Integrated Multidisciplinary Constrained Optimization of Offshore Support Structures

Haghi, Rad; Ashuri, Turaj; Valk, P.; Molenaar, D. P.

doi:10.1088/1742-6596/555/1/012046

Cited by 18 publications

(12 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Fatigue damage calculation is performed using rain-flow cycle counting based on the stress time-signals, and the PalmgrenMiner rule [51,52]. The tower design constraints are the stresses and fatigue damage at 6 cross sections along the tower, and the first and second natural frequencies.…”

Section: Design Constraintsmentioning

confidence: 99%

Multidisciplinary design optimization of large wind turbines—Technical, economic, and design challenges

Ashuri

Zaaijer

Martins

et al. 2016

Energy Conversion and Management

Self Cite

View full text Add to dashboard Cite

a b s t r a c tWind energy has experienced a continuous cost reduction in the last decades. A popular cost reduction technique is to increase the rated power of the wind turbine by making it larger. However, it is not clear whether further upscaling of the existing wind turbines beyond the 5-7 MW range is technically feasible and economically attractive. To address this question, this study uses 5, 10, and 20 MW wind turbines that are developed using multidisciplinary design optimization as upscaling data points. These wind turbines are upwind, 3-bladed, pitch-regulated, variable-speed machines with a tubular tower. Based on the design data and properties of these wind turbines, scaling trends such as loading, mass, and cost are developed. These trends are used to study the technical and economical aspects of upscaling and its impact on the design and cost. The results of this research show the technical feasibility of the existing wind turbines up to 20 MW, but the design of such an upscaled machine is cost prohibitive. Mass increase of the rotor is identified as a main design challenge to overcome. The results of this research support the development of alternative lightweight materials and design concepts such as a two-bladed downwind design for upscaling to remain a cost effective solution for future wind turbines.

show abstract

Section: Design Constraintsmentioning

confidence: 99%

Multidisciplinary design optimization of large wind turbines—Technical, economic, and design challenges

Ashuri

Zaaijer

Martins

et al. 2016

Energy Conversion and Management

Self Cite

View full text Add to dashboard Cite

show abstract

“…5 Previous studies have tackled several areas in wind turbine design, ranging from the optimization of rotor design [6][7][8][9][10] to support structure design. [11][12][13] These studies used various levels of fidelity in the models, ranging from low fidelity (blade element momentum-based fidelity) [14][15][16][17][18][19][20] to higher fidelity (free and prescribed vortex-based fidelity). [21][22][23][24][25][26][27] Currently, most wind turbine blade designs are based on low fidelity models because of their ease of implementation, lower computational cost, and fast convergence to feasible solutions.…”

Section: Introductionmentioning

confidence: 99%

Aerodynamic shape optimization of wind turbine blades using a Reynolds-averaged Navier-Stokes model and an adjoint method

2016

Self Cite

View full text Add to dashboard Cite

Computational fluid dynamics (CFD) is increasingly used to analyze wind turbines, and the next logical step is to develop CFD‐based optimization to enable further gains in performance and reduce model uncertainties. We present an aerodynamic shape optimization framework consisting of a Reynolds‐averaged Navier Stokes solver coupled to a numerical optimization algorithm, a geometry modeler, and a mesh perturbation algorithm. To efficiently handle the large number of design variables, we use a gradient‐based optimization technique together with an adjoint method for computing the gradients of the torque coefficient with respect to the design variables. To demonstrate the effectiveness of the proposed approach, we maximize the torque of the NREL VI wind turbine blade with respect to pitch, twist, and airfoil shape design variables while constraining the blade thickness. We present a series of optimization cases with increasing number of variables, both for a single wind speed and for multiple wind speeds. For the optimization at a single wind speed performed with respect to all the design variables (1 pitch, 11 twist, and 240 airfoil shape variables), the torque coefficient increased by 22.4% relative to the NREL VI design. For the multiple‐speed optimization, the torque increased by an average of 22.1%. Depending on the CFD mesh size and number of design variables, the optimization time ranges from 2 to 24h when using 256 cores, which means that wind turbine designers can use this process routinely. Copyright © 2016 John Wiley & Sons, Ltd.

show abstract

“…Similarly, for the optimum tower, fatigue is an active constraint, which is typically the case for structures subjected to turbulent wind loading. Further information on the design constraint trends has been detailed in previous work . Table lists the active design constraints for both the blade and tower at the optimum.…”

Section: Resultsmentioning

confidence: 99%

“…Further information on the design constraint trends has been detailed in previous work. [58][59][60][61][62][63] Table X lists the active design constraints for both the blade and tower at the optimum. Figure 3 shows a schematic view of the wind turbine compared with the largest man-made space rocket, Saturn V, to show the relative scale of the two designs.…”

Section: Design Variables and Constraintsmentioning

confidence: 99%

Aeroservoelastic design definition of a 20 MW common research wind turbine model

et al. 2016

View full text Add to dashboard Cite

Wind turbine upscaling is motivated by the fact that larger machines can achieve lower levelized cost of energy. However, there are several fundamental issues with the design of such turbines, and there is little public data available for large wind turbine studies. To address this need, we develop a 20 MW common research wind turbine design that is available to the public. Multidisciplinary design optimization is used to define the aeroservoelastic design of the rotor and tower subject to the following constraints: blade‐tower clearance, structural stresses, modal frequencies, tip‐speed and fatigue damage at several sections of the tower and blade. For the blade, the design variables include blade length, twist and chord distribution, structural thicknesses distribution and rotor speed at the rated. The tower design variables are the height, and the diameter distribution in the vertical direction. For the other components, mass models are employed to capture their dynamic interactions. The associated cost of these components is obtained by using cost models. The design objective is to minimize the levelized cost of energy. The results of this research show the feasibility of a 20 MW wind turbine and provide a model with the corresponding data for wind energy researchers to use in the investigation of different aspects of wind turbine design and upscaling. Copyright © 2016 John Wiley & Sons, Ltd.

show abstract

Integrated Multidisciplinary Constrained Optimization of Offshore Support Structures

Cited by 18 publications

References 16 publications

Multidisciplinary design optimization of large wind turbines—Technical, economic, and design challenges

Multidisciplinary design optimization of large wind turbines—Technical, economic, and design challenges

Aerodynamic shape optimization of wind turbine blades using a Reynolds-averaged Navier-Stokes model and an adjoint method

Aeroservoelastic design definition of a 20 MW common research wind turbine model

Contact Info

Product

Resources

About