Optimal operation of water distribution networks by predictive control using MINLP

This paper presents an approach for the operational optimisation of potable water distribution networks. The maximisation of the use of low-cost power (e.g. overnight pumping) and the maintenance of a target chlorine concentration at final delivery points were defined as important optimisation objec...

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Bibliographic Details
Published inWater S. A. Vol. 29; no. 4; pp. 393 - 404
Main Authors Biscos, C., Mulholland, M., Le Lann, M-V., Buckley, C.A., Brouckaert, C.J.
Format Journal Article
LanguageEnglish
Published Pretoria Water Research Commission (WRC) 01.10.2003
Water Research Commision
Subjects
Drinking water
Earth sciences
Earth, ocean, space
Exact sciences and technology
Geochemistry
Hydrology. Hydrogeology
Mineralogy
Mixed integer non-linear programming
Model predictive control
Predictive control
Reservoirs
Silicates
Water distribution
Water geochemistry
Water resources
South Africa
Southern Africa
algorithms
models
cost
Africa
reservoirs
water supply
concentration
networks
chlorine
pumping
optimization
water resource management
drinking water
maintenance
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Summary:This paper presents an approach for the operational optimisation of potable water distribution networks. The maximisation of the use of low-cost power (e.g. overnight pumping) and the maintenance of a target chlorine concentration at final delivery points were defined as important optimisation objectives. The first objective is constrained by the maintenance of minimum emergency volumes in all reservoirs, while the second objective would include the minimisation of chlorine dosage and re-dosage requirements. The combination of dynamic elements (e.g. reservoirs) and discrete elements (pumps, valves, routing) makes this a challenging predictive control and constrained optimisation problem, which is being solved by MINLP (Mixed Integer Non-linear Programming). Initial experimental results show the performance of this algorithm and its ability to control the water distribution process.
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ISSN:0378-4738