Modeling of Meteorological Data for Coastal Regions of Oman

Information of solar radiation at any site is essential for the proper design and assessment of solar energy conversion systems. Empirical modeling is an important and economical tool for the estimation of solar radiation. The aim of this study is to find a suitable model to explain the solar rad...

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Bibliographic Details
Main Author: Mohammed Akaak, Ahmed
Format: Thesis
Language:English
English
Published: 1999
Subjects:
Online Access:http://psasir.upm.edu.my/id/eprint/9459/1/FSAS_1999_17_A.pdf
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Summary:Information of solar radiation at any site is essential for the proper design and assessment of solar energy conversion systems. Empirical modeling is an important and economical tool for the estimation of solar radiation. The aim of this study is to find a suitable model to explain the solar radiation data in Oman. Daily global solar radiation of Oman is modeled using measured climatological data of the four weather stations at different locations over the period of five years. These stations are: Seeb in the North, Surin the East Coast, Masirah, an island off Central Oman and Salalah in the South. The data were obtained from the Directorate General of Civil Aviation and Meteorology in Oman. The daily extraterrestrial solar radiation, H 0' and the maximum daily hours of sunshine, So, are computed. The method used is based on Angstrom formula, which correlates relative global solar radiation to corresponding relative duration of bright sunshine. The daily temperature range (T), the mean humidity (D) and the multiplication of all of them were added to the sunshine duration to give better results. Regression coefficients are obtained and used for prediction of global solar radiation. The results were satisfactory and can be used to predict weather data for stations where such data are not available. Availability of wind energy and its characteristics for four weather stations in Oman has been studied based on primary data collected at these sites for a period of five years. The method used is based on the Weibull parameter distribution. The monthly average wind speed, the monthly mean scale and shape parameters and the monthly mean power density were determined for each station. The results showed that the mean wind speed, the scale and shape parameters and the mean power density have high values during summer season and low values during winter season. The K-S test was applied to the fitted model and showed excellent results for all the stations. As a result wind data used are very well represented by the Weibull distribution function.