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nlr.gov
official
https://www.nlr.gov/docs/libraries/wind-docs/engineering-wkshp2022-5-1-mangan…
1 CFD-BASED MULTIDISCIPLINARY DESIGN OPTIMIZATION OF WIND TURBINE ROTORS Marco Mangano Joaquim R.R.A. Martins With contributions from: Sicheng He, Yingqian Liao, Denis-Gabriel Caprace, Anil Yildirim, Bernardo Pacini, Josh Anibal ATLANTIS project lead: Mario Garcia-Sanz (ARPA-e) Onur Bilgen (Rutgers) 6th WESE Workshop August 31, 2022 Boulder, CO 2 • The next slides cover: • High-fidelity Multidisciplinary Design Optimization (MDO) of a wind turbine rotor using MACH • A combined-fidelity approach that couples WEIS with MACH for life-cycle sizing constraints • The future of high-fidelity MDO: MPhys Today’s takeaway: High-fidelity MDO is a feasible and effective approach to support wind turbine rotor design How to make high-fidelity MDO computationally efficient?
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mdpi.com
article
https://www.mdpi.com/2227-9717/12/1/22
For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. Editor’s Choice articles are based on recommendations by the scientific editors of MDPI journals from around the world. The aim is to provide a snapshot of some of the most exciting work published in the various research areas of the journal. The optimization framework integrates DAFoam as the computational fluid dynamics (CFD) solver, TACS as the finite element method (FEM) solver, Mphys for fluid–structure coupling, and SNOPT as the optimizer within the OpenMDAO framework. The design variables in this optimization process are the blade shape and panel thickness. The remainder of this paper starts with a literature review on the aerostructural optimization of wind turbine blades in Section 2, followed by the methodology on the aerodynamic optimization, structural optimization, and fluid–structural coupling processes of the aerostructural optimization in Section 3, and the main findings are presented and discussed in Section 4.
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core.ac.uk
article
https://core.ac.uk/download/pdf/217154727.pdf
It is the main aim of this research to present some fundamental issues concerning design optimization of the main wind turbine structures, practical realistic
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simscale.com
article
https://www.simscale.com/blog/optimize-wind-farms-cfd
# Wind Farm Optimization with Turbine Placement Using CFD Simulations. BlogEnergyWind Farm Optimization with Turbine Placement Using CFD Simulations. Simulation is becoming well-known as a tool for wind experiments, and in this article we explore the way the SimScale cloud-based 3D simulation software can be used for the design, simulation, and optimization of the power output of a wind farm. The simplest way to assess the efficiency of a wind turbine is through the Betz Law. Schematic of fluid flow across a wind turbine. This change in velocity, as the wind passes through the rotating turbine blades, signifies the transfer of kinetic energy from the wind to the turbine. A simple measure of the efficiency of the wind turbine can be given by the ratio of change in kinetic energy to the undisturbed energy of the wind, as:energy efficiency of the wind turbine given by ratio of change in kinetic energy to undisturbed energy of wind.
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wes.copernicus.org
article
https://wes.copernicus.org/preprints/wes-2021-56/wes-2021-56.pdf
Wind turbines are complex multidisciplinary systems that are challenging to design because of the tightly coupled interactions between different subsystems. Low-fidelity models are computationally efficient but make assumptions and simplifications that limit the accuracy of design studies, whereas high-fidelity models capture more of the actual physics but with increased computational cost. This paper details the use of multifidelity methods for optimizing wind 5 turbine designs by using information from both low- and high-fidelity models to find an optimal solution at reduced cost. Specifically, a trust-region approach is used with a novel corrective function built from a nonlinear surrogate model. We find that for a diverse set of design problems—with examples given in rotor blade geometry design, wind turbine controller design, and wind power plant layout optimization—the multifidelity method finds the optimal design using 38%–58% the computational cost of the high-fidelity-only optimization. We then formulate and solve three optimization problems: aerodynamic blade design for the IEA 15-MW 60 reference wind turbine; a controls optimization using both linearized and nonlinear state-space models; and a wind power 2 https://doi.org/10.5194/wes-2021-56 Preprint.
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websites.umich.edu
research
https://websites.umich.edu/~mdolaboratory/pdf/Ashuri2014.pdf
Table 8: US Dollar (USD) based cost comparison of the NREL and optimized wind turbines Cost component (1000 USD) NREL Optimized Blades 1062.3 1088.4 Hub 130.2 134.4 Pitch mechanism and bearing 242.0 265.2 Nose cone 13.6 14.3 Low speed shaft 166.8 184.3 Main bearings 64.4 72.7 Gearbox 877.2 877.2 Mechanical brake and coupling 11.0 11.0 Generator 398.0 398.0 Power electronics 393.2 393.2 Yaw drive and bearing 146.3 161.2 Main frame 162.7 174.0 Platform and railing 89.5 95.7 Nacelle cover 73.3 73.3 Electrical connections 308.8 308.8 Hydraulic and cooling system 77.2 77.2 Control,safety and condition monitoring 65.3 65.3 Tower 939.1 1005.5 Marinization 561.6 582.6 Turbine capital costs (TCC) 4722.4 4898.5 Foundation system 2174.7 2174.7 Transportation 1568.3 1568.3 Port and staging equipment 144.9 144.9 Turbine installation 732.8 732.8 Electrical interface and connection 2063.5 2063.5 Permits, engineering and site assessment 215.5 215.5 Personnel access equipment 70.2 70.2 Scour protection 403.0 403.0 Decommissioning 362.8 368.1 Balance of station costs (BOS) 7373.2 7373.2 Offshore warranty premium 624.1 647.4 Initial capital cost (ICC) 13083.0 14651.0 Levelized replacement costs 99.0 99.0 Operation and maintenance 561.4 585.4 Fixed charge rate 0.1185 0.1185 AEP (GWhr) 23.91 25.19 LCOE (USD/kWhr) 0.0658 0.0643 4 Discussion and conclusions For many years, the design of wind turbines was based on a single-discipline or sequential approach Quar-ton [1998].
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arc.aiaa.org
article
https://arc.aiaa.org/doi/10.2514/1.J064556
This work presents the first high-fidelity aerostructural optimization study of a large wind turbine rotor. We use blade-resolved fluid dynamics
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sciencedirect.com
article
https://www.sciencedirect.com/science/article/pii/S0306261925010244
This paper presents a comprehensive review of the latest advancements, challenges, and future directions driven by Artificial Intelligence (AI) in the design