Optimasi Desain Turbin Angin Vertikal Menggunakan Algoritma Genetika untuk Peningkatan Efisiensi Energi
Keywords:
Computational Fluid Dynamics, Design Optimization, Energy Efficiency, Genetic Algorithm, Vertical Wind TurbineAbstract
This research aims to optimize the design of a vertical wind turbine to increase the efficiency of converting wind energy into electricity. The main problem faced by conventional vertical wind turbines is the low power coefficient due to suboptimal blade shape and design parameters. To address this issue, this research applies a genetic algorithm (GA) as an evolutionary optimization method to determine the best combination of parameters, such as angle of attack, number of blades, and rotor height-to-diameter ratio. Numerical simulations were performed using computational fluid dynamics (CFD) software to evaluate the aerodynamic performance of each design variation generated by the algorithm. The results show that the application of the genetic algorithm successfully increased energy efficiency by up to 18% compared to the initial design, with more stable airflow distribution and greater rotor torque. These findings demonstrate that integrating genetic algorithm-based optimization and CFD analysis can be an effective approach in developing high-performance vertical wind turbines, while simultaneously supporting increased utilization of renewable energy.
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