This study presents a comprehensive review that systematically examines the technical, aerodynamic, mechanical, and economic criteria used in the selection of small and medium-scale wind turbines. Turbine performance is evaluated within the framework of the rotor diameter–swept area relationship, tip speed ratio (TSR)–power coefficient (Cp) aerodynamic curves, Weibull wind speed distribution, and power curve parameterization. The fundamental mathematical models employed in annual energy production (AEP) calculations are explained, and the decisive influence of the compatibility between the wind regime and turbine characteristics on overall performance is emphasized. Mechanical components (noise, vibration, generator type) and economic indicators (levelized cost of energy—LCOE, operation and maintenance costs, payback periods) are comparatively assessed with respect to turbine selection. In addition, the performance of multi-criteria decision-making methods (AHP, TOPSIS, VIKOR, CoCoSo) and artificial intelligence-based models (ANN, GRU, CEEMD–GRU) is compared based on findings reported in the literature. The results indicate that hybrid optimization approaches are more effective in reducing uncertainty. The study also identifies future research directions, including turbine classification specific to Türkiye, site validation, and artificial intelligence-assisted real-time optimization.
Nesrin İlgin Beyazit (Wed,) studied this question.
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