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UCL School of Energy and Resources

Research in the School of Energy and Resources focuses on both the upstream and downstream development of energy and resources, covering a wide range of disciplines - from engineering and economics to environmental science and law. 

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The Mullard Space Science Laboratory (MSSL) is a world-leading research organisation delivering a broad science programme that is underpinned by a strong capability in space science instrumentation, space-domain engineering, space medicine, systems engineering and project management.

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International Energy Policy Institute

The International Energy Policy Institute (IEPI) was created to address key policy issues in the mineral, energy and resources industries through intensive and innovative research.

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Professor Stefaan Simons

Professor Stefaan Simons

RESEARCH

International Energy Policy Institute

INTERNATIONAL ENERGY POLICY INSTITUTE

The International Energy Policy Institute (IEPI) was created to address key policy issues in the mineral, energy and resources industries through intensive and innovative research.

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Mullard Space Science Laboratory

MULLARD SPACE SCIENCE LABORATORY

The Mullard Space Science Laboratory (MSSL) is a world-leading research organisation delivering a broad science programme that is underpinned by a strong capability in space science instrumentation, space-domain engineering, space medicine, systems engineering and project management.

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UCL Australia PhD presents at MODSIM 2013

6 December 2013

6 December, 2013

“We never know the worth of water till the well is dry.” -   Thomas Fuller

Mariya Koleva, a PhD student at University College London, Australia, presented at the 20th International Congress on Modelling and Simulation (MODSIM2013) in Adelaide on December 6, 2013 on

A Mixed Integer Linear Programming (MILP) model for cost-effective water treatment synthesis

With the outlook of the world population surpassing 9 billion by 2050, households, agriculture and industry expansion will inevitably lead to higher water demands and needs. Consequently, a rising concern, before ‘the well is dry’, addresses the ability to provide sustainable water for the generations yet to come. Reliable access to clean water can be ensured not only by smartly applied integrated water management but also by effective water purification systems. On the other hand, water treatment exerts significant influence on the water production cost. Therefore, designing processes in an adequate and optimal way will allow the resource affordability for the future. 

Deterministic modelling in process synthesis is an excellent approach for tackling the aforementioned challenges. Taken further, various water sources are considered for treatment by the most common separation technologies to produce a final product for different end users. The work below presents the methodology for optimisation of the process operating conditions in order to minimise the number of water purification steps and the annualised variable costs of the selected path.

Abstract

Water is a precious and scarce resource, essential for sustaining nature, human life and industry. Efficient water treatment is recognised as the only method to sustain safe supplies of water in the future. So far, scientific work has focused solely on the performance optimization of individual water purification units due to overall process complexity. A whole-systems approach in the area will be of a significant benefit to industry by increasing overall process efficiency and decreasing plant costs. 

This work addresses the current gap by considering synthesis of water treatment trains using Mixed Integer Linear Programming (MILP). The model accounts for the most common contaminants found in water, secondary treated wastewater, seawater or brackish water. Such major pollution indicators are chemical oxygen demand (COD), biochemical oxygen demand (BOD), total dissolved solids (TDS), total suspended solids (TSS), turbidity and coliforms. The water source is treated to meet potable, process or reclaimed water standards. The set of candidate steps is selected to reflect the most extensively utilised industrial processes such as coagulation-flocculation, membrane filtration and UV disinfection at various operating conditions. The overall number of trains is minimised based on efficiency removal factors and final water purity specifications. The former takes into account the physicochemical properties of the contaminants and the respective regression models for rejection or retention of an addressed impurity in a certain candidate.

A particular case of desalination for drinking water supply is studied. The model is tested for the standard level of contaminants in seawater, TDS and TSS, to be removed by a set of up to 34 candidate trains. For production of ca. 600 m3/h water the model identifies an optimum solution of overall 6 trains consisting of ultrafiltration (UF), nanofiltration(NF) and reverse osmosis (RO). The objective function minimised is the annual operating cost as a function of pumps electricity consumption, membrane cleaning and replacement practices. 

Overall, the results obtained agree with the recent trends in industrial desalination process synthesis and hence, the model can provide a valuable guidance in water purification processes design.

About the speaker

Mariya Koleva is a PhD student at University College London, Australia, specialising in optimal synthesis of water purification processes. View Mariya Koleva’s profile.

About the conference

The 20th International Congress on Modelling and Simulation (MODSIM 2013), hosted by the Modelling and Simulation Society of Australia and New Zealand Inc (MSSANZ), was held in Adelaide, South Australia, December 1-6, 2013. The theme for this year’s congress was ‘Adapting to Change: the multiple roles of modelling’.