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

Energy Reports (Nov 2020)

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

Affiliations

Ali Mostafaeipour: Institute of Research and Development, Duy Tan University, Da Nang 550000, Viet Nam; The Faculty of Civil Engineering, Duy Tan University, Da Nang 550000, Viet Nam; Department of Sustainable Energy, Faculty of Environmental Management, Prince of Songkla University, 90110, Songkhla, Thailand
Mehdi Jahangiri: Department of Mechanical Engineering, Shahrekord Branch, Islamic Azad University, Shahrekord, Iran
Ahmad Haghani: Department of Mechanical Engineering, Shahrekord Branch, Islamic Azad University, Shahrekord, Iran
Seyyed Jalaladdin Hosseini Dehshiri: Department of Industrial Management, Faculty of Management and Accounting, Allameh Tabataba’i University, Tehran, Iran
Seyyed Shahabaddin Hosseini Dehshiri: Department of Mechanical Engineering, Sharif University of Technology, Tehran, Iran
Alibek Issakhov: Faculty of Mechanics and Mathematics, Department of Mathematical and Computer Modelling, Al-Farabi Kazakh National University, Almaty, Kazakhstan
Ahmad Sedaghat: School of Engineering, Australian College of Kuwait, Safat 13015, Kuwait
Hamed Saghaei: Department of Electrical Engineering, Shahrekord Branch, Islamic Azad University, Shahrekord, Iran
Esther T. Akinlabi: Department of Mechanical Engineering Science, Faculty of Engineering and the Built Environment, University of Johannesburg, Johannesburg, South Africa
Sam M. Sichilalu: Department of Mechanical Engineering Science, Faculty of Engineering and the Built Environment, University of Johannesburg, Johannesburg, South Africa; Department of Electrical and Electronic Engineering, School of Engineering, University of Zambia, Lusaka, Zambia
Shahariar Chowdhury: Faculty of Environmental Management, Prince of Songkla University, HatYai, Songkhla, 90112, Thailand; Environmental Assessment and Technology for Hazardous Waste Management Research Center, Faculty of Environmental Management, Prince of Songkla University, 90110 Songkhla, Thailand
Kuaanan Techato: Faculty of Environmental Management, Prince of Songkla University, HatYai, Songkhla, 90112, Thailand; Environmental Assessment and Technology for Hazardous Waste Management Research Center, Faculty of Environmental Management, Prince of Songkla University, 90110 Songkhla, Thailand; Corresponding author at: Department of Electrical and Electronic Engineering, School of Engineering, University of Zambia, Lusaka, Zambia.

Journal volume & issue: Vol. 6
pp. 2816 – 2827

Abstract

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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.

Published in Energy Reports

ISSN: 2352-4847 (Online)
Publisher: Elsevier
Country of publisher: United Kingdom
LCC subjects: Technology: Electrical engineering. Electronics. Nuclear engineering
Website: http://www.journals.elsevier.com/energy-reports/

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