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dc.contributor.authorMubiru, J.
dc.contributor.authorBanda, E.J.K.B.
dc.date.accessioned2022-01-07T16:39:19Z
dc.date.available2022-01-07T16:39:19Z
dc.date.issued2012
dc.identifier.citationJ. Mubiru, E.J.K.B. Banda, Monthly average daily global solar irradiation maps for Uganda: A location in the equatorial region, Renewable Energy,https://doi.org/10.1016/j.renene.2011.11.018.en_US
dc.identifier.urihttps://nru.uncst.go.ug/xmlui/handle/123456789/1150
dc.description.abstractProper sizing of solar energy systems is necessary in order to optimize their output. This requires a database of solar irradiation for locations for which the systems are being assessed. Solar irradiation data is also required in modeling a building’s thermal performance, as input into ecological and crop models and evaluation of long-term effects of climatological changes. Solar irradiation data can be provided through measurements. In Uganda, measurements of global solar irradiation have been carried out for a few locations because the measuring instruments are expensive to purchase and install. An alternative to obtaining solar irradiation data is to estimate it either by use of an appropriate solar irradiation model or interpolation of the few existing records. The present study attempted to draw global solar irradiation maps for Uganda. Global solar irradiation values were estimated for eight out of twelve stations using an artificial neural networks model proposed for Uganda. Measured values of monthly average daily global solar irradiation were used for the remaining four stations. The values for the twelve stations were then utilized for the interpolation using moving average method. The result is a set of twelve global solar irradiation maps for Uganda with relative errors in the range of 8%–16%.en_US
dc.language.isoenen_US
dc.publisherRenewable Energyen_US
dc.subjectMap;Model;Solar irradiation;Interpolationen_US
dc.titleMonthly Average Daily Global Solar Irradiation Maps For Uganda: A Location In The Equatorial Regionen_US
dc.typeArticleen_US


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