Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/61698
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dc.contributor.authorWebby, R.-
dc.contributor.authorBoland, J.-
dc.contributor.authorMetcalfe, A.-
dc.date.issued2007-
dc.identifier.citationAustralia and New Zealand Industrial and Applied Mathematics (ANZIAM) Journal, 2007; 49:C184-C199-
dc.identifier.issn1446-1811-
dc.identifier.urihttp://hdl.handle.net/2440/61698-
dc.description.abstractDue in part to an increasing population and climatic change, fresh water demand is rapidly outpacing fresh water supply. In Australia desalination plants are already used to obtain fresh water from brackish water and seawater, but they have high energy requirements. Solar collectors could provide power, but solar irradiance is variable and desalination plants work most efficiently with constant power. We model a system of photovoltaic arrays and storage batteries. Daily solar intensity and water demand are stochastic. A stochastic linear program finds the optimal blend of water from available sources---groundwater, desalination and stormwater---to meet daily demand. The optimal use of a given size of solar irradiance collection system is found by stochastic dynamic programming. Long term net benefits are obtained as a function of the system size.-
dc.description.statementofresponsibilityR. B. Webby, J. Boland and A. V. Metcalfe-
dc.description.urihttp://anziamj.austms.org.au/ojs/index.php/ANZIAMJ/article/view/320-
dc.language.isoen-
dc.publisherAustralian Mathematical Society-
dc.rights© Australian Mathematical Society 2007-
dc.source.urihttp://anziamj.austms.org.au/ojs/index.php/ANZIAMJ/article/view/320/181-
dc.titleStochastic programming to evaluate renewable power generation for small-scale desalination-
dc.typeJournal article-
pubs.publication-statusPublished-
dc.identifier.orcidMetcalfe, A. [0000-0002-7680-3577]-
Appears in Collections:Aurora harvest
Environment Institute publications
Mathematical Sciences publications

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