Wind Energy Resource Estimation of the Upper Atmosphere over Southern Africa

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  • 1 Department of Geographical and Environmental Sciences, University of Natal, Durban, South Africa
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Abstract

On the basis of daily ECMWF data over the period 1982–89, the mean seasonal and mean annual wind energy resource fields on the isobaric surfaces 1000, 850, 700, 500, 300, 200, and 100 hPa, within the latitude–longitudinal zone 0°–50°S and 0°–45°E, have been calculated and analyzed. Generally, maximum wind energy is recorded on the 3OO-hPa surface, and the intensities are greater by about 25%–30% in winter than in summer. The greatest continental wind energy resources are experienced over the southern tip of the southern African subcontinent, where it was established that the free atmospheric resources exceed those near the surface by at least an order of magnitude. The two-dimensional Gaussian distribution of the wind vector has been used to provide an indirect estimate of the wind energy resource. Good agreement between this measure and the direct estimate of wind energy was obtained, demonstrating the potential usefulness of the two-dimensional Gaussian distribution in estimating upper-air wind energy resources.

Abstract

On the basis of daily ECMWF data over the period 1982–89, the mean seasonal and mean annual wind energy resource fields on the isobaric surfaces 1000, 850, 700, 500, 300, 200, and 100 hPa, within the latitude–longitudinal zone 0°–50°S and 0°–45°E, have been calculated and analyzed. Generally, maximum wind energy is recorded on the 3OO-hPa surface, and the intensities are greater by about 25%–30% in winter than in summer. The greatest continental wind energy resources are experienced over the southern tip of the southern African subcontinent, where it was established that the free atmospheric resources exceed those near the surface by at least an order of magnitude. The two-dimensional Gaussian distribution of the wind vector has been used to provide an indirect estimate of the wind energy resource. Good agreement between this measure and the direct estimate of wind energy was obtained, demonstrating the potential usefulness of the two-dimensional Gaussian distribution in estimating upper-air wind energy resources.

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