MULTI-OBJECTIVE KRIGING-BASED OPTIMIZATION FOR MODERN WIND TURBINE DESIGN
In this study, we present the implementation of gradient-free multi-objective kriging-based optimization for high fidelity wind turbine design. The optimization process was done by using multi-objective genetic algorithm based on expected hypervolume improvement and high-fidelity computational fluid...
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| Format: | Final Project |
| Language: | Indonesia |
| Online Access: | https://digilib.itb.ac.id/gdl/view/33534 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | In this study, we present the implementation of gradient-free multi-objective kriging-based optimization for high fidelity wind turbine design. The optimization process was done by using multi-objective genetic algorithm based on expected hypervolume improvement and high-fidelity computational fluid dynamics for evaluating the objective functions. These methods are applied on NREL Phase VI wind turbine geometry. The objectives of the optimization are to minimize the blade volume and to maximize the output torque of the wind turbine. Optimization variables are chosen to be 70 control points that can be displaced to obtain various blade geometry. Radial basis function-based mesh deformation technique is applied to deform the wind turbine mesh and geometry. From the present study, the optimization processes are going well and produce a set of solution of the optimized blade. From the set of solutions, three configurations that represent the torque-optimized geometry, balanced-optimized geometry, and volume-optimized geometry are chosen. From the results, the torque-optimized geometry has 6% increase in torque and 1% volume reduction. The balanced-optimized has 4% increase in torque and 5% volume reduction. Meanwhile the volume-optimized geometry has constant torque and 7% volume reduction. |
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