Operational Decision-Making on Desalination Plants

Author:

Dargam Fatima C.C.1,Perz Erhard1,Bergmann Stefan1,Rodionova Ekaterina1,Sousa Pedro2,Souza Francisco Alexandre A.2,Matias Tiago2,Ortiz Juan Manuel3ORCID,Esteve-Nuñez Abraham3,Rodenas Pau3,Bonachela Patricia Zamora4

Affiliation:

1. SimTech Simulation Technology, Austria

2. Oncontrol Technologies, Portugal

3. IMDEA Water Institute, Spain

4. Aqualia – FCC Group, Spain

Abstract

This paper describes some of the work carried out within the Horizon 2020 project MIDES (MIcrobial DESalination for low energy drinking water), which is developing the world's largest demonstration of a low-energy sys-tem to produce safe drinking water. The work in focus concerns the support for operational decisions on desalination plants, specifically applied to a mi-crobial-powered approach 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 application of the environment IPSEpro for the stage of process modelling and simulation; and on the system DataBridge for auto-mated control, which employs techniques of Machine Learning.

Publisher

IGI Global

Subject

Modeling and Simulation,General Computer Science

Reference25 articles.

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2. Pretreatment systems in desalination plants to reduce extreme events impact in drinking water production;J.Arevalo;Proceedings of the 1st pan‐European Water and Sanitation Safety Planning and Extreme Weather Events Conference,2017

3. Dargam, F. C. C., & Perz, E. (1998). A Decision Support System for Power Plant Design. European Journal of Operational Research, 109, 310-320.

4. Data Mining and Statistics: What’s the connection?;J. H.Friedman;Computing Science and Statistics.,1998

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