Autonomous intake selection optimisation model for a dual source drinking water treatment plant
| Autor: | Edoardo Bertone, Kelvin O'Halloran, Michael Bartkow, K. Mann |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Engineering
business.industry 0208 environmental biotechnology Environmental engineering 02 engineering and technology 010501 environmental sciences 01 natural sciences 020801 environmental engineering Dual source Water treatment Water quality Raw water business Water resource management Selection (genetic algorithm) Water utility 0105 earth and related environmental sciences Water Science and Technology |
| Zdroj: | Water Supply. 18:279-287 |
| ISSN: | 1607-0798 1606-9749 |
| Popis: | The Mudgeeraba drinking water treatment plant, in Southeast Queensland, Australia, can withdraw raw water from two different reservoirs: the smaller Little Nerang dam (LND) by gravity, and the larger Advancetown Lake, through the use of pumps. Selecting the optimal intake is based on water quality and operators' experience; however, there is potential to optimise this process. In this study, a comprehensive hybrid (data-driven, chemical, and mathematical) intake optimisation model was developed, which firstly predicts the chemicals dosages, and then the total (chemicals and pumping) costs based on the water quality at different depths of the two reservoirs, thus identifying the cheapest option. A second data-driven, probabilistic model then forecasts the volume of the smaller LND 6 weeks ahead in order to minimise the depletion and spill risks. This is important in case the first model identifies this reservoir as the optimal intake solution, but this could lead in the long term to depletion and full reliance on the electricity-dependent Advancetown Lake. Both models were validated and proved to be accurate, and with the potential for substantial monetary savings for the water utility. |
| Databáze: | OpenAIRE |
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