Aerodynamic design optimization of wind turbine rotors under geometric uncertainty

Abstract

Presented is a robust optimization strategy for the aerodynamic design of horizontal axis wind turbine rotors including the variability of the annual energy production due to the uncertainty of the blade geometry caused by manufacturing and assembly errors. The energy production of a rotor designed with the proposed robust optimization approach features lower sensitivity to stochastic geometry errors with respect to that of a rotor designed with the conventional deterministic optimization approach that ignores these errors. The geometry uncertainty is represented by normal distributions of the blade pitch angle, and the twist angle and chord of the airfoils. The aerodynamic module is a blade-element momentum theory code. Both Monte Carlo sampling and the univariate reduced quadrature technique, a novel deterministic uncertainty analysis method, are used for uncertainty propagation. The performance of the two approaches is assessed in terms of accuracy and computational speed. A two-stage multi-objective evolutionbased optimization strategy is used. Results highlight that, for the considered turbine type, the sensitivity of the annual energy production to rotor geometry errors can be reduced by reducing the rotational speed and increasing the blade loading. The primary objective of the paper is to highlight how to incorporate an efficient and accurate uncertainty propagation strategy in wind turbine design. The formulation of the considered design problem does not include all the engineering constraints adopted in real turbine design, but the proposed probabilistic design strategy is fairly independent of the problem definition and can be easily extended to turbine design systems of any complexity

Multidisciplinary Design Optimization of Aerospace Transportation Systems

“…MOPED has been successfully used to solve test cases [2] and engineering problems, such as the MOO of a hang-glider rigid wing [66,67], the optimal orbit acquisition of formation flying satellites [3], the MOO of subsonic airfoils [34,68,69], the optimization of orbit transfer maneuvers [70,71], the optimization of flight control systems [72,73], and the robust design of wind turbines [74][75][76].…”

Aeroelastic validation and Bayesian updating of a downwind wind turbine

“…However, unsteady effects were not considered due to computational limitations. An aerodynamic design optimisation for a horizontal axis wind turbine (HAWT) under geometric uncertainty was studied using the univariate reduced quadrature (UEQ) approach, but the aerodynamics was based on blade element momentum (BEM) and a single airfoil shape was employed for the entire length of the blade. A stochastic analysis of flow‐induced instabilities because of uncertainties in flow forces as well as structural properties was performed using a linear stability analysis and modelling the aerodynamics based on Theodorsen theory.…”

“…However, unsteady effects were not considered due to computational limitations. An aerodynamic design optimisation for a horizontal axis wind turbine (HAWT) under geometric uncertainty was studied 30 using the univariate reduced quadrature (UEQ) approach, but the aerodynamics was based on blade element momentum (BEM) and a single airfoil shape was employed for the entire length of the blade.…”

Inverse Aerodynamic Optimization Considering Impacts of Design Tip Speed Ratio for Variable-Speed Wind Turbines

“…Therefore, the aerodynamic optimization of wind turbine rotors plays a crucial role in the design of wind turbines. Generally, the current aerodynamic design for wind turbines is divided into two major categories: the direct method [2][3][4][5][6][7][8][9][10] and the inverse method [11][12][13][14][15][16][17]. As compared with the former, the latter is distinguished by its clear principle, analytical process and fast convergence.…”