Coastal South African cities like Port Elizabeth are said to have a strong potential for wind energy. This study aims to model wind data in order to be able assess the power potential belonging to a given site. The main challenge in modelling wind direction data is that it is categorized as circular data and therefore requires special techniques for handling that are different from usual statistical samples. Statistical tools such as descriptive measures and distribution fitting, were re-invented for directional data by researchers in this field. The von Mises distribution is a predominant distribution in circular statistics and is commonly used to describe wind directions. In this study, the circular principles described by previous researchers were developed by using the statistical software, Mathematica. Graphical methods to present the wind data were developed to give an overview of the behaviour of the winds in any given area. Data collected at Coega, an area near Port Elizabeth, South Africa, was used to illustrate the models which were established in this study. Circular distributions were fit to the directional data in order to make appropriate conclusions about the prevailing wind directions in this area.
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:nmmu/vital:10579 |
| Date | January 2012 |
| Creators | Moodley, Kirshnee |
| Publisher | Nelson Mandela Metropolitan University, Faculty of Science |
| Source Sets | South African National ETD Portal |
| Language | English |
| Detected Language | English |
| Type | Thesis, Masters, MSc |
| Format | vii, 74 leaves, pdf |
| Rights | Nelson Mandela Metropolitan University |
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