Multi-disciplinary constrained optimization of wind turbines. Bottasso, C. L., Campagnolo, F., & Croce, A. Multibody System Dynamics, 27(1):21–53, Springer, 2012. doi abstract bibtex We describe procedures for the multi-disciplinary design optimization of wind turbines, where design parameters are optimized by maximizing a merit function, subjected to constraints that translate all relevant design requirements. Evaluation of merit function and constraints is performed by running simulations with a parametric high-fidelity aero-servo-elastic model; a detailed cross-sectional structural model is used for the minimum weight constrained sizing of the rotor blade. To reduce the computational cost, the multi-disciplinary optimization is performed by a multi-stage process that first alternates between an aerodynamic shape optimization step and a structural blade optimization one, and then combines the two to yield the final optimum solution. A complete design loop can be performed using the proposed algorithm using standard desktop computing hardware in one-two days. The design procedures are implemented in a computer program and demonstrated on the optimization of multi-MW horizontal axis wind turbines and on the design of an aero-elastically scaled wind tunnel model.
@Article{Bottasso2012,
author = {Bottasso, Carlo Luigi and Campagnolo, Filippo and Croce, Alessandro},
title = {Multi-disciplinary constrained optimization of wind turbines},
doi = {10.1007/s11044-011-9271-x},
journal = {Multibody System Dynamics},
number = {1},
pages = {21--53},
publisher = {Springer},
volume = {27},
year = {2012},
abstract = {We describe procedures for the multi-disciplinary design optimization of wind turbines, where design parameters are optimized by maximizing a merit function, subjected to constraints that translate all relevant design requirements. Evaluation of merit function and constraints is performed by running simulations with a parametric high-fidelity aero-servo-elastic model; a detailed cross-sectional structural model is used for the minimum weight constrained sizing of the rotor blade. To reduce the computational cost, the multi-disciplinary optimization is performed by a multi-stage process that first alternates between an aerodynamic shape optimization step and a structural blade optimization one, and then combines the two to yield the final optimum solution. A complete design loop can be performed using the proposed algorithm using standard desktop computing hardware in one-two days. The design procedures are implemented in a computer program and demonstrated on the
optimization of multi-MW horizontal axis wind turbines and on the design of an aero-elastically scaled wind tunnel model.}
}
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