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dc.contributor.advisor Lesaoana, Maseka
dc.contributor.advisor Ncube, Ozias
dc.contributor.author Nedzingahe, Livhuwani
dc.date.accessioned 2014-09-04T07:37:18Z
dc.date.available 2014-09-04T07:37:18Z
dc.date.issued 2010
dc.identifier.uri http://hdl.handle.net/10386/1150
dc.description Thesis (Mathematics) -- University of Limpopo, 2010 en_US
dc.description.abstract Forecasting electricity consumption is a challenge for most power utilities. In South Africa the anxiety posed by electricity supply disruption is a cause for concern in sustainable energy planning. Accurate forecasting of future electricity consumption has been identified as an essential input to this planning process. Forecasting electricity consumption has been widely researched and several methodologies suggested. However, various methods that have been proposed by a number of researchers are dependent on environment and market factors related to the scope of work under study making portability a challenge. The aim of this study is to investigate models to forecast short term electricity consumption for operational use and medium term electricity consumption for tactical use in the Ferrochrome sector in South Africa. An Autoregressive Moving Average method is suggested as an appropriate tool for operational planning. The Holt-Winter Linear seasonal smoothing method is suggested for tactical planning. Keywords: Forecasting, electricity consumption, operational planning, tactical planning, ARIMA, Holt-Winter Linear seasonal smoothing, Ferrochrome sector en_US
dc.language.iso en en_US
dc.publisher University of Limpopo (Medunsa Campus ) en_US
dc.relation.requires Acrobat 6 en_US
dc.subject Electricity consumption en_US
dc.subject Sustainable energy en_US
dc.title Forecasting models for operational and tactical requirements in electricity consumption: The case of the Ferrochrome Sector in South Africa en_US
dc.type Thesis en_US


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