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The objective of this research is to limit the risks of fully automated operation of drinking water treatment plants and to improve their operation by using an integrated system of process models and emulated process automation software. This thesis contains the design of such an integrated system. The use of the system is investigated in the three identified applications, i) optimization of process control, ii) training of operation supervisors and iii) virtual commissioning of process automation software.

Eureau is the European Federation of National Associations of Water and Wastewater Services. At the request of Eureau Commission 1, dealing with drinking water, a survey was made focusing on raw drinking water sources and drinking water treatment technologies applied in Europe. Raw water sources concerned groundwater, surface water, surface water with artificial recharge and river bank filtration. Treatment schemes concerned no treatment, conventional treatment, advanced treatment and conventional plus advanced treatment. The response covered 73% of the population to which drinking water is supplied by the utilities joint in Eureau. Groundwater and surface water are the major raw water sources (>90%). In total, 59% of the drinking water supply concerns nottreated drinking water or drinking water treated with only conventional technologies, while 12% of the drinking water is not disinfected. Vulnerabilities of the European drinking water supply are the contamination of raw water sources with emerging substances, the absence of disinfection and the potential formation of disinfection by-products. Based on this, research needs are the development of quantitative structure activity relationships (QSARs) to better understand and predict the removal rates of treatment technologies for emerging contaminants, the introduction of Water Safety Plans to prevent hygienic contamination of drinking water, and the optimization of disinfection processes and strategies.

Hydrodynamic processes largely determine the efficacy of drinking water treatment systems, in particular disinfection systems. A lack of understanding of the hydrodynamics has resulted in suboptimal designs of these systems. The formation of unwanted disinfection-by-products and the energy consumption or use of chemicals is therefore higher than necessary. In drinking water engineering, computational fluid dynamics (CFD) is therefore increasingly applied to predict the performance of treatment installations and to optimise these installations. CFD uses advanced numerical models to predict flow, mixing and (bio)-chemical reactions. In this thesis, the hydrodynamics and (bio)-chemistry in ozone and UV systems are studied by means of CFD models combined with experimental techniques. This combination leads to further development of CFD modelling as a tool to evaluate the performance of drinking water treatment installations. If the CFD model is applied properly, accounting for the complex turbulent motions and validated by experiments, this tool leads to a better design of UV reactors, ozone systems and other systems dictated by hydrodynamics. This work resulted in new insights in the applicability of models in ozone and UV installations, and new insights in design aspects of these installations.

This research deals with the contribution of process simulation models to the factory acceptance test (FAT) of process automation (PA) software of drinking water treatment plants. Two test teams tested the same piece of modified PA-software. One team used an advanced virtual commissioning (AVC) system existing of PA-emulation and integrated process simulation models, the other team used the same PA-emulation but basic parameter relations instead of the process simulation models, the VC-system. Each test team found one (different) error of the thirteen errors put into the software prior to the experiment; the majority of the errors was found prior to the functional test. The team using the AVC-system found three errors, the team using the VC-system found four, but the AVC-team judged 1% of the test items ‘not possible’, the VC-team 17%. It was concluded that the hypothesis that with AVC more errors could be found than with VC could not be accepted. So, for the FAT of PAsoftware of drinking water treatment plants, the addition of basic parameter relations to PA-emulation satisfied. Not the exact process behavior helped to find errors, but the passing of process thresholds.

Drinking water treatment plants automation becomes more sophisticated, more on-line monitoring systems become available and integration of modeling environments with control systems becomes easier. This gives possibilities for model-based optimization. In operation of drinking water treatment plants, the processes are usually optimized individually on the basis of "rules of thumb" and operator knowledge and experience. However, changes in operational conditions of individual processes can affect subsequent processes and an optimal operation, which can include a number of water quality parameters, costs and environmental impact is different for every operator. Improvement of the operation of a drinking water treatment plant is possible by using an integrated model of the entire water treatment plant as an instrument for operational support and for process control. For this purpose, it is important that explicit objectives are defined for the operation. From the research it is concluded that the objective for integrated optimization of the operation of drinking water treatment should be the improvement of water quality and not a priori reduction of environmental impact or costs. In the research an integrated model for ozonation, including ozone decay, bromate formation, assimilable organic carbon (AOC) formation, E. coli disinfection, CT and decrease in UV absorbance at 254 nm (UVA254) is developed. With the model, different control strategies for ozonation are assessed. The research also describes a newly developed design for ozone installations, the dissolved ozone plug flow reactor, (DOPFR) and the effect of character and removal of natural organic matter (NOM) prior to ozonation. The research was carried out as part of the project Promicit, a cooperation of Waternet, Delft University of Technology, DHV B.V. and ABB B.V. and was subsidized by SenterNovem, agency of the Dutch Ministry of Economic Affairs. Part of the experiments was performed in cooperation with Kiwa Water Research.