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Statistical evaluation of using the new generation of wind turbines in South Africa

Ali Mostafaeipour, Mehdi Jahangiri, Ahmad Haghani, Seyyed Jalaladdin Hosseini Dehshiri, Seyyed Shahabaddin Hosseini Dehshiri, Alibek Issakhov, Ahmad Sedaghat, Hamed Saghaei, Esther T. Akinlabi, Sam M. Sichilalu, Shahariar Chowdhury, Kuaanan Techato

2020Energy Reports86 citationsDOIOpen Access PDF

Abstract

In the view of the latest status and the potential of developing wind energy in South Africa, the present study aims to perform technical–economic–environmental​ analysis on a wind turbine system with HOMER software using the 20-years average data of the wind speed obtained from NASA’s database, for providing the electricity to residential buildings. The results showed that the Port Elizabeth station, had the lowest levelized cost of electricity (LCOE) with the value of -0.363 $/kWh when using the EOLO wind turbine, and the Bloemfontein station had the highest LCOE with the value of 1.601 $/kWh when using the Turby wind turbine. The results from the step-wise assessment ratio analysis (SWARA) weighting method demonstrated the wind penetration, total production, and capital cost as the most important sub-indices with the weights of 0.106, 0.095, and 0.091, respectively. Using the additive ratio assessment (ARAS), weighted sum method (WSM), and weighted aggregated sum product assessment (WASPAS) techniques, the cities under study were ranked, and the cities of East London and Bloemfontein were identified as the most suitable and the most unsuitable stations for the use of household-scale wind turbines, respectively.

Topics & Concepts

Wind powerStatistical analysisComputer scienceEnvironmental scienceMarine engineeringEngineeringStatisticsElectrical engineeringMathematicsWind Energy Research and Development
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