Design of an Aeroelastically Tailored 10 MW Wind Turbine Rotor

Zahle, Frederik; Tibaldi, Carlo; Pavese, Christian; McWilliam, Michael; Blasques, José Pedro Albergaria Amaral; Hansen, Morten Hartvig

doi:10.1088/1742-6596/753/6/062008

Cited by 34 publications

(42 citation statements)

References 8 publications

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“…The HAWTOpt2 optimization framework [Zahle et al (2016)] is a MDO tool developed by DTU Wind Energy based on…”

Section: Optimization Frameworkmentioning

confidence: 99%

“…The framework evaluates the fatigue damage with a frequency domain model from HAWCStab2 [Tibaldi et al (2015)]. More details on the framework are given in [Zahle et al (2016)]. …”

Section: Optimization Frameworkmentioning

confidence: 99%

“…In the recent years several MDO frameworks have been developed to perform wind turbine multi-disciplinary optimization design (Bottasso et al (2012); Ashuri et al (2014); Merz (2015a, b) ;Fischer et al (2014); Ning et al (2014); McWilliam (2015)). In this work an optimization framework called HAWTOpt2 [Zahle et al (2016)] is utilized which enables concurrent optimization of the structure and outer shape of a wind turbine blade. This tool 15 builds on the experience gained with the HAWTOpt code [Fuglsang and Madsen (1999)] but is otherwise a completely new code-base written in the Python programming language.…”

mentioning

confidence: 99%

“…The HAWTOpt2 framework will produce aero-elastic tailored blades that will passively torsion to shed loads [Zahle et al (2016)]. This work looked at how passive load alleviation 20 Wind Figure 9 shows the torsional deformation at the tip over a range of wind-speeds in steady uniform conditions.…”

mentioning

confidence: 99%

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Aero-elastic Wind Turbine Design with Active Flaps for AEP Maximization

McWilliam¹,

Barlas²,

Madsen³

et al. 2017

Preprint

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Abstract.In optimal wind turbine design, there is a compromise between maximizing the energy producing forces and minimizing the absolute peak loads carried by the structures. Active flaps are an attractive strategy because they give engineers greater freedom to vary the aerodynamic forces under any condition. Flaps can be used in a variety of different ways (i.e. reducing fatigue, peak loads etc.), however this article focuses on how quasi-static actuation as a function of mean wind speed can be used for Annual 5 Energy Production (AEP) maximization. Numerical design optimization of the DTU 10M W Reference Wind Turbine (RWT), with the HAWTOpt2 framework, was used to both find the optimal flap control strategy and the optimal turbine designs. The research shows that active flaps can provide a 1% gain in AEP for aero-structurally optimized blades in both add-on (i.e. the flap is added after the blade is designed) and integrated (i.e. the blade design and flap angle is optimized together) solutions.The results show that flaps are complementary to passive load alleviation because they provide high-order alleviation, where 10 passive strategies only provide linear alleviation with respect to average wind speed. However, the changing loading from the flaps further complicates the design of torsionally active blades, thus, integrated design methods are needed to design these systems.

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“…The HAWTOpt2 optimization framework [Zahle et al (2016)] is a MDO tool developed by DTU Wind Energy based on…”

Section: Optimization Frameworkmentioning

confidence: 99%

“…The framework evaluates the fatigue damage with a frequency domain model from HAWCStab2 [Tibaldi et al (2015)]. More details on the framework are given in [Zahle et al (2016)]. …”

Section: Optimization Frameworkmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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Aero-elastic Wind Turbine Design with Active Flaps for AEP Maximization

McWilliam¹,

Barlas²,

Madsen³

et al. 2017

Preprint

Self Cite

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“…This has been addressed by several previous works using BEM-based aeroleastic tools combined with various cross-sectional analytical or finite element based structural tools. Zahle et al showed that simultaneous design of the aerodynamic shape and structural layout of a blade leads to passive load alleviation through torsional couplings Zahle et al (2016) allowing significant increases in AEP without increasing loads and blade mass. LCoE has been minimized by other researchers while taking aerodynamics, structures, and controls into account, thereby truly treating it as an MDO problem both for 5 MW turbines (Ashuri et al, 2014) and for 20 MW turbines (Ashuri et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Multipoint high-fidelity CFD-based aerodynamic shape optimization of a 10 MW wind turbine

Madsen¹,

Zahle²,

Sørensen³

et al. 2018

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Abstract. The wind energy industry relies heavily on CFD to analyze new turbine designs. To utilize CFD further upstream the design process where lower fidelity methods such as BEM are more common, requires the development of new tools. Tools that utilize numerical optimization are particularly valuable because they reduce the reliance on design by trial and error. We present the first comprehensive 3D CFD adjoint-based shape optimization of a modern 10&thisp;MW offshore wind turbine. The optimization problem is aligned with a case study from IEA Wind Task 37, making it possible to compare our findings with the BEM results from this case study, allowing us to determine the value of design optimization based on high-fidelity models. The comparison shows, that the overall design trends suggested by the two models do agree, and that it is particularly valuable to consult the high-fidelity model in areas such as root and tip where BEM is inaccurate. In addition, we compare two different CFD solvers to quantify the effect of modeling compressibility and to estimate the accuracy of the chosen grid resolution and order of convergence of the solver. Meshes up to 14 · 106 cells are used in the optimization whereby flow details are resolved. The present work shows that it is now possible to successfully optimize modern wind turbines aerodynamically under normal operating conditions using RANS models. The key benefit of a 3D RANS approach is that it is possible to optimize the blade planform and cross-sectional shape simultaneously, thus tailoring the shape to the actual 3D flow over the rotor, which is particularly important near the root and tip of the blade. This work does not address evaluation of extreme loads used for structural sizing, where BEM-based methods have proven very accurate, and therefore will likely remain the method of choice.

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Including the power regulation strategy in aerodynamic optimization of wind turbines for increased design freedom

2022

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In wind turbine optimization, the standard power regulation strategy follows a constrained trajectory based on the maximum power coefficient. It can be updated automatically during the optimization process by solving a nested maximization problem at each iteration. We argue that this model does not take advantage of the load alleviation potential of the regulation strategy and additionally requires significant computational effort. An alternative approach is proposed, where the rotational speed and pitch angle control points for the entire operation range are set as design variables, changing the problem formulation from nested to one-level. The nested and one-level formulations are theoretically and numerically compared on different aerodynamic blade design optimization problems for AEP maximization. The aerodynamics are calculated with a steady-state blade element momentum method. The onelevel approach increases the design freedom of the problem and allows introducing a secondary objective in the design of the regulation strategy. Numerical results indicate that a standard regulation strategy can still emerge from a one-level optimization. Second, we illustrate that novel optimal regulation strategies can emerge from the one-level optimization approach. This is demonstrated by adding a thrust penalty term and a constraint on the maximum thrust. A region of minimal thrust tracking and a peak-shaving strategy appear automatically in the optimal design.control co-design, multi-disciplinary analysis and optimization, power regulation strategy, wind turbine blade design | INTRODUCTIONDesigning a modern wind turbine is a complex engineering task, due to the multi-disciplinary nature and the uncertain environment it must operate in. Many different objectives and requirements need to be considered during the design process: power extraction, reduction of costs, stability, noise, and so forth. In addition, the designer has to take into account the different disciplines involved with the goals of (i) accurately forecast the behavior of the final design and (ii) take advantage of the potential couplings between disciplines to improve the design. This makes numerical optimization an ideal tool to be used for wind turbine design. Numerous studies have focused on the development of numerical tools for optimization with the goal of handling the multi-disciplinary aspect of wind turbine design. For example, Bottasso et al 1 take in account the aero-elastic

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Design of an Aeroelastically Tailored 10 MW Wind Turbine Rotor

Cited by 34 publications

References 8 publications

Aero-elastic Wind Turbine Design with Active Flaps for AEP Maximization

Aero-elastic Wind Turbine Design with Active Flaps for AEP Maximization

Multipoint high-fidelity CFD-based aerodynamic shape optimization of a 10 MW wind turbine

Including the power regulation strategy in aerodynamic optimization of wind turbines for increased design freedom

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