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At least 307 records · Page 17

The de-correlation of westerly winds and westerly-wind stress over the Southern Ocean during the Last Glacial Maximum

This paper investigates the changes of the Southern Westerly Winds (SWW) and Southern Ocean (SO) upwelling between the Last Glacial Maximum (LGM) and preindustrial (PI) in the PMIP3/CMIP5 simulations, highlighting the role of the Antarctic sea ice in modulating the wind stress effect on the ocean. Particularly, a discrepancy may occur between the changes in SWW and westerly wind stress, caused primarily by an equatorward expansion of winter Antarctic sea ice that undermines the wind stress in driving the liquid ocean. Such discrepancy may reflect the LGM condition in reality, in view of that the model simulates this condition has most credible simulation of modern SWW and Antarctic sea ice. The effect of wind stress on the SO upwelling is further explored via the wind-induced Ekman pumping, which is reduced under the LGM condition in all models, in part by the sea-ice “capping” effect present in the models.

Antarctic sea ice↗

Benchmarking Anticipated Wind Project Lifetimes: Results from a Survey of U.S. Wind Industry Professionals

This paper draws on a survey of wind industry professionals to clarify trends in the expected useful life of land-based wind power plants in the United States. The expected useful life of a project affects expectations about its profitability, the timing of possible decommissioning or repowering, and its levelized costs. We find that most wind project developers, sponsors and long-term owners have increased project-life assumptions over time, from a typical term of ~20 years in the early 2000s to ~25 years by the mid-2010s and ~30 years more recently. Current assumptions range from 25 to 40 years, with an average of 29.6 years. The estimated average levelized cost of energy (LCOE) for new wind projects built in 2018 is $\$ $40.4/MWh (real 2018$\$ $), assuming a 20-year project life. With a 25-year useful life and no change in assumed operations and maintenance (O&M) expenditures or wind plant performance over time, LCOE declines by 10%, to $\$ $36.2/MWh, because capital costs are recovered over five additional years of production. At the now-common 30-year assumed life, levelized costs decrease another 7%, to $\$ $33.5/MWh (under the same unaltered assumptions about O&M and performance). Even longer assumed lifetimes lead to further (but diminishing) LCOE reductions—e.g., to $\$ $31.7/MWh and $\$ $30.3/MWh for 35- and 40-year lives, respectively. The data and trends presented here may inform assumptions used by electric system planners, modelers and analysts. The results may also provide useful benchmarks to the wind industry, helping developers and assets owners to compare their expectations with those of their peers.

17 WIND ENERGY↗

Nalu-Wind and OpenFAST: A high-fidelity modeling and simulation environment for wind energy. Milestone ECP-Q2-FY19

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 the culmination of several parallel development activities towards the goal of establishing a full-physics simulation capability for modeling wind turbines operating in turbulent atmospheric inflow conditions. The demonstration simulation performed in this milestone is the first step towards the "ground truth" simulation and includes the following components: neutral atmospheric boundary layer inflow conditions generated using a precursor simulation, a hybrid RANS/LES simulation of the wall-resolved turbine geometry, hybridization of the turbulence equations using a blending function approach to transition from the atmospheric scales to the blade boundary layer scales near the turbine, fluid-structure interaction (FSI) that accounts for the complete set of blade deformations (bending, twisting and pitch motion, yaw and tower displacements) by coupling to a comprehensive turbine dynamics code (OpenFAST). The use of overset mesh methodology for the simulations in this milestone presents a significant deviation from the previous efforts where a sliding mesh approach was employed to model the rotation of the turbine blades. The choice of overset meshes was motivated by the need to handle arbitrarily large deformations of the blade and to allow for blade pitching in the presence of a controller and the ease of mesh generation compared to the sliding mesh approach. FSI and the new timestep algorithm used in the simulations were developed in partnership with the A2e High-Fidelity Modeling project. The individual physics components were verified and validated (V%V) through extensive code-to-code comparisons and with experiments where possible. The detailed V&V efforts provide confidence in the final simulation where these physics models were combined together even though no detailed experimental data is available to perform validation of the final configuration. Taken together, this milestone successfully demonstrated the most advanced simulation to date that has been performed with Nalu-Wind.

17 WIND ENERGY↗

Conflict Resolution for Wind-Optimal Aircraft Trajectories in North Atlantic Oceanic Airspace with Wind Uncertainties

Air traffic in the North Atlantic oceanic airspace (NAT) experiences very strong winds caused by jet streams. Flying wind-optimal trajectories increases individual flight efficiency, which is advantageous when operating in the NAT. However, as the NAT is highly congested during peak hours, a large number of potential conflicts between flights are detected for the sets of wind-optimal trajectories. Conflict resolution performed at the strategic level of flight planning can significantly reduce the airspace congestion. However, being completed far in advance, strategic planning can only use predicted environmental conditions that may significantly differ from the real conditions experienced further by aircraft. The forecast uncertainties result in uncertainties in conflict prediction, and thus, conflict resolution becomes less efficient. This work considers wind uncertainties in order to improve the robustness of conflict resolution in the NAT. First, the influence of wind uncertainties on conflict prediction is investigated. Then, conflict resolution methods accounting for wind uncertainties are proposed.

wind uncertainties↗

Investigating Core Gaps and the Development of Subcomponent Validation Methods for Wind Turbine Blades: Preprint

Core gaps are a common manufacturing defect observed in wind blade composite sandwich constructions, which occur when sheets of core material are not properly butted up against each other in the mold. The aim of this study was to characterize core gaps in composite sandwich constructions at the coupon scale. This was to gain an initial understanding of the defect before developing appropriate methodologies for more complex subcomponents as part of a much broader wind blade structural validation and damage tolerance program. Long beam flexure in 4-point-bending was chosen as the most appropriate loading scenario. Beam specimens were characterized with and without 10 mm core gaps in fiberglass/balsa sandwich beams. The core gaps were characterized with two separate resin systems; a Hexion epoxy and Arkema's Elium resins system (a novel, infusible thermoplastic). Results showed that the Elium beams without the core gaps were had a 15% lower static strength than their epoxy counterparts. The introduction of the core gap to the epoxy beams reduced their static strength by 35%. The Elium beams, however, exhibited negligible strength reductions with the inclusion of the core gap. Overall, this characterization study provided pertinent information with regards to core gaps as a manufacturing defect to allow for continued development of damage tolerance and subcomponent validation methodologies with the inclusion of manufacturing defects.

17 WIND ENERGY↗

Predicting wind farm operations with machine learning and the P2D‐RANS model: A case study for an AWAKEN site

Abstract The power performance and the wind velocity field of an onshore wind farm are predicted with machine learning models and the pseudo‐2D RANS model, then assessed against SCADA data. The wind farm under investigation is one of the sites involved with the American WAKE experimeNt (AWAKEN). The performed simulations enable predictions of the power capture at the farm and turbine levels while providing insights into the effects on power capture associated with wake interactions that operating upstream turbines induce, as well as the variability caused by atmospheric stability. The machine learning models show improved accuracy compared to the pseudo‐2D RANS model in the predictions of turbine power capture and farm power capture with roughly half the normalized error. The machine learning models also entail lower computational costs upon training. Further, the machine learning models provide predictions of the wind turbulence intensity at the turbine level for different wind and atmospheric conditions with very good accuracy, which is difficult to achieve through RANS modeling. Additionally, farm‐to‐farm interactions are noted, with adverse impacts on power predictions from both models.

17 WIND ENERGY↗

Final Report on the Creation of the Wind Integration National Dataset (WIND) Toolkit and API: October 1, 2013 - September 30, 2015

The primary objective of this work was to create a state-of-the-art national wind resource data set and to provide detailed wind plant output data for specific sites based on that data set. Corresponding retrospective wind forecasts were also included at all selected locations. The combined information from these activities was used to create the Wind Integration National Dataset (WIND), and an extraction tool was developed to allow web-based data access.

17 WIND ENERGY↗

Benchmarking U.S. Small Wind Costs with the Distributed Wind Taxonomy

The objective of this report is to benchmark costs for small wind projects installed in the United States using a distributed wind taxonomy. Consequently, this report is a starting point to help expand the U.S. distributed wind market by informing potential areas for small wind cost-reduction opportunities and providing a benchmark to track future small wind cost-reduction progress.

17 WIND ENERGY↗

Definition of the UMaine VolturnUS-S Reference Platform Developed for the IEA Wind 15-Megawatt Offshore Reference Wind Turbine

The following report defines the UMaine VolturnUS-S reference floating offshore wind turbine (FOWT) semi-submersible designed to support the IEA-15-240-RWT 15-megawatt (MW) reference turbine. The semi-submersible is a generic steel version of the UMaine patented concrete floating foundation technology developed by the US Department of Energy. This report serves as an addendum to the previously published report, NREL/TP-5000-75698 IEA Wind TCP Task 37: Definition of the IEA Wind 15-Megawatt Offshore Reference Wind Turbine, and provides details on a floating semi-submersible design developed to support the15MW reference wind turbine.

17 WIND ENERGY↗

Advanced Distributed Wind Turbine Controls Series: Part 4-Wind Energy in Microgrids – Microgrids, Infrastructure Resilience, and Advanced Controls Launchpad (MIRACL)

In recent years, the technical capabilities and requirements for distributed wind turbines to provide ancillary services beyond maximum energy production has increased. Ancillary services, leveraged through advanced wind turbine controls, can support grid stability, reliability, and resilience. In the context of a microgrid, wind turbines can provide ancillary services that are useful in both islanded and grid-connected modes, as demonstrated in previous parts of this report series. This report focuses on how wind turbines with advanced controls and power electronics can support the stability of the microgrid during transitions from grid-connected to island mode, and back. This report documents simulation results from a model of the National Renewable Energy Laboratory (NREL) Flatirons Campus containing NREL's 600-kilowatt Controls Advanced Research Turbine. Using this turbine, we demonstrate through desktop simulation how a wind turbine can support the voltage and frequency of a microgrid during transitions - from making planned transitions seamless to keeping all loads online during some unplanned transitions to supporting black start in the event of an open transition (blackout).

17 WIND ENERGY↗

Benchmarking U.S. Small Wind Costs with the Distributed Wind Taxonomy

The objective of this report is to benchmark costs for small wind projects installed in the United States using a distributed wind taxonomy. Consequently, this report is a starting point to help expand the U.S. distributed wind market by informing potential areas for small wind cost-reduction opportunities and providing a benchmark to track future small wind cost-reduction progress.

17 WIND ENERGY↗

Impacts of wind field characteristics and non-steady deterministic wind events on time-varying main-bearing loads

Abstract. This work considers the characteristics and drivers of the loads experienced by wind turbine main bearings. Simplified load response models of two different hub and main-bearing configurations are presented, representative of both inverting direct-drive and four-point-mounted geared drivetrains. The influences of deterministic wind field characteristics, such as wind speed, shear, yaw offset, and veer, on the bearing load patterns are then investigated for similarity scaled 5, 7.5, and 10 MW reference wind turbine models. Main-bearing load response in cases of deterministic gusts and extreme changes in wind direction are also considered for the 5 MW model. Perhaps surprisingly, veer is identified as an important driver of main-bearing load fluctuations. Upscaling results indicate that similar behaviour holds as turbines become larger, but with mean loads and load fluctuation levels increasing at least cubically with the turbine rotor radius. Strong links between turbine control and main-bearing load response are also observed.

17 WIND ENERGY↗

Wind Vision: Updating the DOE 20% Wind Energy by 2030 Report (Poster)

The 20% Wind Energy by 2030 report was developed as part of the Advanced Energy Initiative. Published in 2008, the report was largely based on information collected and analyzed in 2006. Much has changed since then, including shifts in technology, markets, and policy. The industry needs a new, clear, vision for wind power that is shared among stakeholders from the U.S. government, industry, academia, and NGO communities. At WINDPOWER 2013, the U.S. Department of Energy, in partnership with the American Wind Energy Association and the Wind Energy Foundation, launched a project to update the 20% report with new objectives. This conference poster outlines the elements of the new Wind Vision.

17 WIND ENERGY↗

Comparison of Mean and Dynamic Wake Characteristics between Research-Scale and Full-Scale Wind Turbines

Comprehensive utility-scale wake measurements from commercial wind plants are difficult to obtain. As a result, research in wind farm aerodynamics is often based on smaller-scale measurements and on numerical experiments. It is therefore crucial for the scientific community to understand how results compare across scales. In this work, three actuator-line large-eddy simulations are performed to investigate the sensitivity of mean and dynamic wake characteristics to changes in hub height (for the same turbine model) and in rotor size and properties (for a research-scale and a land-based-scale rotor at the same hub height). Results reveal that ground proximity has a large effect on wake expansion via turbulent transport of axial momentum and on the magnitude of lateral and vertical meandering. The rotor-size experiment suggests that wakes from different-scale turbines expand similarly when not limited by the ground, but that the meandering magnitude is not easily translatable across scales. Finally, the short-rotor wake recovers faster than the tall-rotor wake, but the far wakes of the different-sized rotors at the same absolute height are scalable.

17 WIND ENERGY↗

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↗