(86c) Predictive Modelling of a Conventional Clean Water Treatment Work | AIChE

# (86c) Predictive Modelling of a Conventional Clean Water Treatment Work

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University College London
University College London

Adequate and safe water is important for human health and well-being, economic production, and sustainable development, and failure to ensure the safety of drinking water may expose the community to the risk of waterborne and infectious diseases. The water industry in the United Kingdom is regarded as one of the most heavily regulated industries, and water utilities are faced with increasingly tighter targets for the quality of the water received at customers’ taps. While the principles of drinking water treatment have been established for more than a century, water treatment plants have become increasingly complex due to the introduction of the more stringent regulations. These developments have further increased the need for optimum functionality of the water treatment plants to remain competitive by minimising risks.

Mathematical models are essential to describe, predict and control the complicated interactions between different parts of a clean water treatment process, and thereby facilitate a more accurate prediction of a plant’s operational status and help to identify capacities for improvements and risk minimisation, a concept which is well understood within the process industry but not yet established within the water treatment industry. However, most modelling work within water operations has so far been based on empirical observations or hydraulic modelling, rather than mathematically describable relationships of the process. By accurately modelling the controlled flows of water from source of supply through treatment units such as flocculators, filters, chlorinators, intermediate storage vessels and pumps through to treated-water delivery, simulations can predict the behaviour of continuous and sequence process controls and their effects on water flows, pressures and hold-ups in vessels. This will in turn lead to better water quality, cost reduction and a more sustainable performance of the water treatment plant.

The objective of this work is the development of a novel dynamic mathematical model representing a complete conventional water treatment plant. Established data from the literature for single units have been used to verify the performance of each unit individually, and are then combined to enable the simulation of a complete clean water treatment work. Based on real industrial data from one of the United Kingdom’s largest water treatment companies, we will demonstrate how this model allows the characterisation and quantification of changes in process parameters in one operational unit, and their effects on the overall treatment process, thus allowing plant wide operational optimisation for risk mitigation.