Optimization of Interplant Water Reuse in Industrial Parks

Considering Water Treatment Systems

Master Thesis (2024)
Author(s)

N.A. Koldewijn (TU Delft - Civil Engineering & Geosciences)

Contributor(s)

H. Spanjers – Mentor (TU Delft - Sanitary Engineering)

L. C. Rietveld – Graduation committee member (TU Delft - Sanitary Engineering)

Gijsbert Korevaar – Graduation committee member (TU Delft - Energy and Industry)

J.A. Garzón Díaz – Graduation committee member (TU Delft - Sanitary Engineering)

Faculty
Civil Engineering & Geosciences
Copyright
© 2024 Niels Koldewijn
More Info
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Publication Year
2024
Language
English
Copyright
© 2024 Niels Koldewijn
Graduation Date
30-01-2024
Awarding Institution
Delft University of Technology
Programme
['Civil Engineering']
Sponsors
Sweco
Faculty
Civil Engineering & Geosciences
Reuse Rights

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Abstract

Reusing water is a crucial part of the solution for addressing the growing concern regarding the risk of water scarcity in industrialized and urbanized areas. This study introduces a tool for the design of water networks, focusing on water reuse in industrial parks. Utilizing a mixed-integer nonlinear programming (MINLP) model developed earlier, this tool is the first in water network design models that operates with open-source software, while considering water treatment systems and multiple constituents. A literature study is conducted to discover shortcomings in water network design models and to find a foundational model to use to develop the tool. The developed tool creates a water network based on the optimization of the costs of water obtained from water sources, the costs of treatment systems, and optionally the piping costs. The treatment systems are used to regenerate the water for reuse in industrial plants and to meet environmental discharge limits. The tool develops local optimal solutions as an output. Additionally, this study is the first to integrate a water treatment systems database into a water network design model. However, this database needs to be expanded before it is usable. This study demonstrates the tool through three case studies.

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