Comparative Performance of Meta-Heuristic Algorithms for Low-Speed Wind Turbine Blade Structural Optimization
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Abstract
The comparative assessment of recent Metaheuristics (MHs) optimization techniques was conducted within the context of low-speed wind turbine (LS-WT) blade design, with a focus on simultaneously addressing aerodynamic and structural considerations. The study encompasses two LS-WT design problems: the first aims to minimize wind turbine (WT) mass, while the second employs a weighted sum technique to simultaneously minimize WT mass and maximize turbine power. A comparative study on the performance of several recent MHs on the LS-WT problems has been conducted. The optimal design of the WT in the second problem exhibits greater dimensions compared to the shape in the first problem. The WT mass in the second problem is approximately 21 percent higher than in the first problem, reflecting the higher power output achieved in the second problem is more than 5.7 percent compared to the first problem. Statistical analysis of fitness values revealed that L-SHADE exhibited superior performance in terms of both average fitness and standard deviation compared to other algorithms.
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This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
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