automated control. The work is based on the ap-plication of the environment IPSEpro for the stage of process modelling and sim-ulation; and on the system DataBridge for automated control, which employs techniques of Machine Learning.

Item Type: Book Section
Additional Information: ICDSST 2020: 6th EWG-DSS International Conference on Decision Support System Technology
Special Focus:  “Cognitive Decision Support Systems & Technologies”
May 27th-29th, 2020 - organized by the EWG-DSS and the University of Zaragoza in Spain.  
https://icdsst2020.wordpress.com/

Uncontrolled Keywords: Operational Decision Support; Desalination Plants; Process Model-ling; Process Simulation; IPSEpro; Plant Monitoring; Automated Control; Ma-chine Learning, Horizon2020 Project, MIDES, Microbial Desalination Cell, MDC, Low-energy Process, Treated Wastewater, Drinking Water, Climate Change Adaptation, Sustainability.
Subjects: Q Science > QA Mathematics > QA76 Computer software
T Technology > TA Engineering (General). Civil engineering (General)
Depositing User: Belén Barroeta
Date Deposited: 27 May 2020 09:49
Last Modified: 27 May 2020 09:49
URI: http://eprints.imdea-agua.org:13000/id/eprint/1168

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