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Please use this identifier to cite or link to this item: http://hdl.handle.net/11375/16789
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DC FieldValueLanguage
dc.contributor.advisorSmith, A.A.-
dc.contributor.authorAddo, C.K.O.-
dc.date.accessioned2015-03-04T20:46:04Z-
dc.date.available2015-03-04T20:46:04Z-
dc.date.issued1987-12-
dc.identifier.urihttp://hdl.handle.net/11375/16789-
dc.description.abstract<p> The Volta River Authority (VRA) is responsible for the generation and transmission of power in Ghana. For this purpose, VRA owns and operates two hydroelectric generating stations (at Akosombo and Kpong) with a combined installed capacity of 1060 Kw. The Akosombo plant is served by the Lake Volta Reservoir. Prediction of inflows into the Volta Lake is one of the important functions of the reservoir management group.</p> <p>For this project, some of the more recent methods of mathematical modelling are investigated with a view to building a simple stochastic model which adequately represents and forecasts the Volta river average monthly flow. The Box-Jenkins family of models are employed in this exercise. A parsimonious model in the form of a seasonal autoregressive integrated moving average (SARIMA) model is arrived at which adequately models and forecasts the available data.</p> <p>The selected model is reasonably easy to set up, has few parameters to estimate and therefore making the updating of these parameters a relatively simple task.</p>en_US
dc.language.isoen_USen_US
dc.subjectVolta, River, Authority, lake, stochastic model, forecastingen_US
dc.titleVolta River Flows Stochastic Modelling and Forecastingen_US
dc.typeThesisen_US
dc.contributor.departmentNoneen_US
dc.description.degreetypeThesisen_US
dc.description.degreeMaster of Engineering (MEngr)en_US
Appears in Collections:Open Access Dissertations and Theses

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