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This paper presents a fast and efficient aerodynamic optimization method for megawatt class wind turbines. For this purpose WP_Baseline 1.5 MW wind turbine is used as a test case. Modified particle swarm optimization (PSO) algorithm is used in this study. PSO parameteric studies are conducted, to increase both efficiency and speed of optimization cycle. Since in aerodynamic optimization, it is very desirable to limit the number of the variables, in this study geometric 'class function/shape function' transformation technique (CST) is used for blade geometry parameterization and the appropriate order of shape function polynomial is proposed for S818, S825 and S826 airfoils. Improved Blade Element Momentum (IBEM) theory is implemented for wind turbine power output estimation, validated with experimental and Computational Fluid Dynamic (CFD) data of AOC wind turbine. The aerodynamic data needed for IBEM is provided by XFoil software. XFoil output data for pressure coefficient and wall shear stress which are validated against experimental and CFD data, are applied as the aerodynamic input data for IBEM method.
The twist, the chord and 3 types of airfoil for all sections of the turbine blade are optimized using IBEM method. Optimization is performed with realistic constraints to produce feasible geometry. The performance of the final optimized geometry is simulated via 3D steady incompressible Navier–Stokes equations coupled with Transition SST Model CFD simulation to predict the performance improvement. The results show about 4 percent power enhancement for WP_Baseline wind turbine.

Keywords: Optimization, Aerodynamic, Particle Swarm Algorithm, Horizontal axis wind turbine

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