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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 73 records · Page 4

Bias Characterization, Vertical Interpolation, and Horizontal Interpolation for Distributed Wind Siting Using Mesoscale Wind Resource Estimates

Much like their counterparts in utility-scale wind energy, developers of industrial, small-scale and distributed wind turbine deployments need to understand and accurately characterize the wind resource to properly assess the power generation and financial ramifications during siting and planning. National Renewable Energy Laboratory’s WIND (Wind Integration National Dataset) Toolkit (WTK) provides a best-in-class wind resource dataset generated using the Weather Research and Forecasting (WRF) model. This dataset includes parameters such as the wind speed, wind direction, and temperature at various heights, plus atmospheric stability near the surface. This data is available at 2-km spatial resolution and five-minute temporal resolution across 7 years, from 2007 to 2013 through a publicly accessible API interface. The Tools Assessing Performance (TAP) project seeks to extend this dataset to allow long term resource estimates and leverage it to better equip distributed wind equipment manufacturers, owner-operators, and installation professionals with better tools for practical siting applications. In this report, we present the results from our investigation within the TAP project focused on characterization of bias in WTK-based wind speed estimates and evaluation of vertical and horizontal interpolation techniques. We discuss the tradeoffs between different techniques and their combinations, as well as describe the lower bounds we determine for the studied validation errors. While the specific estimates we present are specific to WTK and the validation dataset we have chosen for this investigation (NREL's Wind Resource Meteorological Database), the overall analysis and the studied techniques are general enough to be applied to a broader set of wind datasets, both simulation-based and observational.

17 WIND ENERGY↗

U.S. Department of Energy Competitiveness Improvement Project (CIP) 2024 Small Turbine Certification and/or Listing Awardee: NPS Solutions LLC

This fact sheet describes the 2024 Competitiveness Improvement Project (CIP) award received by NPS Solutions LLC for Small Turbine Certification and/or Listing. The U.S. Department of Energy's (DOE's) CIP awards cost-shared subcontracts and technical support to manufacturers of small and medium-sized wind turbines. Managed by NREL on behalf of DOE's Wind Energy Technologies Office, CIP helps advance wind energy as a cost-effective, distributed generation technology option.

17 WIND ENERGY↗

U.S. Department of Energy Competitiveness Improvement Project (CIP) 2024 Small Turbine Certification and Listing Awardee: Uprise Energy

This fact sheet describes the 2024 Competitiveness Improvement Project (CIP) award received by Uprise Energy for small turbine certification and listing. The U.S. Department of Energy's (DOE's) CIP awards cost-shared subcontracts and technical support to manufacturers of small and medium-sized wind turbines. Managed by NREL on behalf of DOE's Wind Energy Technologies Office, CIP helps advance wind energy as a cost-effective, distributed generation technology option.

17 WIND ENERGY↗

The effect of wind direction shear on turbine performance in a wind farm in central Iowa

Abstract. Numerous studies have shown that atmospheric conditions affect wind turbine performance; however, some findings have exposed conflicting results for different locations and diverse analysis methodologies. In this study, we explore how the change in wind direction with height (direction wind shear), a site-differing factor between conflicting studies, and speed shear affect wind turbine performance. We utilized lidar and turbine data collected from the 2013 Crop Wind Energy eXperiment (CWEX) project between June and September in a wind farm in north-central Iowa. Wind direction and speed shear were found to follow a diurnal cycle; however, they evolved differently with increasing wind speeds. Using a combination of speed and direction shear values, we found large direction and small speed shear to result in underperformance. We further analyzed the effects of wind veering on turbine performance for specific values of speed shear and found detrimental conditions on the order of 10 % for wind speed regimes predominantly located in the middle of the power curve. Focusing on a time period of ramping electricity demand (06:00–09:00 LT – local time) exposed the fact that large direction shear occurred during this time and undermined turbine performance by more than 10 %. A predominance of clockwise direction shear (wind veering) cases compared to counterclockwise (wind backing) was also observed throughout the campaign. Moreover, large veering was found to have greater detrimental effects on turbine performance compared to small backing values. This study shows that changes in wind direction with height should be considered when analyzing turbine performance.

17 WIND ENERGY↗

A baseline for ensemble-based, time-resolved inflow reconstruction for a single turbine using large-eddy simulations and latent diffusion models

We are interested in reconstructing winds flowing through a turbine on a second-by-second basis over a 10 min window. Previously, we developed a machine learning algorithm that takes in a snapshot of wind speed measurements and generates ensembles of three-dimensional wind field estimates. Here, we use these estimates as initial conditions in large-eddy simulations and reconstruct atmospheric and turbine response dynamic quantities in a synthetic field campaign. In doing so, we establish a baseline for model validation that future time-aware data assimilation techniques will be compared to. In turbine-free case studies, ground truth wind speeds consistently fall within our estimated wind speed distribution for the first 100 s after the simulation start. In simulations with turbines, the wind estimates show a small bias of 0.10 m s 1 and good correlation of 0.80 during the first 100 s. During this window, our estimates of the Blade 1 bending moment and generator power typically span the ground truth, with the estimate of the former performing better overall. In summary, this approach shows promise as a stand-alone technique for reconstructing real-world inflow and turbine dynamics in 1-2 min windows and as a foundation for future time-aware data assimilation techniques.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Competitiveness Improvement Project Informational Workshop

The National Renewable Energy Laboratory (NREL) is hosted an in-person workshop and webinar for the distributed wind Competitiveness Improvement Project (CIP) on Tuesday, December 17, 2019, at NREL's Flatirons Campus. The CIP is a periodic solicitation issued by NREL on behalf of the U.S. Department of Energy's Wind Energy Technologies Office. Through a competitive process, component suppliers and manufacturers of small- to medium-sized wind turbine technology are awarded cost-shared subcontracts to optimize their designs, develop advanced manufacturing processes, and perform turbine testing. The CIP aims to make wind energy cost competitive with other distributed generation technologies and increase the number of wind turbine designs certified to national performance and safety standards.

17 WIND ENERGY↗

U.S. Department of Energy Competitiveness Improvement Project (CIP) 2024 Technology Commercialization Awardee: Siva Powers America Inc.

This fact sheet describes the 2024 Competitiveness Improvement Project (CIP) award received by Siva Powers America Inc. for a Technology Commercialization Award. The U.S. Department of Energy's (DOE's) CIP awards cost-shared subcontracts and technical support to manufacturers of small and medium-sized wind turbines. Managed by NREL on behalf of DOE's Wind Energy Technologies Office, CIP helps advance wind energy as a cost-effective, distributed generation technology option.

17 WIND ENERGY↗

U.S. Department of Energy Competitiveness Improvement Project (CIP) 2024 Manufacturing Process Innovation Awardee: Bergey Windpower Co.

This fact sheet describes the 2024 Competitiveness Improvement Project (CIP) award received by Bergey Windpower Co. for manufacturing process innovation. The U.S. Department of Energy's (DOE's) CIP awards cost-shared subcontracts and technical support to manufacturers of small and medium-sized wind turbines. Managed by NREL on behalf of DOE's Wind Energy Technologies Office, CIP helps advance wind energy as a cost-effective, distributed generation technology option.

17 WIND ENERGY↗

U.S. Department of Energy Competitiveness Improvement Project (CIP) 2024 Component Innovation Awardee: Windurance LLC

This fact sheet describes the 2024 Competitiveness Improvement Project (CIP) award received by Windurance LLC for component innovation. The U.S. Department of Energy's (DOE's) CIP awards cost-shared subcontracts and technical support to manufacturers of small and medium-sized wind turbines. Managed by NREL on behalf of DOE's Wind Energy Technologies Office, CIP helps advance wind energy as a cost-effective, distributed generation technology option.

17 WIND ENERGY↗

U.S. Department of Energy Competitiveness Improvement Project (CIP) 2024 Technology Commercialization Awardee: EWT Americas Inc.

This fact sheet describes the 2024 Competitiveness Improvement Project (CIP) award received by EWT Americas, Inc., for technology commercialization. The U.S. Department of Energy's (DOE's) CIP awards cost-shared subcontracts and technical support to manufacturers of small and medium-sized wind turbines. Managed by NREL on behalf of DOE's Wind Energy Technologies Office, CIP helps advance wind energy as a cost-effective, distributed generation technology option.

17 WIND ENERGY↗

U.S. Department of Energy Competitiveness Improvement Project (CIP) 2024 Prototype Installation and Testing Awardee: Accelerate Wind

This fact sheet describes the 2024 Competitiveness Improvement Project (CIP) award received by Accelerate Wind for Prototype Installation and Testing. The U.S. Department of Energy's (DOE's) CIP awards cost-shared subcontracts and technical support to manufacturers of small and medium-sized wind turbines. Managed by NREL on behalf of DOE's Wind Energy Technologies Office, CIP helps advance wind energy as a cost-effective, distributed generation technology option.

17 WIND ENERGY↗

U.S. Department of Energy Competitiveness Improvement Project (CIP) 2024 Prototype Installation and Testing Awardee: Pecos Wind Power

This fact sheet describes the 2024 Competitiveness Improvement Project (CIP) award received by Pecos Wind Power for Prototype Installation and Testing. The U.S. Department of Energy's (DOE's) CIP awards cost-shared subcontracts and technical support to manufacturers of small and medium-sized wind turbines. Managed by NREL on behalf of DOE's Wind Energy Technologies Office, CIP helps advance wind energy as a cost-effective, distributed generation technology option.

17 WIND ENERGY↗

U.S. Department of Energy Competitiveness Improvement Project (CIP) 2024 Inverter Listing Awardee: Eocycle America Corporation

This fact sheet describes the 2024 Competitiveness Improvement Project (CIP) award received by Eocycle America Corporation for Inverter Listing. The U.S. Department of Energy's (DOE's) CIP awards cost-shared subcontracts and technical support to manufacturers of small and medium-sized wind turbines. Managed by NLR on behalf of DOE, CIP helps advance wind energy as a cost-effective, distributed generation technology option.

17 WIND ENERGY↗

U.S. Department of Energy Competitiveness Improvement Project 2024 Technology Commercialization Awardee: Intelligent Energy Systems

This fact sheet describes the 2024 Competitiveness Improvement Project (CIP) award received by Intelligent Energy Systems for technology commercialization. The U.S. Department of Energy's (DOE's) CIP awards cost-shared subcontracts and technical support to manufacturers of small and medium-sized wind turbines. Managed by NLR on behalf of DOE's Wind Energy Technologies Office, CIP helps advance wind energy as a cost-effective, distributed-generation technology option.

17 WIND ENERGY↗

Control of large wind turbine generators connected to utility networks

This is an investigation of the control requirements for variable pitch wind turbine generators connected to electric power systems. The requirements include operation in very small as well as very large power systems. Control systems are developed for wind turbines with synchronous, induction, and doubly fed generators. Simulation results are presented. It is shown how wind turbines and power system controls can be integrated. A clear distinction is made between fast control of turbine torque, which is a peculiarity of wind turbines, and slow control of electric power, which is a traditional power system requirement.

Hinrichsen, E. N.↗

Advanced Distributed Wind Turbine Controls Series: Part 2-Wind Energy in Isolated Grids – Microgrids, Infrastructure Resilience, and Advanced Controls Launchpad (MIRACL)

In an isolated grid, wind turbines are typically deployed to provide energy to maximize energy production, reduce diesel-fuel consumption, reduce carbon emissions, and reduce costs for energy and fuel transportation. However, in addition to solely providing energy to the power system, wind turbines contain rotating masses and inverter-based controls that can enable various reliability and resilience services through advance controls. As part of the Microgrids, Infrastructure Resilience, and Advanced Controls Launchpad (MIRACL) this paper demonstrates, through desktop simulations, advanced wind turbine controls that can be employed to support higher contributions of wind in isolated grids, and to demonstrate ways that wind can play a role in supporting stability of an isolated grid. This isolated grid used in these desktop simulations is comprised of a wind turbine (600 kW), solar PV (430 kW), battery energy storage system (1 MW/1MWh), a simulated diesel generator (2 MW) and various types of loads (critical, dynamic). We developed a model of the subsystems in MATLAB/Simulink and validated them with available data from real-world components on NREL's Flatirons Campus. These validated models are then configured for various case studies. We compare the output of the desktop simulation with a baseline case with the diesel generator. Active and reactive power control of the wind turbine can help improve frequency and voltage responses in the isolated grid, respectively. By utilizing a small integrated battery energy storage system in the DC-link of the wind turbine, we also demonstrate that wind turbines can help blackstart a critical load comparable to its rated power and support other renewables (e.g. solar PV) come online and pick up an additional load. This report illustrates some of these reliability and resilience services a wind turbine can provide in an isolated grid.

17 WIND ENERGY↗

Implementing Inertial Control for PMSG-WTG in Region 2 Using Virtual Synchronous Generator with Multiple Virtual Rotating Masses

With the increasing integration of renewable energy, the problems associated with a deteriorating grid frequency profile and potential power system instability have become more significant. In this paper, the inertial control algorithm using a virtual synchronous generator (VSG) is implemented on a Type 4 permanent magnet synchronous generator (PMSG) wind turbine generator (WTG). The overall nonlinear dynamic model and its small-signal linearization of the PMSG-WTG using a VSG is established and comprehensively analyzed. Inevitably, the direct application of the VSG introduces a large inertia, which causes conflict between the fast variance of available wind power and inverter control with slow dynamics, particularly in Region 2 of the wind turbine. Aiming to address such issues, a VSG with multiple virtual rotating masses is proposed to improve the active power tracking performance as well as to boost the inertial control of a VSG. The inertial responses are verified in a modified 10-MVA IEEE 14-bus microgrid system. The assessment of the simulation results demonstrates the applicability of the VSG on renewable energy generation units.

17 WIND ENERGY↗

DigiFloat (Final Scientific/Technical Report)

This purpose of this report is to document the development of a floating offshore wind platform Digital Twin for the ARPA-E-funded DigiFloat project led by Principle Power, Inc. In Offshore Wind, Digital Twins are aimed at reducing farm-wide OPEX expenditures through reduced-basis inspection, assessing life extension methods, and obtaining better knowledge of the deployed assets for future product optimization. There is a high level of technical effectiveness and economic feasibility for the technology investigated, as it uses commercial off-the-shelf sensors, and a commercial software package. A substantial portion of the project goals are improvement of existing technology for use with floating wind turbines, and new application of an existing technology to a rapidly-growing sector. A few sensors applied to a small number of units bring benefit to the entire fleet of floating wind turbines in a given farm, and in other future wind farms. The benefits to the public of this project are further optimization and maturation of floating wind technology, to bring it to the U.S. market faster and cheaper.

17 WIND ENERGY↗