A combined simulation-optimisation modelling framework for assessing the energy use of urban water systems
Journal of Environmental Management, ISSN: 0301-4797, Vol: 274, Page: 111166
2020
- 13Citations
- 57Captures
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Article Description
Reliance on new and alternative water supply sources is a desirable option for upgrading existing and ageing urban water system infrastructure that is no longer able to cater for steadily increasing water demand. This transformation will increasingly involve the use of decentralised, more complex and energy intensive urban water systems. Modelling capability that takes a holistic systems approach to optimize the dynamic interactions between water and energy is needed to evaluate the performance of fit-for-purpose water supply systems for the urban sector. This paper presents a simulation-optimisation model to concurrently simulate and optimize an urban water supply system based on minimum energy use when water of alternative quality is supplied to different users on a ‘fit-for-purpose’ basis. The model uses a System Dynamics approach to simulate the energy use of different water supply systems in the form of stocks and flows combined with a Genetic Algorithm (GA) technique to optimize energy use while satisfying all the water demands. The comprehensive model framework is built on a Matlab/Simulink® platform. Life Cycle Energy Assessment (LCEA) is used to generate the embodied energy use variables which are input to the simulation-optimisation model. The model is sufficiently flexible to accommodate water supply systems of variable spatial scales and analyse water and energy use at variable time scales. The application of the modelling framework on the Aurora urban development estate, Australia, shows that the model produces essential information about the water supply and energy use intensity according to specified criteria.
Bibliographic Details
http://www.sciencedirect.com/science/article/pii/S0301479720310914; http://dx.doi.org/10.1016/j.jenvman.2020.111166; http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85089561245&origin=inward; http://www.ncbi.nlm.nih.gov/pubmed/32835871; https://linkinghub.elsevier.com/retrieve/pii/S0301479720310914; https://dx.doi.org/10.1016/j.jenvman.2020.111166
Elsevier BV
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