Multi-Criteria Evaluation of Wind Turbines using Entropy-based-TOPSIS and CoCoSo Methods: Insights from a Turkish Case Study
Melisa Şahin, Derya Deli̇ktaş
University of Utah
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This study evaluated different alternatives using entropy-based TOPSIS and CoCoSo techniques, which are multi-criteria decision-making (MCDM) methods, to optimise the decision-making process in wind turbine selection. The study considered six criteria: price, rated power, rotor diameter, turbine size, noise emission value, and annual energy production. As a result of the analyses, Wind turbine-3 and Wind turbine-4 were the most suitable options. The findings revealed that criteria such as energy efficiency, sizeable nominal power, and minimisation of sound emission play a critical role in wind turbine selection. The findings of this study provide a more objective and analytical approach for decision-makers in wind energy projects. The Entropy-based TOPSIS and CoCoSo methodologies used in this study provide consistent and reliable results in evaluating alternatives. In particular, the fact that the CoCoSo method obtains similar rankings with TOPSIS shows that the methods can complement each other in multi-criteria decision-making problems.
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计算机 / AIMulti-Criteria Decision Making
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