Probabilistic design optimization of horizontal axis wind turbine rotors

Considerable interest in renewable energy has increased in recent years due to the concerns raised over the environmental impact of conventional energy sources and their price volatility. In particular, wind power has enjoyed a dramatic global growth in installed capacity over the past few decades. Nowadays, the advancement of wind turbine industry represents a challenge for several engineering areas, including materials science, computer science, aerodynamics, analytical design and analysis methods, testing and monitoring, and power electronics. In particular, the technological improvement of wind turbines is currently tied to the use of advanced design methodologies, allowing the designers to develop new and more efficient design concepts. Integrating mathematical optimization techniques into the multidisciplinary design of wind turbines constitutes a promising way to enhance the profitability of these devices. In the literature, wind turbine design optimization is typically performed deterministically. Deterministic optimizations do not consider any degree of randomness affecting the inputs of the system under consideration, and result, therefore, in an unique set of outputs. However, given the stochastic nature of the wind and the uncertainties associated, for instance, with wind turbine operating conditions or geometric tolerances, deterministically optimized designs may be inefficient. Therefore, one of the ways to further improve the design of modern wind turbines is to take into account the aforementioned sources of uncertainty in the optimization process, achieving robust configurations with minimal performance sensitivity to factors causing variability. The research work presented in this thesis deals with the development of a novel integrated multidisciplinary design framework for the robust aeroservoelastic design optimization of multi-megawatt horizontal axis wind turbine (HAWT) rotors, accounting for the stochastic variability related to the input variables. The design system is based on a multidisciplinary analysis module integrating several simulations tools needed to characterize the aeroservoelastic behavior of wind turbines, and determine their economical performance by means of the levelized cost of energy (LCOE). The reported design framework is portable and modular in that any of its analysis modules can be replaced with counterparts of user-selected fidelity. The presented technology is applied to the design of a 5-MW HAWT rotor to be used at sites of wind power density class from 3 to 7, where the mean wind speed at 50 m above the ground ranges from 6.4 to 11.9 m/s. Assuming the mean wind speed to vary stochastically in such range, the rotor design is optimized by minimizing the mean and standard deviation of the LCOE. Airfoil shapes, spanwise distributions of blade chord and twist, internal structural layup and rotor speed are optimized concurrently, subject to an extensive set of structural and aeroelastic constraints. The effectiveness of the multidisciplinary and robust design framework is demonstrated by showing that the probabilistically designed turbine achieves more favorable probabilistic performance than those of the initial baseline turbine and a turbine designed deterministically

Robust aerodynamic design optimization of variable speed wind turbine rotors

Background: Manufacturing and assembly tolerances may cause wind turbine (WT) energy production to differ significantly from nominal design targets. Issue can be alleviated in two ways: A. Reducing tolerances. This may be expensive. B. Developing reliable and computationally affordable robust analysis and design optimization technologies. Robust WT rotor is one yielding minimal variations of aerodynamic performance arising due to errors affecting rotor geometry. Objectives: To develop/demonstrate computational framework for the robust design optimization of WT rotors. Main aim is to 1) maximize expectation and 2) minimize standard deviation of yearly energy production. Highlight computational effectiveness of the Univariate Reduced Quadrature approach to ‘deterministic’ uncertainty propagation. Highlight capabilities of a recently developed multi-level evolution-based optimizer

Wind turbine design optimization under environmental uncertainty

Wind turbine design optimization is typically performed considering a given wind distribution. However, turbines so designed often end up being used at sites characterized by different wind distributions, and this results in significant performance penalties. This paper presents a probabilistic integrated multidisciplinary approach to the design optimization of multimegawatt wind turbines accounting for the stochastic variability of the mean wind speed. The presented technology is applied to the design of a 5 MW rotor for use at sites of wind power class from 3 to 7, where the mean wind speed at 50 m above the ground ranges from 6.4 to 11.9 m/s. Assuming the mean wind speed to vary stochastically in such range, the rotor design is optimized by minimizing mean and standard deviation of the levelized cost of energy. Airfoil shapes, spanwise distributions of blade chord and twist, blade internal structural layup and rotor speed are optimized concurrently, subject to structural and aeroelastic constraints. The probabilistically designed turbine achieves a more favourable probabilistic performance than the initial baseline turbine. The presented probabilistic design framework is portable and modular in that any of its analysis modules can be replaced with counterparts of user-selected fidelity

Aerodynamic design optimization of wind turbine rotors under geometric uncertainty

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

Robust aerodynamic design optimization of horizontal axis wind turbines

The work reported in this paper deals with the development of a design system for the robust aerodynamic design optimization of horizontal axis wind turbine rotors. The system developed is here used to design a 126-m diameter, three-bladed rotor, featuring minimal sensitivity to uncertainty associated with blade manufacturing tolerances. In particular, the uncertainty affecting the rotor geometry is associated with the radial distributions of blade chord and twist, and the airfoil thickness. In this study, both geometric and operative design variables are treated as part of the optimization. Airfoil aerodynamics and rotor aeroelasticity are predicted by means of XFOIL and FAST codes, respectively, and a novel deterministic method, the Univariate Reduced Quadrature, is used for uncertainty propagation. The optimization is performed by means of a two-stage multi-objective evolution-based algorithm, aiming to maximize the rotor expected annual energy production and minimize its standard deviation. The design optimization is subjected to a single structural constrain associated with the maximum out-of-plane blade tip deflection. The results of this research highlight that a lower sensitivity to uncertainty tied to manufacturing tolerances can be achieved by lowering the angular speed of the rotor

Wind turbine design optimization under environmental uncertainty

Wind turbine design optimization is typically performed considering a given wind distribution. However, turbines so designed often end up being used at sites characterized by different wind distributions, and this results in significant performance penalties. This paper presents a probabilistic integrated multidisciplinary approach to the design optimization of multimegawatt wind turbines accounting for the stochastic variability of the mean wind speed. The presented technology is applied to the design of a 5 MW rotor to be used at sites of wind power class from 3 to 7, where the mean wind speed at 50 m above the ground ranges from 6.4 to 11.9 m/s. Assuming the mean wind speed to vary stochastically in such range, the rotor design is optimized by minimizing mean and standard deviation of the levelized cost of energy. Airfoil shapes, spanwise distributions of blade chord and twist, internal structural layup and rotor speed are optimized concurrently, subject to structural and aeroelastic constraints. The probabilistically designed turbine achieves a more favorable probabilistic performance than the initial baseline turbine. The presented probabilistic design framework is portable and modular in that any of its analysis modules can be replaced with counterparts of user-selected fidelity

Robust aerodynamic design optimisation of horizontal axis wind turbine rotors

The work reported in this paper deals with the development of a design system for the robust aerodynamic design optimization of horizontal axis wind turbine rotors. The system developed is here used to design a 126-m diameter, three-bladed rotor, featuring minimal sensitivity to uncertainty associated with blade manufacturing tolerances. In particular, the uncertainty affecting the rotor geometry is associated with the radial distributions of blade chord and twist, and the airfoil thickness. In this study, both geometric and operative design variables are treated as part of the optimization. Airfoil aerodynamics and rotor aeroelasticity are predicted by means of XFOIL and FAST codes, respectively, and a novel deterministic method, the Univariate Reduced Quadrature, is used for uncertainty propagation. The optimization is performed by means of a two-stage multi-objective evolution-based algorithm, aiming to maximize the rotor expected annual energy production and minimize its standard deviation. The design optimization is subjected to a single structural constrain associated with the maximum out-of-plane blade tip deflection. The results of this research highlight that a lower sensitivity to uncertainty tied to manufacturing tolerances can be achieved by lowering the angular speed of the rotor

Robust aerodynamic design optimization of horizontal axis wind turbine rotors

The work reported in this paper deals with the development of a design system for the robust aerodynamic design optimization of horizontal axis wind turbine rotors. The system developed is here used to design a 126-m diameter, three-bladed rotor, featuring minimal sensitivity to uncertainty associated with blade manufacturing tolerances. In particular, the uncertainty affecting the rotor geometry is associated with the radial distributions of blade chord and twist, and the airfoil thickness. In this study, both geometric and operative design variables are treated as part of the optimization. Airfoil aerodynamics and rotor aeroelasticity are predicted by means of XFOIL and FAST codes, respectively, and a novel deterministic method, the Univariate Reduced Quadrature, is used for uncertainty propagation. The optimization is performed by means of a two-stage multi-objective evolution-based algorithm, aiming to maximize the rotor expected annual energy production and minimize its standard deviation. The design optimization is subjected to a single structural constrain associated with the maximum out-of-plane blade tip deflection. The results of this research highlight that a lower sensitivity to uncertainty tied to manufacturing tolerances can be achieved by lowering the angular speed of the rotor

Characterization of the unsteady aerodynamic response of a floating offshore wind turbine

The disruptive potential of floating wind turbines has attracted the interest of both industry and scientific community. Lacking a rigid foundation, such machines are subject to large displacements whose impact on the aerodynamic performance is not yet fully acknowledged. In this work, the unsteady aerodynamic response to an harmonic surge motion of a scaled version of the DTU10MW turbine is investigated in detail. The imposed displacements have been chosen representative of typical platform motions. The results of different numerical models are validated against high fidelity wind tunnel tests specifically focused on the aerodynamics. Also a linear analytical model, relying on the quasi-steady assumption, is presented as a theoretical reference. The unsteady responses are shown to be dominated by the first surge harmonic and a frequency domain characterization, mostly focused on the thrust oscillation, is conducted involving aerodynamic damping and mass parameters. A very good agreement among codes, experiments and quasi-steady theory has been found clarifying some literature doubts. A convenient way to describe the unsteady results in non-dimensional form is proposed, hopefully serving as reference for future work