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At least 55 records · Page 3

Torsional Vibration in the National Wind Technology Center’s 2.5-Megawatt Dynamometer

This report documents the torsional drivetrain dynamics of the NWTC's 2.5-megawatt dynamometer as identified experimentally and as calculated using lumped parameter models using known inertia and stiffness parameters. The report is presented in two parts beginning with the identification of the primary torsional modes followed by the investigation of approaches to damp the torsional vibrations. The key mechanical parameters for the lumped parameter models and justification for the element grouping used in the derivation of the torsional modes are presented. The sensitivities of the torsional modes to different test article properties are discussed. The oscillations observed from the low-speed and generator torque measurements were used to identify the extent of damping inherently achieved through active and passive compensation techniques. A simplified Simulink model of the dynamometer test article integrating the electro-mechanical power conversion and control features was established to emulate the torque behavior that was observed during testing. The torque response in the high-speed, low-speed, and generator shafts were tested and validated against experimental measurements involving step changes in load with the dynamometer operating under speed-regulation mode. The Simulink model serves as a ready reference to identify the torque sensitivities to various system parameters and to explore opportunities to improve torsional damping under different conditions.

17 WIND ENERGY↗

Bat Acoustical Surveys at the National Renewable Energy Laboratory, National Wind Technology Center: July 2010-November 2010

An acoustical bat use survey was conducted at the NWTC from July 6, 2010 to November 7, 2010, using a passive acoustical method with AnaBat Systems Bat Detectors (Titley Electronics). The purpose of this survey was to obtain information about use by bats within the Project area. All data were collected from one bat detector. Bat activity was determined by the number of bat passes (number of echolocation calls recorded with = 2 chirps) per detector night. Species composition, temporal distribution (by month), and peak activity levels were analyzed. A total of 12,425 bat passes was recorded during the survey period for an index of activity of 99.40 bat passes per detector night. Of the 12,425 total bat passes, 8,772 passes could be identified to species (70.18 identified bat passes per detector night). Species identified included big brown bat, eastern red bat, fringed myotis, hoary bat, silver-haired bat, and Myotis bat group (which may include western small-footed myotis, western long-eared myotis, little brown myotis, and long-legged myotis). Most bats were detected in July (3,952 total bat passes) and August (5,058 total bat passes). The Myotis bat group was most the most frequently detected (4,373 identified bat passes). There were no peaks of activity during the monitoring period, but rather constant fluctuation. No Federally- or state-listed threatened, endangered, or candidate species or species of special concern were identified during surveys.

54 ENVIRONMENTAL SCIENCES↗

Blade Testing Trends (Presentation)

As an invited guest speaker, Michael Desmond presented on NREL's NWTC structural testing methods and capabilities at the 2014 Sandia Blade Workshop held on August 26-28, 2014 in Albuquerque, NM. Although dynamometer and field testing capabilities were mentioned, the presentation focused primarily on wind turbine blade testing, including descriptions and capabilities for accredited certification testing, historical methodology and technology deployment, and current research and development activities.

17 WIND ENERGY↗

NREL’s Controllable Grid Interface Saves Time and Resources, Improves Reliability of Renewable Energy Technologies; NREL (National Renewable Energy Laboratory)

The National Renewable Energy Laboratory's (NREL) controllable grid interface (CGI) test system at the National Wind Technology Center (NWTC) is one of two user facilities at NREL capable of testing and analyzing the integration of megawatt-scale renewable energy systems. The CGI specializes in testing of multimegawatt-scale wind and photovoltaic (PV) technologies as well as energy storage devices, transformers, control and protection equipment at medium-voltage levels, allowing the determination of the grid impacts of the tested technology.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Accomplishments and Year-End Performance Report; Wind Energy Program: Fiscal Year 2021

The National Wind Technology Center (NWTC), located at the U.S. Department of Energy's (DOE's) National Renewable Energy Laboratory (NREL) Flatirons Campus, has been a driving force in advancing wind energy technology research worldwide since its designation as a DOE national research center in 1992. Enabled by the Flatirons Campus's world-class facilities, scientists, engineers, analysts, and researchers are pushing the frontiers of science to pursue wind energy innovation. In Fiscal Year (FY) 2021, NREL continued to provide the technical expertise, research capabilities, and industry understanding to support DOE's ambitious climate action and research goals by advancing technology, addressing market and deployment barriers, and driving down costs with more efficient, reliable, and predictable wind energy systems. One of several highlights, NREL received an R&D 100 Special Recognition Award for its Thermoplastic Resin System for Wind Turbine Blades. This breakthrough in the wind turbine manufacturing process will enable the production of recyclable blades that are stronger, longer, and less expensive, while increasing energy capture, decreasing energy and transportation costs, and increasing blade reliability. In a year when the entire U.S. economy struggled to address workforce gaps, an NREL study compared wind industry needs, training programs, and hiring practices with perspectives from students and recent college graduates. Researchers hope that, by pinpointing areas of disconnect, the expectations of employers who have difficulty filling entry-level jobs can better align with the preparation of the potential applicants who find it hard to break into the field. The lab also made numerous new data and modeling resources available in FY 2021. Recent NREL releases include a modeling tool for predicting the power performance and structural loads of wind turbines within a wind farm (FAST.Farm), a computational framework for modeling golden eagle behavior near wind farms, and 20 years of offshore wind data. Updates were also made to the widely used Wind Plant Integrated Systems Design and Engineering Model (WISDEM), which couples engineering and cost models to examine system-level trade-offs. Now, bolstered by a renewed national commitment to tackle climate change and revitalize the U.S. economy through increased investment in clean energy - particularly in offshore wind energy - NREL stands poised to lead the way to a sustainable future that powers the United States with significant levels of reliable, low-cost, accessible wind energy. This report provides an overview of the achievements NREL made on behalf of DOE's Wind Energy Technologies Office (WETO) and other partners during FY 2021 (between Oct. 1, 2020, and Sept. 30, 2021).

Flatirons Campus↗

Multi-Megawatt-Scale Power-Hardware-in-the-Loop Interface for Testing Ancillary Grid Services by Converter-Coupled Generation

Power-hardware-in-the-loop (PHIL) is a simulation tool that can support electrical systems engineers in the development and experimental validation of novel, advanced control schemes that ensure the robustness and resiliency of electrical grids that have high penetrations of low-inertia variable renewable resources. With PHIL, the impact of the device under test on a generation or distribution system can be analyzed using a real-time simulator (RTS). PHIL allows for the interconnection of the RTS with a 7 megavolt ampere (MVA) power amplifier to test multi-megawatt renewable assets available at the National Wind Technology Center (NWTC). This paper addresses issues related to the development of a PHIL interface that allows testing hardware devices at actual scale. In particular, the novel PHIL interface algorithm and high-speed digital interface, which minimize the critical loop delay, are discussed.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Distributed Real-Time Simulation and its Applications to Wind Energy Research

This paper presents a novel approach - distributed Real-Time Simulations (RTS) - for innovative wind energy and grid integration research. Distributed RTS is performed with Digital Real-Time Simulators (DRTS) in different geographical locations and connected over the Internet. Geographically distributed RTS supports - higher computation capability for RTS, leveraging distributed assets, novel testing techniques and hybridized smart grid testbeds. This paper discusses some of the basic aspects of distributed RTS with the communication delay as a probabilistic variable. To leverage hardware resources and enable flexible collaboration of national laboratories, the distributed RTS connection between the simulators at Idaho National Laboratory (INL) and National Wind Test Center (NWTC) at National Renewable Energy Laboratory (NREL) is established. The main objective of this distributed lab setup is to perform wind turbine characterization and assessment of wind integration studies in large scale grids. Several systematic steps based on integrating models are carried out to assess the impact of communication delay on distributed RTS.

17 WIND ENERGY↗

WISDEM® (Wind-Plant Integrated System Design and Engineering Model) [SWR-14-05]

The Wind-Plant Integrated System Design and Engineering Model (WISDEM®) is a set of models for assessing overall wind plant cost of energy (COE). The models use wind turbine and plant cost and energy production as well as financial models to estimate COE and other wind plant system attributes. WISDEM® is accessed through Python, is built using OpenMDAO, https://openmdao.org/, and uses several sub-models that are also implemented within OpenMDAO. These sub-models can be used independently but they are required to use the overall WISDEM® turbine design capability. Please install all of the pre-requisites prior to installing WISDEM® by following the directions below. For additional information about the NWTC effort in systems engineering that supports WISDEM® development, please visit the official NREL systems engineering for wind energy website. https://www.nlr.gov/wind/systems-engineering

Ning, S.Andrew↗

KiteFAST

KiteFAST is a simulator for airborne wind energy systems based on NREL's OpenFAST whole turbine simulator. KiteFAST is a multi-physics engineering tool for modeling the coupled aero-servo-elastic dynamics of airborne wind energy systems i.e. a wind-energy kite. The engineering model is like NREL's OpenFAST tool for land-based or offshore horizontal-axis wind turbines atop towers, in that KiteFAST models the important physical phenomena and system couplings, including the wind/aerodynamic excitation and full-system dynamics response (fuselage, wings, tail, stabilizers, pylons, nacelles, rotors, tether, ground station, control surfaces, and controller) under both normal (for fatigue) and extreme (for ultimate) loading conditions. The configuration of the wind-energy kite is assumed to have one fuselage; two wings (starboard, port) attached to the fuselage; one vertical stabilizer attached the fuselage; two horizontal stabilizers (starboard, port) attached to the vertical stabilizer; one or more pylons per wing, each with two rotors (top, bottom); one ground-station-fixed tether with a bridal connection to the wings, and nominal circular motion of the energy kite in the port (left) direction. The general configuration of the control surfaces assumes one or more flaps per wing, two rudders on the vertical stabilizer, two elevators per horizontal stabilizer, and rotors with variable speed and rotor-collective blade pitch. KiteFAST was developed from (1) the existing MBDyn open-source multi-body dynamics code; (2) the existing/modified OpenFAST modules NWTC Subroutine Library, AirfoilInfo, InflowWind, MoorDyn, and TurbSim; and (3) new source code for a) generating MBDyn models of the energy kite (KiteMBDyn Preprocessor), b) computing quasi-steady energy-kite aerodynamics (KiteAeroDyn, KiteAeroDyn Driver, KiteVSM, ActuatorDisk), c) interfacing an energy-kite controller, and d) coupling the various KiteFAST modules together (KiteFASTMBD).

Jonkman, Jason↗

WISDEM® v3.4.1(Wind Plant Integrated System Design and Engineering Model) [SWR-14-05]

The Wind Plant Integrated System Design and Engineering Model (WISDEM®) is a set of models for assessing overall wind plant cost of energy (COE). The models use wind turbine and plant cost and energy production as well as financial models to estimate COE and other wind plant system attributes. WISDEM® is accessed through Python, is built using OpenMDAO, and uses several sub-models that are also implemented within OpenMDAO. These sub-models can be used independently but they are required to use the overall WISDEM® turbine design capability. Please install all of the pre-requisites prior to installing WISDEM® by following the directions below. For additional information about the NWTC effort in systems engineering that supports WISDEM® development, please visit the official NREL systems engineering for wind energy website. https://www.nlr.gov/wind/systems-engineering

Dykes, Katherine↗

WISDEM® v3.15.2 2024 (Wind-Plant Integrated System Design and Engineering Model) [SWR-14-05]

The Wind-Plant Integrated System Design and Engineering Model (WISDEM®) is a set of models for assessing overall wind plant cost of energy (COE). The models use wind turbine and plant cost and energy production as well as financial models to estimate COE and other wind plant system attributes. WISDEM® is accessed through Python, is built using OpenMDAO, and uses several sub-models that are also implemented within OpenMDAO. These sub-models can be used independently but they are required to use the overall WISDEM® turbine design capability. Please install all of the pre-requisites prior to installing WISDEM® by following the directions below. For additional information about the NWTC effort in systems engineering that supports WISDEM® development, please visit the official NREL systems engineering for wind energy website. https://www.nrel.gov/wind/systems-engineering.html

Dykes, Katherine↗

Mechanical Loads Test Report for the U.S. Department of Energy 1.5-Megawatt Wind Turbine

The objective of the test was to obtain a baseline characterization of the mechanical loads of the DOE 1.5 wind turbine located at NREL. The test was conducted in accordance with the International Electrotechnical Commission (IEC) Technical Specification, IEC 61400-13 Wind Turbine Generator Systems – Part 13: Measurement of mechanical loads; First Edition 2001-06 [1]. The National Wind Technology Center (NWTC) at NREL conducted this test in accordance with its quality system procedures so that the final test report meets the full requirements of its accreditation by the American Association for Laboratory Accreditation (A2LA). NREL’s quality system requires that all applicable requirements specified by A2LA and International Standards Organization/IEC 17025 be met or to note any exceptions in the test report.

1.5 MW↗

Power Performance Test Report for the U.S. Department of Energy 1.5-Megawatt Wind Turbine

The U.S. Department of Energy (DOE) acquired and installed a 1.5-megawatt (MW) wind turbine at the National Wind Technology Center (NWTC) at the National Renewable Energy Laboratory (NREL). This turbine (hereafter referred to as the DOE 1.5) is envisioned to become an integral part of the research initiatives for the DOE Wind Program, such as Atmosphere to Electrons (A2e). A2e is a multiyear DOE research initiative targeting significant reductions in the cost of wind energy through an improved understanding of the complex physics governing wind flow into and through wind farms. For more information, visit http://energy.gov/eere/wind/atmosphere-electrons. To validate new and existing high-fidelity simulations, A2e must deploy several experimental measurement campaigns across different scales. Proposed experiments include wind tunnel tests, scaled field tests, and large field measurement campaigns at operating wind plants. Data of interest includes long-term atmospheric data sets, wind plant inflow, intra-wind plant flows (e.g., wakes), and rotor loads measurements. It is expected that new, high-fidelity instrumentation will be required to successfully collect data at the resolutions required to validate the high-fidelity simulations.

17 WIND ENERGY↗

Gearbox Reliability Collaborative Phase 3 Gearbox 2 Test Report

Many gearboxes in wind turbines have not been achieving their expected design life [1]; they do, however, commonly meet or exceed the design criteria specified in current standards in the gear, bearing, and wind turbine industry as well as third-party certification criteria. The cost of gearbox replacements and rebuilds, as well as the downtime associated with these failures, has elevated the cost of wind energy. In 2006, the U.S. Department of Energy established the National Renewable Energy Laboratory (NREL) Gearbox Reliability Collaborative (GRC). Its key goal is to understand the root causes of premature gearbox failures and improve their reliability [2]. The GRC is examining a hypothesis that the gap between design-estimated and actual wind turbine gearbox reliability is caused by underestimation of loads, inaccurate design tools, the absence of critical elements in the design process, or insufficient testing. This test report describes the recent tests of GRC gearbox (GB) 2 in the National Wind Technology Center (NWTC) dynamometer and documents any modifications to the original test plan [3]. In this manner, it serves as a guide for interpreting the publicly released data sets with brief analyses to illustrate the data. Specific objectives of the test were to assess the effect of dynamic nontorque load (NTL) on the planetary section, generator misalignment on the highspeed shaft (HSS), and field representative conditions on the gearbox in general. Detailed analysis of those test objectives will be presented in subsequent publications.

17 WIND ENERGY↗

Economic and Performance Analysis of Gear Box Failures. Cooperative Research and Development Final Report, CRADA Number CRD-07-236

The National Renewable Energy Laboratory (NREL) in Golden, CO, USA is forming a collaborative within the wind energy industry to address reliability issues on wind turbines. The National Wind Technology Center (NWTC), leading the collaborative effort, will allow gearbox manufacturers, bearing manufacturers, wind turbine owner/operators, and wind turbine manufacturers to team up for joint projects that address specific issues regarding design and reliability of wind turbine gearboxes. The primary means of investigation will be through full scale testing and analysis of actual gearboxes, both in the field and in the NREL 2.5 MW dynamometer test facility. These teams would contribute resources into a campaign that is intended to serve the mutual interests of a majority of the wind and gearbox industry stakeholders in addition to the specific project team objectives. that address specific issues regarding design and reliability of wind turbine gearboxes. The primary means of investigation will be through full scale testing and analysis of actual gearboxes, both in the field and in the NREL 2.5 MW dynamometer test facility. These teams would contribute resources into a campaign that is intended to serve the mutual interests of a majority of the wind and gearbox industry stakeholders in addition to the specific project team objectives.

17 WIND ENERGY↗

NREL and DONG Energy Collaboration for Grid Simulator Controls and Testing: Cooperative Research and Development Final Report, CRADA Number CRD-13-527

The National Renewable Energy Laboratory (NREL) and DONG Energy are interested in collaborating for the development of control algorithms, modeling, and grid simulator testing of wind turbine generator systems involving NWTC's advanced Controllable Grid Interface (CGI). NREL and DONG Energy will work together to develop control algorithms, models, test methods, and protocols involving NREL's CGI, as well as appropriate data acquisition systems for grid simulation testing. The CRADA also includes work on joint publication of results achieved from modeling and testing efforts. Further, DONG Energy will send staff to NREL on a long-term basis for collaborative work including modeling and testing. NREL will send staff to DONG Energy on a short-term basis to visit wind power sites and participate in meetings relevant to this collaborative effort. DOE has provided NREL with over 10 years of support in developing custom facilities and capabilities to enable testing of full-scale integrated wind turbine drivetrain systems in accordance with the needs of the US wind industry. NREL currently operates a 2.5MW dynamometer and is in the processes of commissioning a 5MW dynamometer and a grid simulator (referred to as a 'Controllable Grid Interface' or CGI). DONG Energy is the market leader in offshore wind power development, with currently over 1 GW of on- and offshore wind power in operation, and 1.3 GW under construction. DONG Energy has on-going R&D projects involving high voltage DC (HVDC) transmission.

17 WIND ENERGY↗

Distributed Wind Resource Assessment: State of the Industry

In support of the U.S. Department of Energy (DOE) Wind and Water Power Technologies Office (WWPTO) goals, researchers from DOE's National Renewable Energy Laboratory (NREL), National Wind Technology Center (NWTC) are investigating the Distributed Wind Resource Assessment (DWRA) process, which includes pre-construction energy estimation as well as turbine site suitability assessment. DWRA can have a direct impact on the Wind Program goals of maximizing stakeholder confidence in turbine performance and safety as well as reducing the levelized cost of energy (LCOE). One of the major components of the LCOE equation is annual energy production. DWRA improvements can maximize the annual energy production, thereby lowering the overall LCOE and improving stakeholder confidence in the distributed wind technology sector by providing more accurate predictions of power production. Over the long term, one of the most significant benefits of a more defined DWRA process could be new turbine designs, tuned to site-specific characteristics that will help the distributed wind industry follow a similar trajectory to the low-wind-speed designs in the utility-scale industry sector. By understanding the wind resource better, the industry could install larger rotors, capture more energy, and as a result, increase deployment while lowering the LCOE. a direct impact on the Wind Program goals of maximizing stakeholder confidence in turbine performance and safety as well as reducing the levelized cost of energy (LCOE). One of the major components of the LCOE equation is annual energy production. DWRA improvements can maximize the annual energy production, thereby lowering the overall LCOE and improving stakeholder confidence in the distributed wind technology sector by providing more accurate predictions of power production. Over the long term, one of the most significant benefits of a more defined DWRA process could be new turbine designs, tuned to site-specific characteristics that will help the distributed wind industry follow a similar trajectory to the low-wind-speed designs in the utility-scale industry sector. By understanding the wind resource better, the industry could install larger rotors, capture more energy, and as a result, increase deployment while lowering the LCOE.

17 WIND ENERGY↗

An Integrated Approach To Offshore Wind Energy Assessment: Great Lakes 3D Wind Experiment

This grant supported fundamental research into the characterization of flow parameters of relevance to the wind energy industry focused on offshore and the coastal zone. A major focus of the project was application of the latest generation of remote sensing instrumentation and also integration of measurements and numerical modeling to optimize characterization of time-evolving atmospheric flow parameters in 3-D. Our research developed a new data-constrained Wind Atlas for the Great Lakes, and developed new insights into flow parameters in heterogeneous environments. Four experiments were conducted during the project: At a large operating onshore wind farm in May 2012; At the National Renewable Energy Laboratory National Wind Technology Center (NREL NWTC) during February 2013; At the shoreline of Lake Erie in May 2013; and At the Wind Energy Institute of Canada on Prince Edward Island in May 2015. The experiment we conducted in the coastal zone of Lake Erie indicated very complex flow fields and the frequent presence of upward momentum fluxes and resulting distortion of the wind speed profile at turbine relevant heights due to swells in the Great Lakes. Additionally, our data (and modeling) indicate the frequent presence of low level jets at 600 m height over the Lake and occasions when the wind speed profile across the rotor plane may be impacted by this phenomenon. Experimental data and modeling of the fourth experiment on Prince Edward Island showed that at 10-14 m escarpment adjacent to long-overseas fetch the zone of wind speed decrease before the terrain feature and the increase at (and slightly downwind of) the escarpment is ~3–5% at turbine hub-heights. Additionally, our measurements were used to improve methods to compute the uncertainty in lidar-derived flow properties and to optimize lidar-scanning strategies. For example, on the basis of the experimental data we collected plus those from one of our research partners we advanced a new methodology to estimate a priori the uncertainty in wind speed retrievals from arc scans based on site characteristics such as wind velocity, turbulence intensity and proposed scan geometry. Insights regarding use of remote sensing technologies deriving from project experiments were used to compile a best practice document http://doi.org/10.7298/X4QV3JGF for measuring wind speeds and turbulence offshore through in-situ and remote sensing technologies. A project-specific web-site was developed and is available at: http://www.geo.cornell.edu/eas/PeoplePlaces/Faculty/spryor/DoE_AIATOWEA/index.html

17 WIND ENERGY↗