Lost in optimisation of water distribution systems? A literature review of system operation
- Authors: Mala-Jetmarova, Helena , Sultanova, Nargiz , Savic, Dragan
- Date: 2017
- Type: Text , Journal article , Review
- Relation: Environmental Modelling and Software Vol. 93, no. (2017), p. 209-254
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- Description: Optimisation of the operation of water distribution systems has been an active research field for almost half a century. It has focused mainly on optimal pump operation to minimise pumping costs and optimal water quality management to ensure that standards at customer nodes are met. This paper provides a systematic review by bringing together over two hundred publications from the past three decades, which are relevant to operational optimisation of water distribution systems, particularly optimal pump operation, valve control and system operation for water quality purposes of both urban drinking and regional multiquality water distribution systems. Uniquely, it also contains substantial and thorough information for over one hundred publications in a tabular form, which lists optimisation models inclusive of objectives, constraints, decision variables, solution methodologies used and other details. Research challenges in terms of simulation models, optimisation model formulation, selection of optimisation method and postprocessing needs have also been identified. © 2017
Comparison of multiple surrogates for 3D CFD model in tidal farm optimisation
- Authors: Moore, William , Mala-Jetmarova, Helena , Gebreslassie, Mulualem , Tabor, Gavin , Belmont, Michael , Savic, Dragan
- Date: 2016
- Type: Text , Conference proceedings
- Relation: 12th International Conference on Hydroinformatics - Smart Water for the Future, HIC 2016; Songdo Convensialncheon, South Korea; 21st-26th August 2016; published in Procedia Engineering Vol. 154, p. 1132-1139
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- Description: Marine currents have been identified as a considerable renewable energy source. Therefore, in recent years, research on optimising tidal stream farm layouts in order to maximise power output has emerged. Traditionally, computational fluid dynamics (CFD) models are used to model power output, but their computational cost is prohibitive within an optimisation algorithm. This paper uses surrogate models in place of CFD simulations to optimise the layout of tidal stream farm layouts. Surrogates are functions which are designed to emulate the behaviour of other models with radically reduced computational expense. Two surrogate models are applied and compared: artificial neural network (ANN) and k-nearest neighbours regression (k-NN). We measure their suitability by four criteria: accuracy, efficiency, robustness and performance within an optimisation algorithm. The results reveal that the ANN surrogate is superior in every criteria to the k-NN surrogate. However, the k-NN surrogate is also able to perform adequate optimisation. Finally, we demonstrate that optimisation relying solely on surrogate models is a viable approach, with dramatically reduced computational expense of optimisation. © 2016 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license.
- Description: Procedia Engineering