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At least 19 records

FAST Modularization Framework for Wind Turbine Simulation: Full-System Linearization: Preprint

The wind engineering community relies on multiphysics engineering software to run nonlinear time-domain simulations e.g. for design-standards-based loads analysis. Although most physics involved in wind energy are nonlinear, linearization of the underlying nonlinear system equations is often advantageous to understand the system response and exploit well-established methods and tools for analyzing linear systems. This paper presents the development and verification of the new linearization functionality of the open-source engineering tool FAST v8 for land-based wind turbines, as well as the concepts and mathematical background needed to understand and apply it correctly.

17 WIND ENERGY↗

High-order methods for wind turbine simulations and moving to next-generation platforms

The goal of the ExaWind project is to enable predictive simulations of wind farms comprised of many megawatt-scale turbines situated in complex terrain. Predictive simulations will require computational fluid dynamics (CFD) simulations for which the mesh resolves the geometry of the turbines and captures the rotation and large deflections of blades. Whereas such simulations for a single turbine are arguably petascale class, multi-turbine wind farm simulations will require exascale-class resources. The primary physics codes in the ExaWind project are Nalu-Wind, which is an unstructured-grid solver for the acoustically incompressible Navier-Stokes equations, and OpenFAST, which is a whole-turbine simulation code. The Nalu-Wind model consists of the mass-continuity Poisson-type equation for pressure and a momentum equation for the velocity. For such modeling approaches, simulation times are dominated by linear-system setup and solution for the continuity and momentum systems. For the ExaWind challenge problem, the moving meshes greatly affect overall solver costs as reinitialization of matrices and recomputation of preconditioners is required at every time step. This milestone represents an effort to increase the fidelity of Nalu-Wind at a fixed resolution through the implementation of a tensor-product based, matrix-free high order scheme. High order finite element methods have increased local work per datum communicated and have the potential to provide significantly more accurate solutions at a fixed number of degrees of freedom. Previous to this milestone, Nalu-Wind had an arbitrary order Control Volume Finite Element Method discretization as a solver option, but it required too much memory and was too slow to be of practical use. The work in this milestone addresses these issues by first implementing an implicit, high order solver that only partially assembles the global system. This reduces the memory footprint of the high-order scheme by orders of magnitude for higher polynomial orders. Second, a faster, tensor-product based method for evaluating the action of the left-hand side was implemented. This reduces the amount of computational work required by the scheme and dramatically enhanced the time-to-solution on example problems. Finally, this milestone is an evaluation of the value of high order methods in the wind application space. With the enhancements to memory and computational cost, accuracy vs. time-to-solution was evaluated for several resolutions on an under-resolved Taylor Green vortex test case. Results show that the high order scheme is cost-competitive with the production low-order schemes in Nalu-Wind, being moderately more expensive than the production edge-based vertex centered finite volume scheme. The evaluation of accuracy on the test case shows a potential benefit to high order at the highest resolution while not deteriorating accuracy on the lowest tested resolution. More work is needed to show value in the wind application, but positive strides have been made.

17 WIND ENERGY↗

A new coupling of a GPU-resident large-eddy simulation code with a multiphysics wind turbine simulation tool

The development of new wind farm control strategies can benefit from combined analysis of flow dynamics in the farm and the behavior of individual turbines within one simulation environment. In this work, we present such an environment by developing a new coupling between the large-eddy simulation (LES) code GRASP and the multiphysics wind turbine simulation tool OpenFAST via an actuator line model (ALM). In addition, the implementation of the recently proposed filtered actuator line model (FALM) within the coupling is described. The new ALM implementation is cross-verified with results from four other commonly used research LES codes. The results for the blade loads and the near wake obtained with the new coupling are consistent with the other codes. Deviations are observed in the far wake. The results further indicate that the FALM is able to reduce the lift and power overprediction from which the traditional ALM suffers on coarse LES grids. This new simulation environment paves the way for future wind farm simulations under realistic weather conditions by leveraging GRASP's ability to impose data from large-scale meteorological models as boundary conditions.

17 WIND ENERGY↗

Trailed vorticity modeling for aeroelastic wind turbine simulations in stand still

Current fast aeroelastic wind turbine codes suitable for certification lack an induction model for standstill conditions. A trailed vorticity model previously used as addition to a blade element momentum theory based aerodynamic model in normal operation has been extended to allow computing the induced velocities in standstill. The model is validated against analytical results for an elliptical wing in constant inflow and against stand still measurements from the NREL/NASA Phase VI unsteady experiment. The extended model obtains good results in case of the elliptical wing, but underpredicts the steady loading for the Phase VI blade in attached flow. The prediction of the dynamic force coefficient loops from the Phase VI experiment is improved by the trailed vorticity modeling in both attached flow and stall in most cases. The exception is the tangential force coefficient in stall, where the codes and measurements deviate and no clear improvement is visible.

17 WIND ENERGY↗

ExaWind: Open‐source CFD for hybrid‐RANS/LES geometry‐resolved wind turbine simulations in atmospheric flows

Abstract Predictive high‐fidelity modeling of wind turbines with computational fluid dynamics, wherein turbine geometry is resolved in an atmospheric boundary layer, is important to understanding complex flow accounting for design strategies and operational phenomena such as blade erosion, pitch‐control, stall/vortex‐induced vibrations, and aftermarket add‐ons. The biggest challenge with high‐fidelity modeling is the realization of numerical algorithms that can capture the relevant physics in detail through effective use of high‐performance computing. For modern supercomputers, that means relying on GPUs for acceleration. In this paper, we present ExaWind, a GPU‐enabled open‐source incompressible‐flow hybrid‐computational fluid dynamics framework, comprising the near‐body unstructured grid solver Nalu‐Wind, and the off‐body block‐structured‐grid solver AMR‐Wind, which are coupled using the Topology Independent Overset Grid Assembler. Turbine simulations employ either a pure Reynolds‐averaged Navier–Stokes turbulence model or hybrid turbulence modeling wherein Reynolds‐averaged Navier–Stokes is used for near‐body flow and large eddy simulation is used for off‐body flow. Being two‐way coupled through overset grids, the two solvers enable simulation of flows across a huge range of length scales, for example, 10 orders of magnitude going from O(μm) boundary layers along the blades to O(10 km) across a wind farm. In this paper, we describe the numerical algorithms for geometry‐resolved turbine simulations in atmospheric boundary layers using ExaWind. We present verification studies using canonical flow problems. Validation studies are presented using megawatt‐scale turbines established in literature. Additionally presented are demonstration simulations of a small wind farm under atmospheric inflow with different stability states.

17 WIND ENERGY↗

Implementation and Validation of a Generalized Actuator Disk Parameterization for Wind Turbine Simulations Within the FastEddy Model

ABSTRACT Fast and accurate large‐eddy simulation (LES) of the atmospheric boundary layer plays a crucial role in advancing wind energy research. Long‐duration wind farm studies at turbine‐resolving scales have become increasingly important to understand the intricate interactions between large wind farms and the atmospheric boundary layer. However, the prohibitive computational cost of these turbulence‐ and turbine‐resolving simulations has precluded such modeling to be exercised on a regular basis. To that end, we implement and validate the generalized actuator disk (GAD) model in the computationally efficient, graphics processing unit (GPU)–resident, LES model FastEddy. We perform single‐turbine simulations under three atmospheric stabilities (neutral, unstable, and stable) and compare them against observations from the Scaled Wind Farm Technology (SWiFT) facility and other LES codes from the recent Wakebench turbine wake model benchmark. Our idealized LES results agree well with observed wake velocity deficit and downstream recovery across stability regimes. Turbine response in terms of rotational speed, generated power, torque, and thrust coefficient are well predicted across stability regimes and are consistent with the LES results from the benchmark. The FastEddy simulations are found to be at least two orders of magnitude more efficient than the traditional CPU‐based LES models, opening the door for realistic LES simulations of full wind plants as a viable standard practice.

17 WIND ENERGY↗

Analysis of Wind Turbine Simulation Models: Assessment of Simplified versus Complete Methodologies: Preprint

This paper presents the current status of simplified wind turbine models used for power system stability analysis. This work is based on the ongoing work being developed in IEC 61400-27. This international standard, for which a technical committee was convened in October 2009, is focused on defining generic (also known as simplified) simulation models for both wind turbines and wind power plants. The results of the paper provide an improved understanding of the usability of generic models to conduct power system simulations.

17 WIND ENERGY↗

Impact of Limited Degree of Freedom Drag Coefficients on a Floating Offshore Wind Turbine Simulation

The worldwide effort to design and commission floating offshore wind turbines (FOWT) is motivating the need for reliable numerical models that adequately represent their physical behavior under realistic sea states. However, properly representing the hydrodynamic quadratic damping for FOWT remains uncertain, because of its dependency on the choice of drag coefficients (dimensionless or not). It is hypothesized that the limited degree of freedom (DoF) drag coefficient formulation that uses only translational drag coefficients causes mischaracterization of the rotational DoF drag, leading to underestimation of FOWT global loads, such as tower base fore-aft shear. To address these hydrodynamic modeling uncertainties, different quadratic drag models implemented in the open-source mid-fidelity simulation tool, OpenFAST, were investigated and compared with the experimental data from the Offshore Code Comparison Collaboration, Continued, with Correlation (OC5) project. The tower base fore-aft shear and up-wave mooring line tension were compared under an irregular wave loading condition to demonstrate the effects of the different damping models. Two types of hydrodynamic quadratic drag formulations were considered: (1) member-based dimensionless drag coefficients applied only at the translational DoF (namely limited-DoF drag model) and (2) quadratic drag matrix model (in dimensional form). Based on the results, the former consistently underestimated the 95th percentile peak loads and spectral responses when compared to the OC5 experimental data. In contrast, the drag matrix models reduced errors in estimates of the tower base shear peak load by 7–10% compared to the limited-DoF drag model. The underestimation in the tower base fore-aft shear was thus inferred be related to mischaracterization of the rotational pitch drag and the heave motion/drag by the limited-DoF model.

17 WIND ENERGY↗

Evaluation of different inertial control methods for variable-speed wind turbines simulated by fatigue, aerodynamic, structures and turbulence (FAST)

To mitigate the degraded power system inertia and undesirable primary frequency response caused by large-scale wind power integration, the frequency support capabilities of variable-speed wind turbines is studied in this work. This is made possible by controlled inertial response, which is demonstrated on a research turbine - controls advanced research turbine, 3-bladed (CART3). Two distinct inertial control (IC) methods are analysed in terms of their impacts on the grids and the response of the turbine itself. The released kinetic energy in the IC methods are determined by the frequency measurement or shaped active power reference in the turbine speed-power plane. The wind turbine model is based on the high-fidelity turbine simulator fatigue, aerodynamic, structures and turbulence, which constitutes the aggregated wind power plant model with the simplified power converter model. The IC methods are implemented over the baseline CART3 controller, evaluated in the modified 9-bus and 14-bus testing power grids considering different wind speeds and different wind power penetration levels. The simulation results provide various insights on designing such kinds of ICs. The authors calculate the short-term dynamic equivalent loads and give a discussion about the turbine structural loadings related to the inertial response.

17 WIND ENERGY↗

Recommendations on Model Fidelity for Wind Turbine Gearbox Simulations: Preprint

This work investigates the minimum level of fidelity required to accurately simulate wind turbine gearboxes using state-of-the-art design tools. Excessive model fidelity including drivetrain complexity, gearbox complexity, excitation sources, and imperfections, significantly increases computational time, but may not provide a commensurate increase in the value of the results. Essential design parameters are evaluated, including the planetary load-sharing factor, gear tooth load distribution, and sun orbit motion. Based on the sensitivity study results, recommendations for the minimum model fidelities are provided.

17 WIND ENERGY↗

The creation of a comprehensive metocean data set for offshore wind turbine simulations: Comprehensive metocean data set

A database of meteorological and ocean conditions is presented for use in offshore wind energy research and design. The original data are from 23 ocean sites around the USA and were obtained from the National Data Buoy Center run by the National Oceanic and Atmospheric Administration. The data are presented in a processed form that includes the variables of interest for offshore wind energy design: wind speed, significant wave height, wave peak-spectral period, wind direction and wave direction. For each site, a binning process is conducted to create conditional probability functions for each of these variables. The sites are then grouped according to geographic location and combined to create three representative sites, including a West Coast site, an East Coast site and a Gulf of Mexico site. Both the processed data and the probability distribution parameters for the individual and representative sites are being hosted on a publicly available domain by the National Renewable Energy Laboratory, with the intent of providing a standard basis of comparison for meteorological and ocean conditions for offshore wind energy research worldwide.

17 WIND ENERGY↗

Scavenger removal of bird carcasses at simulated wind turbines: Does carcass type matter?

Abstract Wind energy development can negatively impact bird populations due to bird–turbine collisions. To accurately estimate bird mortality at wind farms, the number of dead birds found under turbines is commonly corrected for carcass removal by scavengers, which is quantified by measuring persistence of experimental carcasses through time. These studies often use domestic birds as surrogates because carcasses of wild birds (e.g., raptors) are difficult to obtain. We assessed scavenger removal of carcasses from five bird species at simulated turbines to determine whether domestic surrogates are scavenged at a different rate than raptors, species of interest for wind turbine mortality. The percentage of carcasses scavenged during 14‐d rounds ranged from 34.6% for American kestrels ( Falco sparverius ) to 65.4% for chickens ( Gallus gallus ), and the percentage of carcasses completely removed ranged from 13.5% for red‐tailed hawks ( Buteo jamaicensis ) to 67.3% for northern bobwhites ( Colinus virginianus ). Carcass type (i.e., species) was the only predictor included in the best‐fit logistic regression model of complete carcass removal, and a survival analysis indicated carcass type influenced elapsed time to scavenging events. Our results suggest the use of surrogate species to quantify carcass removal at wind turbines could lead to inaccurate mortality estimates.

17 WIND ENERGY↗

The Role of Surface Energy Exchange for Simulating Wind Inflow: An Evaluation of Multiple Land Surface Models in WRF for the Southern Great Plains Site Field Campaign Report

The Weather Research and Forecasting (WRF) model is used to investigate choice of land surface model (LSM) on the near-surface wind profile, including heights reached by multi-megawatt wind turbines. Simulations of wind profiles and surface energy fluxes were made using five LSMs of varying degrees of sophistication in dealing with soil-plant-atmosphere feedbacks for the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility’s Southern Great Plains (SGP) Central Facility in Oklahoma. Surface-flux and wind-profile measurements were available for validation. The WRF model was run for three two-week periods during which varying canopy and meteorological conditions existed. The LSMs predicted a wide range of energy-flux and wind-shear magnitudes even during the cool autumn period when we expected less variability. Simulations of energy fluxes varied in accuracy by model sophistication, whereby LSMs with very simple or no soil-plant-atmosphere feedbacks were the least accurate; however, the most complex models did not consistently produce more accurate results. Errors in wind shear also were sensitive to LSM choice and were partially related to the accuracy of energy flux data. The variability of LSM performance was relatively high, suggesting that LSM representation of energy fluxes in the WRF model remains a significant source of uncertainty for simulating wind turbine inflow conditions.

54 ENVIRONMENTAL SCIENCES↗

A Comparison of Classical and Aggregation-Based Algebraic Multigrid Preconditioners for High-Fidelity Simulation of Wind Turbine Incompressible Flows

This paper presents a comparison of parallel strong scaling performance of classical and aggregation algebraic multigrid (AMG) preconditioners in the context of wind turbine simulations. Fluid motion is governed by the incompressible Navier--Stokes equations, discretized in space with control-volume finite elements and in time with an inexact projection scheme using an implicit integrator. A discontinuous-Galerkin sliding-mesh algorithm captures rotor motion. The momentum equations are solved with iterative Krylov methods, preconditioned by symmetric Gauss--Seidel (SGS) in Trilinos and $\ell_1$ SGS in hypre. The mass-continuity equation is solved with GMRES preconditioned by AMG and can account for the majority of simulation time. Reducing this continuity solve time is crucial. Wind turbine simulations present two unique challenges for AMG preconditioned solvers: the computational meshes include strongly anisotropic elements, and mesh motion requires matrix reinitialization and computation of preconditioners at each time step. Detailed timing profiles are presented and analyzed, and best practices are discussed for both classical and aggregation-based AMG. Results are presented for simulations of two different wind turbines with up to 6 billion grid points on two different computer architectures. For moving mesh problems that require linear-system reinitialization, the well-established strategy of amortizing preconditioner setup costs over a large number of time steps to reduce the solve time is no longer valid. Instead, results show that faster time to solution is achieved by reducing preconditioner setup costs at the expense of linear-system solve costs. Standard smoothed aggregation with Chebyshev relaxation was found to perform poorly when compared with classical AMG in terms of solve time and robustness. However, plain aggregation was comparable to classical AMG.

97 MATHEMATICS AND COMPUTING↗