Please use this identifier to cite or link to this item: https://repository.sustech.edu/handle/123456789/1672
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dc.contributor.authorAdam, Mohammed Eissa Abdalla
dc.contributor.authorSupervisor ,- Khamis Arbeesh Saadeldin
dc.date.accessioned2013-09-23T07:09:53Z
dc.date.available2013-09-23T07:09:53Z
dc.date.issued2012-09
dc.identifier.citationAdam, Mohammed Eissa Abdalla. Electrical Energy Demand Forecasting in Nyala city 2012-2025: Mohammed Eissa Abdalla Adam; Khamis Arbeesh Saadeldin . - Khartoum: Sudan University of Science & Technology, College of Engineering, 2012. - 70p. : ill. ; 28cm. - M.S.c.en_US
dc.identifier.urihttp://repository.sustech.edu/handle/123456789/1672
dc.descriptionThesisen_US
dc.description.abstractDemand forecasting is vitally important for the electric industry in the deregulated economy. It has many applications including energy purchasing, generation, load switching, contract evaluation, and infrastructure development. Many mathematical methods have been developed for load forecasting. The aim of this thesis is to introduce the meaning and importance of load forecasting, through an actual study of electrical load growth in Nyala city. According to the real data that were collected they show that the pattern of energy consumption in each household is different based on the variable income level of household occupation and the type of private home. The households in high income level consumed higher electricity than for the households in medium and low income levels. Statistic Package of Social Science (SPSS), Statistical Software Regression analysis, Trend method and Microsoft Excel were used in this thesis for data scheduling and processing, the estimation of equations and for drawing the curves and charts describing the load growth in Nyala city.en_US
dc.language.isoenen_US
dc.publisherSudan University of Science & Technologyen_US
dc.subjectElectricityen_US
dc.subjectNyalaen_US
dc.subject2012en_US
dc.subject2025en_US
dc.titleElectrical Energy Demand Forecasting in Nyala city 2012-2025en_US
dc.typeThesisen_US
Appears in Collections:Masters Dissertations : Engineering

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