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Wind energy as a clean and inexhaustible source of renewable energy can be a key element of sustainable development that decreases dependence of countries on fossil fuels. Therefore, implementing accurate and comprehensive feasibility studies in countries with a high level of consumption of traditional energy resources is vital; an approach encouraged and supported by green funds and climate change action. It is also crucial to helping spur economic and sustainable growth of these countries. In this regard, this study aims at accurate evaluation of onshore wind energy potential in seven coastal cities in the south of Iran. Six Probability Distribution Functions (PDFs) were examined over representative stations. It was deduced that the Weibull function, which is the most used PDF in similar studies, was only applicable to one station. Here, Gamma distribution offered the best fit for three stations and for the other ones, Generalized Extreme Value (GEV) performed better. Considering the ranking of six examined PDFs and the simplicity of Gamma, it was identified as the effective function in the southern coasts of Iran bearing in mind the geographic distribution of stations. Moreover, six wind energy converter power curve functions contributed to investigating the capacity factor. It is found that, using only one function could cause under- or over-estimation. Then, stations were classified based on the National Renewable Energy Laboratory system. Last but not least, examining a range of wind energy converters enabled scholars to extend this study into practice and prioritize the development of stations considering budget limits.

sustainability

Exploring Wind Energy Potential as a Driver of Sustainable Development in the Southern Coasts of Iran: The Importance of Wind Speed Statistical Distribution Model