Abstract
Modern wind turbine aero-structural blade design codes generally use a smaller fraction of the full design load base (DLB) or neglect turbulent inflow as defined by the International Electrotechnical Commission standards. The current article describes an automated blade design optimization method based on surrogate modeling that includes a very large number of design load cases (DLCs) including turbulence. In the present work, 325 DLCs representative of the full DLB are selected based on the message-passing-interface (MPI) limitations in Matlab. Other methods are currently being investigated, e.g. a Python MPI implementation, to overcome the limitations in Matlab MPI and ultimately achieve a full DLB optimization framework. The reduced DLB and the annual energy production are computed using the state-of-the-art aero-servo-elastic tool HAWC2. Furthermore, some of the interior dimensions of the blade structure are optimized using the finite-element based cross-sectional analysis tool BECAS. The optimization framework is applied to redesign the NREL 5 MW wind turbine blade to obtain improvements in rotor performance and blade weight.
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