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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Wind Turbine Design Optimization for Hydrogen Production

To help meet the need for inexpensive green fuels, we are working on wind turbine design optimization specifically for hydrogen production. We have thus far achieved a 1.53% decrease in LCOH as compared to a turbine optimized for LCOE using the same code, design variables, and models. We accomplished this by optimizing some components of the wind turbine tower, rotor, and drivetrain design with hydrogen production and costs in the design loop.

hydrogen↗
DOE OSTI2023

Development of an Unmanned Mobile Current Turbine Platform: Preprint

The design and development of a prototype unmanned mobile floating platform, equipped with a custom low-flow marine current turbine for autonomously seeking and harnessing tidal/coastal currents is described. The platform is an unmanned surface vehicle in the form of a catamaran with two electric outboard motors and capabilities for autonomous navigation. An undershot water wheel, aided by a custom flow concentrator, has been selected as the basic design for the marine current turbine, which is mounted on the stern of the unmanned surface vehicle platform. The concept of operation is that the platform would navigate to a designated marine current resource, autonomously anchor at the location, align itself in the current and deploy the current turbine using a custom cable-lift deployment mechanism. As the turbine harnesses the local current, an onboard power-take-off device converts the harnessed mechanical energy to electricity which is stored in onboard batteries. Considerations of deployment in tidal and coastal waters required obtaining the necessary environmental permits for conducting in-water testing; developing required mitigation measures in protecting local wildlife and their habitats; and identifying potential in-water test sites and surveying them for their suitability in terms of the current resource, bottom type, water depth, and local boat traffic. The design and development of the turbine and the results of initial in-water testing are discussed. The potential for scaling up the system for extended capacity is presented.

ENGINEERING,TIDAL AND WAVE POWER↗
DOE OSTI2022

Mechanism Analysis of Wind Turbine Var Oscillations

Electromagnetic transient simulation of parallel connected 4-MW type-3 wind turbines based on original equipment manufacturer's real-code turbine model shows 1.2-Hz turbine-turbine oscillations in reactive power. This letter reveals why such oscillations occur in the individual var measurement, while being insignificant in the total var measurement, regardless of the varying grid impedance. We adopt two analysis approaches: open-loop single-input single-output analysis and network decomposition. The two approaches differ in their treatment of turbine-network interaction. The open-loop analysis shows that the turbine-turbine oscillation mode is due to an open-loop system pole being attracted to an open-loop system zero. Furthermore, we use network decomposition method to explain why this mode is observable in individual vars while not observable in the total var. The entire system of n -turbines can be viewed as n decoupled circuits. For the two-turbine case, the system has an aggregated mode and a turbine-turbine oscillation mode. Here, the aggregated mode is associated with a circuit associated with the total var, while the turbine-turbine oscillation mode is associated with the var difference and is insensitive to the grid parameters.

17 WIND ENERGY↗
DOE OSTI2023

On the Low Risk of SSR in Type III Wind Turbines Operating in Grid-Forming Control: Preprint

We have shown in a previous work that the risk of sub-synchronous resonance (SSR) between a wind power plant with Type III wind turbines and series-compensated transmission lines is low when the wind turbines in the plant are operated in grid-forming mode, instead of the standard grid-following mode. The fundamental mechanism behind the improved damping characteristics is explained in this paper by modeling the positive and negative sequence impedances of Type III wind turbines for GFM operation mode. It is discovered that the GFM control naturally acts against the negative resistance of Type III wind turbines that results from an interaction between the proportional gain of the rotor-side converter current controller and negative slip. The developed sequence impedance models and improved damping behavior are verified using PSCAD simulations of a 2.5-MW Type III GFM wind turbine. The modeling predictions are also supported by experimentally measuring the sequence impedance response of a 2.5-MW Type III wind turbine during operation in GFL and GFM modes.

grid-following turbine↗
DOE OSTI2024

In-Situ Blade Strain Measurements and Fatigue Analysis of a Cross-Flow Turbine Operating in a Tidal Flow

Cross-flow turbines (CFTs) are inherently unsteady devices with regards to operating principle and loading. By improving our understanding of the dynamic loading on these turbines, we hope to better inform CFT design, improve survivability, and reduce overall costs. The University of New Hampshire (UNH) and the National Renewable Energy Laboratory (NREL) collaborated on a project to instrument and test a four-bladed New Energy Corp. vertical axis cross-flow turbine in a real tidal flow. One blade from the 3.2 m diameter x 1.7 m height turbine was instrumented with eight full-bridge strain gauges along the span of the blade. The turbine was then deployed at the UNH-Atlantic Marine Energy Center (AMEC) Tidal Energy Test Site in Portsmouth, NH. Time-synchronized measurements of blade strain, inflow, thrust, rotational speed, and electrical output were obtained to characterize blade loading under various conditions. The blade strain was examined to assess the dynamic loading and conduct a fatigue analysis on the device.

blade strain↗
DOE OSTI2022

Verification and Validation of Model-Scale Turbine Performance and Control Strategies for the IEA Wind 15 MW Reference Wind Turbine

To enable the fast growth of the floating offshore wind industry, simulation models must be validated with experimental data. Floating wind model-scale experiments in wind–wave facilities have been performed over the last two decades with varying levels of fidelity and limitations. However, the turbine controls in these experiments have considered only limited control strategies and implementations. To allow for control co-design, this research focuses on implementing and experimentally validating more advanced turbine control actions and strategies in a wind–wave basin for a 1:70-scale model of the International Energy Agency’s wind 15 MW reference wind turbine. The control strategies analyzed include torque control, collective pitch control, and transition region control (setpoint smoothing). Our experimental and numerical results include the effects of varying rotor speeds, blade pitches, and wind environments on the turbine thrust and torque. Numerical models from three different software tools are presented and compared to the experimental results. Their ability to effectively represent the aero-dynamic response of the wind turbine to the control actions is successfully validated. Finally, turbine controller tuning parameters based on the derivatives of thrust and torque are derived to allow for improved offshore wind turbine dynamics and to validate the ability of modeling tools to model the dynamics of floating offshore wind turbines with control co-design.

17 WIND ENERGY↗
DOE OSTI2019

Sensitivity analysis of the effect of wind characteristics and turbine properties on wind turbine loads

Proper wind turbine design relies on the ability to accurately predict ultimate and fatigue loads of turbines. The load analysis process requires precise knowledge of the expected wind-inflow conditions as well as turbine structural and aerodynamic properties. However, uncertainty in most parameters is inevitable. It is therefore important to understand the impact such uncertainties have on the resulting loads. The goal of this work is to assess which input parameters have the greatest influence on turbine power, fatigue loads, and ultimate loads during normal turbine operation. An elementary effects sensitivity analysis is performed to identify the most sensitive parameters. Separate case studies are performed on (1) wind-inflow conditions and (2) turbine structural and aerodynamic properties, both cases using the National Renewable Energy Laboratory 5 MW baseline wind turbine. The Veers model was used to generate synthetic International Electrotechnical Commission (IEC) Kaimal turbulence spectrum inflow. The focus is on individual parameter sensitivity, though interactions between parameters are considered. The results of this work show that for wind-inflow conditions, turbulence in the primary wind direction and shear are the most sensitive parameters for turbine loads, which is expected. Secondary parameters of importance are identified as veer, u -direction integral length, and u components of the IEC coherence model, as well as the exponent. For the turbine properties, the most sensitive parameters are yaw misalignment and outboard lift coefficient distribution; secondary parameters of importance are inboard lift distribution, blade-twist distribution, and blade mass imbalance. This information can be used to help establish uncertainty bars around the predictions of engineering models during validation efforts, and provide insight to probabilistic design methods and site-suitability analyses.

17 WIND ENERGY↗
DOE OSTI2022

Comparing wind turbine aeroelastic response predictions for turbines with increasingly flexible blades

Highly flexible blades are becoming more prevalent designs as a potential solution to the transportation challenges associated with large-scale wind turbine rotors. However, there is currently no quantitative definition of “highly flexible” blades. To further develop turbines with highly flexible blades, a precise definition of the term and accurate simulations of turbines with such blades are required. Assumptions made in the traditional aerodynamic model, Blade Element Momentum (BEM) theory, are violated in turbines with flexible blades. However, Free Vortex Wake (FVW) methods can more accurately model these turbine designs. Though more computationally expensive than BEM, FVW methods are still computationally tractable for use in iterative turbine design. The purpose of this work was to determine the blade flexibility at which BEM and FVW methods begin to produce diverging aeroelastic response results. This was accomplished by simulating the BAR-DRC reference turbine with increasingly flexible blades in a range of steady, uniform inflow conditions using OpenFAST, the National Renewable Energy Laboratory’s physics-based turbine engineering tool. Blade-tip deflections confirmed that BEM and FVW results diverge as blade flexibility increases. For the 212 m rotor diameter turbine used in this study, the two methods largely agreed for smaller blade deflections. But their results differed by an average of 5% when the out-of-plane blade-tip deflections exceeded 5% of the blade length and in-plane blade-tip deflections exceeded 1.25% of the blade length, with percent differences approaching 25% at the largest deflections.

17 WIND ENERGY↗
DOE OSTI2019

Market Assessment for Hydropower Turbine Design Tools Using Integrated Datasets of Dams, Turbines, Owners, and Fish

A Department of Energy funded project titled Biologically Based Design and Evaluation of Hydropower Turbines (BioDE) has developed modeling tools and data that are intended to inform the design and installation of more environmentally friendly hydropower turbines. A market assessment was conducted to identify prospective users of these products within the hydropower industry and regulatory community. The market assessment included the development of a dataset of hydropower turbines and their defining characteristics (both physical and biological) for the purpose of refining program outreach and marketing of BioDE tools and data. A specific objective of the analysis was to identify hydropower owners and operators whose turbines were likely candidates for refurbishing or replacement because of senescence or re-licensing. This report describes a dataset that combines turbine properties, licensing status, fish resources, and ownership information on nearly 5,500 turbines at nearly 2,200 hydropower projects throughout the United States. The data analysis categorizes turbines by design type, geographic region, owner, age, license expiration, fish species presence, and regulatory authority. The ultimate result is the identification of the federal and non-federal owners with the most turbines of various types and the most turbines that have the potential to interact with fish species of concern.

13 HYDRO ENERGY↗
DOE OSTI2021

Gaining Insights in Loading Events for Wind Turbine Drivetrain Prognostics

Wind energy is one of the largest sources of renewable energy in the world. To further reduce the operations and maintenance (O&M) costs of wind farms, it is essential to be able to accurately pinpoint the root causes of different failure modes of interest. An example of such a failure mode that is not yet fully understood is white etching cracks (WEC). This can cause the bearing lifetime to be reduced to 5–10% of its design value. Multiple hypotheses are available in literature concerning its cause. To be able to validate or disprove these hypotheses, it is essential to have historic high-frequency measurement data (e.g., load and vibration levels) available. In time, this will allow linking to the history of the turbine operating data with failure data. This paper discusses the dynamic loading on the turbine during certain events (e.g., emergency stops, run-ups, and during normal operating conditions). By combining the number of specific events that each turbine has seen with the severity of each event, it becomes possible to assess which turbines are most likely to show signs of damage.

49 EE - Wind and Water Power Program - Wind (EE-4W↗
DOE OSTI2023

Impact of Detailed Parameter Modeling of Open-Cycle Gas Turbines on Production Cost Simulation: Preprint

Flexible resources are increasingly important as variable renewable energy deployment in the power system increases. Although many systems are transitioning away from fossil fuels, open-cycle gas turbines are likely to play an important balancing role for some time, thus requiring accurate modeling of their operational parameters. This paper explores the impact of detailed representation of three operational parameters - start- up costs, run-up rates, and forced outage rates - in the production cost model of a system as it adopts higher levels of wind and solar. Using PLEXOS simulations of the NREL-118 bus test system, the study examines how more detailed parameter modeling affects outcomes such as the number of start-ups and shutdowns, ramping and total generation costs for open-cycle gas turbines, as renewable energy levels increase. The results suggest the value of detailed parameter modeling and continued research on combustion turbines' ability to provide flexibility.

economic dispatch↗
DOE OSTI2020

Tuning of Nacelle Feedback Gains for Floating Wind Turbine Controllers Using a Two-DOF Model

Designing a collective blade pitch controller for floating offshore wind turbines (FOWTs) poses unique challenges due to the interaction of the controller with the dynamics of the platform. The controller must also handle the competing objectives of power production performance and fatigue load management. Existing solutions either detune the controller with the result of slowed response, make use of complicated tuning methods, or incorporate a nacelle velocity feedback gain. With the goal of developing a simple control tuning method for the general FOWT researcher that is easily extensible to a wide array of turbine and hull configurations, this last idea is built upon by proposing a simple tuning strategy for the feedback gain. This strategy uses a two degree-of-freedom (DoF) turbine model that considers tower-top fore-aft and rotor angular displacements. For evaluation, the nacelle velocity term is added to an existing gain scheduled proportional-integral controller as a proportional gain. The modified controller is then compared to baseline land-based and detuned controllers on an example system for several load cases. First-pass results are favorable, demonstrating how researchers can use the proposed tuning method to efficiently schedule gains for adequate controller performance as they investigate new FOWT configurations.

49 EE - Wind and Water Power Program - Wind (EE-4W↗
DOE OSTI2019

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↗
DOE OSTI2022

Tidal Turbine Test, Downeast Turbines, July 12, 2021

Downeast Turbines tested a tidal turbine prototype with novel rotor/channel system and lateral effluent discharge apparatus (LEDA), during five days of testing in the flume at Alden Lab. Three days of testing (July 12-14, 2021) focused on turbine power metrics of torque and rpm, which were low, and then two days of follow-up testing (July 27-28, 2021) focused on LEDA performance metrics of pressure differential and rates of volumetric flow, with encouraging results. Next step is to to characterize, and even optimize, configurations of the LEDA, using 3D-CFD as a helpful tool, to refine its shape and explore its limits of performance as a means of effluent discharge that augments performance of an instream turbine. An improved configuration of the LEDA will be re-combined with the rotor/channel system of the turbine prototype, and ultimately, the rotor will be re-sized (enlarged), to better match the LEDA's performance capabilities in drawing through a rate of volumetric flow. This submission is Downeast Turbines' Post Access Report for the test event. It includes the files described here (next below), and several reference links. "Downeast TEAMER-Post-Access-Report...docx" is a document file containing the report. "Appendices A, B, and C" are included in this file, and so are "Figures #1-7." "Appendix D - Test Data Workbooks.zip" is an archive file containing all post access data (raw data tables, calculating tables, and graphs), presented in fourteen Excel workbooks as described in the report. "Appendix E - Post Access Figures.zip" is an archive file containing "Figures #8-52," of the report.

16 TIDAL AND WAVE POWER↗
DOE OSTI2023

Design, Manufacture, and Testing of an Open-Source Benchmark Composite Hydrokinetic Turbine Blade: Preprint

In a trend toward clean energy alternatives, recent years have seen great strides in the marine energy space. Consequently, there is a pressing need for the design, development, and validation of novel energy harvesting technologies such as hydrokinetic devices, which capture kinetic energy from waves, tides, and currents. However, these devices span numerous concepts and designs that often lack solid benchmark research that can be freely referenced throughout their development. This work focuses on the design process of an open-source composite hydrokinetic turbine blade for a three-bladed marine turbine rotor assembly with a diameter of 2.5 m. The proposed blade consists of two structural composite skins that are bonded with an adhesive and filled with a foam core. This study also explores and contrasts the efficiency and resolution of low-fidelity rapid design methodologies and comprehensive high-fidelity approaches in the context of blade design, modeling, and analysis efforts, a key objective in this research. Blade hydrodynamic loads were modeled and applied to finite-element blade models to study deformations and potential failure. Ongoing and upcoming efforts will result in blade manufacture and structural testing at the National Renewable Energy Laboratory. In future work, multiple blades will be deployed at the Living Bridge site at the University of New Hampshire and will be compared to rigid aluminum blades of the same geometry, developed by Sandia National Laboratories. Ultimately, this research will lay foundational groundwork for researchers and manufacturers, establishing a baseline composite blade design that will serve as a benchmark in the development of future hydrokinetic turbine blades.

blade design↗
DOE OSTI2022

Data-driven wind turbine wake modeling via probabilistic machine learning

Wind farm design primarily depends on the variability of the wind turbine wake flows to the atmospheric wind conditions and the interaction between wakes. Physics-based models that capture the wake flow field with high-fidelity are computationally very expensive to perform layout optimization of wind farms, and, thus, data-driven reduced-order models can represent an efficient alternative for simulating wind farms. In this work, we use real-world light detection and ranging (LiDAR) measurements of wind-turbine wakes to construct predictive surrogate models using machine learning. Specifically, we first demonstrate the use of deep autoencoders to find a low-dimensional latent space that gives a computationally tractable approximation of the wake LiDAR measurements. Then, we learn the mapping between the parameter space and the (latent space) wake flow fields using a deep neural network. Additionally, we also demonstrate the use of a probabilistic machine learning technique, namely, Gaussian process modeling, to learn the parameter-space-latent-space mapping in addition to the epistemic and aleatoric uncertainty in the data. Finally, to cope with training large datasets, we demonstrate the use of variational Gaussian process models that provide a tractable alternative to the conventional Gaussian process models for large datasets. Furthermore, we introduce the use of active learning to adaptively build and improve a conventional Gaussian process model predictive capability. Overall, we find that our approach provides accurate approximations of the wind-turbine wake flow field that can be queried at an orders-of-magnitude cheaper cost than those generated with high-fidelity physics-based simulations.

Deep neural networks↗
DOE OSTI2024

Online Learning of Effective Turbine Wind Speed in Wind Farms

To develop better wind farm controllers that can meet more complex objectives, methods of modeling the wind turbine wakes at low computational expense are needed. Gaussian process (GP) regression offers a computationally inexpensive framework for learning complex functions from noisy measurements with very few datapoints. In this work, an online learning approach is presented to learn the rotor-averaged wind velocity at downstream wind turbines with GPs, using the available datastream of wind field measurements and wind turbine control set-points. This framework can readily be integrated into model-based controls methods because the model a) is updated online at low computational expense, b) assumes a mathematically favorable Gaussian form, and c) explicitly quantifies the stochastic nature of the wake field so that the trade-off between exploration and exploitation, and the uncertainty in the prediction, can be utilized. We show that a GP-learned model can match true values with errors within 0.5% on average, with as few as 5 training data points.

Gaussian process↗
DOE OSTI2021

Integration of Storage in the DC Link of a Full Converter-Based Distributed Wind Turbine

Energy storage is known to support the dispatchability of variable renewable resources. In this paper, we model a battery energy storage system (BESS) integrated with the DC link of a Type IV full converter-based wind turbine and the necessary controls to achieve efficient dispatch. To support the validation of control methodologies, we build a detailed model of a Type IV research wind turbine at the National Renewable Energy Laboratory (NREL), the Controls Advanced Research Turbine (CART 3), and we integrated a lithium-ion BESS model in grid-following mode into the model. The simulation results illustrate the sizing and control of the DC link-integrated BESS for a given variable wind resource and varying dispatch strategies (i.e., under constant, uncertain, and ramping wind scenarios). The integrated storage can smooth variabilities in distributed wind output, hedge against uncertainties, provide the ramping capability, as well as support stability under voltage and frequency transients. All of these have been illustrated in MATLAB/Simulink.

DC-link voltage↗