海水淡化厂的操作决策:从过程建模和仿真到机器学习的监测和自动控制

IF 0.6 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS

International Journal of Decision Support System Technology Pub Date : 2022-12-05 DOI:10.4018/ijdsst.315639

Fátima C. C. Dargam, E. Perz, S. Bergmann, E. Rodionova, Pedro Sousa, Francisco Alexandre A. Souza, Tiago Matias, J. M. Ortiz, A. Estéve-Núñez, Pau Rodenas, Patricia Zamora Bonachela

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引用次数: 0

摘要

本文描述了地平线2020项目MIDES(低能耗饮用水微生物脱盐)中开展的一些工作，该项目正在开发世界上最大的低能耗系统示范，以生产安全饮用水。重点工作涉及支持海水淡化厂的操作决策，特别是应用于水处理和海水淡化的微微生物动力方法，从过程建模、过程模拟、优化和实验室验证阶段开始，一直到工厂监测和自动控制阶段。该工作基于应用环境IPSEpro进行过程建模和仿真阶段;以及采用机器学习技术的自动化控制系统DataBridge。

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Operational Decision-Making on Desalination Plants: From Process Modelling and Simulation to Monitoring and Automated Control With Machine Learning

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.

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来源期刊

International Journal of Decision Support System Technology COMPUTER SCIENCE, INFORMATION SYSTEMS-

CiteScore

2.20

自引率

18.20%

发文量