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At least 271 records · Page 15

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DOE OSTI2020

A simple method for modelling fatigue spectra of small wind turbine blades

Small-scale wind turbines have market opportunities in distributed energy generation applications but face future challenges in remaining cost competitive compared with solar photovoltaic systems. High unit costs can be attributed to design conservatism when calculating fatigue loads of key structural components such as the blades. In this study, we use the aeroelastic software FAST to highlight limitations of the International Electrotechnical Commission 61400-2:2013 small wind turbine design standard for calculating fatigue life using the simplified load model. We present a modified method for calculating the fatigue spectra of small wind turbine blades. An advantage of this method is that it does not require complex aeroelastic simulations or field measurements. This modified method is intended to be implemented early in the blade design stage, such as during rotor optimization simulations, allowing for multiple rotor configurations to be rapidly compared.

17 WIND ENERGY↗

DOE OSTI2021

Evaluating the Grid Impact of Oregon Offshore Wind

This analysis used high resolution offshore wind data and a detailed production cost model of the Western Interconnection to explore the value and operational impact of integrating offshore wind along Oregon's coastline. Leveraging local technical stakeholder expertise and input, we determined a set of scenarios to explore. These scenarios varied offshore wind penetrations and explored the differences of integrating offshore wind in the current grid and a potential future grid. This allowed us to determine how changes to the rest of the system and increasing penetrations of offshore wind affected our findings. We identified a number of key findings from the analysis, including that 2.6 GW of nameplate capacity offshore wind could be integrated into the Oregon power system with minimal curtailment due to transmission congestion or other factors. The range of system value provided by offshore wind ranges between $\$$65/MWh and $\$$85/MWh across the various scenarios considered. We also examined the influence offshore wind had on the trans-Cascade power flow, where we determined a strong correlation between offshore wind generation and reduction in flow across the Cascades. Finally, we also determined that offshore wind could serve between 84 - 93% of Coastal Oregon loads depending on the scenario.

17 WIND ENERGY↗

DOE OSTI2021

Evaluating the Grid Impact of Oregon Offshore Wind [Slides]

This analysis used high-resolution offshore wind data and a detailed production cost model (PCM) of the Western Interconnection to explore the value and operational impact of integrating offshore wind along Oregon's coastline. Leveraging local technical stakeholder expertise and input, we determined a set of scenarios to explore. These scenarios vary both offshore wind capacities and the Western Interconnection generation and transmission infrastructure. From the scenario modeling and analysis, we identified the following key findings. In addition, we simulated a subset of the scenarios for a range of historical weather years (2007-2013), to understand the robustness of our findings to different weather conditions. Trans-coastal transmission constraints and congestion are the key drivers to the curtailment of Oregon offshore wind. Once power can be delivered into the Willamette Valley, there are few system constraints that lead to a significant curtailment of offshore wind off the coast of Oregon. Approximately 2.6 GW of installed offshore wind capacity can be integrated into Oregon's power system without major upgrades to trans-coastal transmission while avoiding significant curtailment. The system value provided by offshore wind ranges between $\$65$ /MWh and $\$85$ /MWh across the various scenarios considered. Offshore wind heavily influences the flow of the cross Cascade transmission. Across all scenarios, we found a robust relationship of approximately 500-550 MW decrease in the hourly flow of the cross Cascade transmission for every 1,000 MW of hourly offshore wind generation. However, we also found there was not a strong relationship between the highest cross-Cascade transmission flow hours and high offshore wind generation, limiting the extent to which offshore wind can be considered a non-wires alternative to cross cascade transmission. Depending on the meteorological year, 880-1,580 MW and 1,650-3,100 MW can be counted on to serve coastal loads with 2.6 GW and 5 GW of offshore wind capacity, respectively. Offshore wind allows for more optimal daily and hourly scheduling of hydropower, while still complying with various technical and regulatory constraints on the water resource. Oregon offshore wind has the potential to contribute to the evening net load peak in California (i.e., mitigate duck curve challenges), however transmission congestion between California and Oregon limits this contribution. Co-located storage at the point of interconnection for offshore wind reduces curtailment when trans-coastal transmission is not upgraded, providing a non-wires alternative to increase offshore wind capacity beyond 2.6 GW.

17 WIND ENERGY↗

DOE OSTI2021

Distributed Wind Market Report: 2021 Edition

The Distributed Wind Market Report: 2021 Edition provides stakeholders with statistics and analysis of the distributed wind market, along with insight into its trends and characteristics. The report analyzes distributed wind projects of all sizes and details the U.S. small wind market.

17 WIND ENERGY↗

DOE OSTI2021

OpenDSS-wrapper (Distribution System Co-simulator with Distributed Energy Resource Controls)

Electric grid transformation with the proliferation of distributed energy resources (DER), such as solar photovoltaic (PV), wind, advanced energy storage technologies, and electric vehicles, and the growing use of communication technologies in both transmission and distribution systems are increasing the need to capture the interactions among these systems. Advanced modeling, control, and simulation tools that can perform co-simulation of electric power systems with other domains become indispensable to accurately model these interactions. To address this need, we have developed a codebase that integrates an electric power distribution system simulator, DER models, and DER controls. The codebase is based on OpenDSS, a distribution system simulator, and an existing open source co-simulation framework called HELICS. The contribution and uniqueness of the proposed codebase is that it tailors the generic HELICS framework specifically for distribution grid-related applications. The codebase includes an OpenDSS wrapper that controls the simulation, implements advanced DER controls, and extracts power flows, voltages, and other power system element information from the the distribution network modeled in OpenDSS. Sample HELICS federates, including a federate for OpenDSS, are provided that can communicate messages through the HELICS interface. Sample federates can be modified and additional HELICS federates can be added by the user depending on their use case requirements. SEE ALSO: https://github.com/NREL/dss-cosim

Blonsky, Michael↗

DOE OSTI2022

2020 Awardee of Two Small Wind Turbine Certification and Listing Awards: QED

With support from the Competitiveness Improvement Project's Small Wind Turbine Certification and Listing awards, QED Wind Power LLC will expand their ability to manufacture and distribute their 20-kilowatt, small wind turbine model to larger national markets. QED Wind Power aims to achieve this by conducting and completing testing of their small wind turbine and achieve safety and performance certification and listing with support from the National Renewable Energy Laboratory. This fact sheet provides an overview of QEDWind Power's project, how the company will achieve the goals of the two awards, and how the project fits within the overall Competitiveness Improvement Project.

CIP↗

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↗

NASA NTRS2011

Wind and Temperature Spectrometry of the Upper Atmosphere in Low-Earth Orbit

Wind and Temperature Spectrometry (WATS) is a new approach to measure the full wind vector, temperature, and relative densities of major neutral species in the Earth's thermosphere. The method uses an energy-angle spectrometer moving through the tenuous upper atmosphere to measure directly the angular and energy distributions of the air stream that enters the spectrometer. The angular distribution gives the direction of the total velocity of the air entering the spectrometer, and the energy distribution gives the magnitude of the total velocity. The wind velocity vector is uniquely determined since the measured total velocity depends on the wind vector and the orbiting velocity vector. The orbiting spectrometer moves supersonically, Mach 8 or greater, through the air and must point within a few degrees of its orbital velocity vector (the ram direction). Pointing knowledge is critical; for example, pointing errors 0.1 lead to errors of about 10 m/s in the wind. The WATS method may also be applied without modification to measure the ion-drift vector, ion temperature, and relative ion densities of major ionic species in the ionosphere. In such an application it may be called IDTS: Ion-Drift Temperature Spectrometry. A spectrometer-based coordinate system with one axis instantaneously pointing along the ram direction makes it possible to transform the Maxwellian velocity distribution of the air molecules to a Maxwellian energy-angle distribution for the molecular flux entering the spectrometer. This implementation of WATS is called the gas kinetic method (GKM) because it is applied to the case of the Maxwellian distribution. The WATS method follows from the recognition that in a supersonic platform moving at 8,000 m/s, the measurement of small wind velocities in the air on the order of a few 100 m/s and less requires precise knowledge of the angle of incidence of the neutral atoms and molecules. The same is true for the case of ion-drift measurements. WATS also provides a general approach that can obtain non-equilibrium distributions as may exist in the upper regions of the thermosphere, above 500 km and into the exosphere. Finally, WATS serves as a mass spectrometer, with very low mass resolution of roughly 1 part in 3, but easily separating atomic oxygen from molecular nitrogen.

Herrero, Federico↗

DOE OSTI2023

Valuation of Distributed Wind Turbines Providing Multiple Market Services

The role of wind turbines has traditionally been limited to providing energy capacity to the grid, but the availability of smart inverters and recent regulatory changes provide the technical and policy capability for wind turbines to also provide ancillary services. However, in contrast to the technical and policy aspects, the valuation of distributed wind turbines providing such services has not been thoroughly studied. This paper presents an optimal market-participation method for distributed wind turbines and valuates different strategies in California Independent System Operator’s balancing area. The services include energy capacity, regulation up and down, and reserves. An optimization problem is formulated to determine optimal power output for each service and demonstrated using historical data for one complete year. The revenues from multiple services are quantified, and a sensitivity analysis is performed to relate market prices with revenues. It is found that the optimal strategy generates 6% more revenue compared to the revenue from participating in the energy market only. Also, the reduced energy prices in future scenarios increase the relative importance of market participation in ancillary services.

Bhatti, Bilal Ahmad↗

DOE OSTI2020

Coastal Community Resiliency Enhancement Using Marine Hydrokinetic (MHK) Resources and Networked Microgrids

Enormous challenges are inherent in the operation of modern distribution grids. In particular, distribution feeders can be severely compromised under extreme conditions such as large-scale weather events (e.g., hurricanes, floods, and other types of natural disasters). To combat this problem, they turn to local energy support from distributed energy resources, such as solar and wind, marine hydrolinetic (MHK), and other types of energy. In this report, we investigate the actual characteristics of MHK resources to enhance coastal community resiliency. Two typical types of MHK resources (i.e., wave and tidal resources) illustrate the coastal resilience enhancement framework. By identifying their operational characteristics, such as target time-scales and potential power generation variations, we detail a holistic coastal community resiliency enhancement framework that integrates both optimization and control efforts. The optimization problem is formulated to significantly minimize the power outage time at the critical infrastructures in coastal communities by implementing multiple autonomous and dynamic microgrids around MHK resources. Therefore, during severe power outages caused by natural disasters (e.g., floods, hurricanes), the coastal community load profiles can be satisfied using local MHK resources in each microgrid with limited or no power support from upstream power grids.

16 TIDAL AND WAVE POWER↗

DOE OSTI2021

Resource Occurrence and Productivity in Existing and Proposed Wind Energy Lease Areas on the Northeast US Shelf

States in the Northeast United States have the ambitious goal of producing more than 22 GW of offshore wind energy in the coming decades. The infrastructure associated with offshore wind energy development is expected to modify marine habitats and potentially alter the ecosystem services. Species distribution models were constructed for a group of fish and macroinvertebrate taxa resident in the Northeast US Continental Shelf marine ecosystem. These models were analyzed to provide baseline context for impact assessment of lease areas in the Middle Atlantic Bight designated for renewable wind energy installations. Using random forest machine learning, models based on occurrence and biomass were constructed for 93 species providing seasonal depictions of their habitat distributions. We developed a scoring index to characterize lease area habitat use for each species. Subsequently, groups of species were identified that reflect varying levels of lease area habitat use ranging across high, moderate, low, and no reliance on the lease area habitats. Among the species with high to moderate reliance were black sea bass ( Centropristis striata ), summer flounder ( Paralichthys dentatus ), and Atlantic menhaden ( Brevoortia tyrannus ), which are important fisheries species in the region. Potential for impact was characterized by the number of species with habitat dependencies associated with lease areas and these varied with a number of continuous gradients. Habitats that support high biomass were distributed more to the northeast, while high occupancy habitats appeared to be further from the coast. There was no obvious effect of the size of the lease area on the importance of associated habitats. Model results indicated that physical drivers and lower trophic level indicators might strongly control the habitat distribution of ecologically and commercially important species in the wind lease areas. Therefore, physical and biological oceanography on the continental shelf proximate to wind energy infrastructure development should be monitored for changes in water column structure and the productivity of phytoplankton and zooplankton and the effects of these changes on the trophic system.

17 WIND ENERGY↗

DOE OSTI2020

miniGAN: a proxy application for generative adversarial networks

miniGAN is a python-based machine learning proxy application for generative adversarial networks, developed through the Exascale Computing Project's (ECP) ExaLearn project. It will be included in the main ECP proxy application and the machine learning proxy application suite. It is a proxy for ECP cosmological(CosmoFlow, ExaGAN) and wind energy(ExaWind) applications. miniGAN will be distributed to ECP hardware vendors as part of hardware codesign. miniGAN uses the Numpy/PyTorch/TensorFlow/Keras/Horovod frameworks and libraries. It also relies on the Kokkos and Kokkos-Kernels packages developed here at Sandia Labs. SAND2020-2038 M Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.

Ellis, John↗

DOE OSTI2021

Network Based Estimation of Wind Farm Power and Velocity Data Under Changing Wind Direction

This paper describes an estimation algorithm for velocity and power output signals in a wind farm under changing wind direction. A graph-theoretic definition describes the wind farm as a collection of nodes (turbines) and time-varying weighted edges (inter-turbine wake propagation) that change as a function of incoming wind direction. The velocity at each turbine is determined through a discrete input-output model. Changes in wind direction serve as the input and the output is defined in terms of a time-varying weighted adjacency matrix that depends on the time-delay of information propagation between turbines. These delays, which are defined in terms of the advection speed of the wind and the distance between the turbines, capture the delayed effect of wind direction changes on the inter-connectivity of the graph as the wind conditions at the farm inlet propagate through the turbine array. An event-based update framework is employed to capture time-dependent topology changes due to shifts in wind direction. Simulation results for dynamically changing wind inlet directions to a circular wind farm are compared to predictions from both the static and dynamic versions of the FLOw Redirection and Induction in Steady State (FLORIS) model. The approach is shown to enable real-time tracking of dynamic changes to wind farm power output within a framework that can be easily integrated into real-time, horizon-based, control strategies that typically do not account for wind direction changes.

distributed↗

NASA NTRS1985

Gravity Waves

In recent years it has been widely recognized that vertically propagating gravity waves play an important role in the dynamics of the middle atmosphere in partly determining the large scale temperature and wind structure through their energy and momentum transport. In particular, the meridional temperature distribution and the mean wind profile in the upper mesosphere are considered to be largely affected by the turbulence diffusion and friction that gravity waves induce through their breaking. For an understanding of the middle atmosphere circulation, it is therefore very important to know the global distribution and temporal variation of gravity waves in a climatological sense. The results of the statistics for gravity wave activity in the stratosphere and mesosphere are presented as a function of latitude and month, with the aid of meteorological rocket network observations.

Hirota, I.↗

NASA NTRS1992

Anisotropy of the energetic neutral atom flux in the heliosphere

Characteristics of the energetic neutral atoms born at the heliospheric interface are considered for plasma flow structure resulting from a two-shock model of the interaction between the solar wind and the interstellar medium. The energy distributions of heliospheric energetic neutral atoms (HELENAs) are calculated and it is shown that the HELENA flux is highly anisotropic at the earth's orbit. The characteristics of the HELENA flux are highly sensitive to the size of the heliosphere. This supports the conclusion that measurements of HELENAs from the earth's orbit would provide an efficient tool to remotely study the heliosphere.

Gruntman, Michael A.↗

DOE OSTI2022

Design Innovations for Deployable Wind Turbines

Deployable wind turbines have the potential to produce on-site electricity for defense and disaster relief needs, both increasing resiliency and overall energy production diversity.

17 WIND ENERGY↗

NASA NTRS2010

Crossed, Small-Deflection Energy Analyzer for Wind/Temperature Spectrometer

Determination of neutral winds and ion drifts in low-Earth-orbit missions requires measurements of the angular and energy distributions of the flux of neutrals and ions entering the satellite from the ram direction. The magnitude and direction of the neutral-wind (or ion-drift) determine the location of the maximum in the angular distribution of the flux. Knowledge of the angle of maximum flux with respect to satellite coordinates (pointing) is essential to determine the wind (or ion-drift) vector. The crossed Small-Deflection Energy Analyzer (SDEA) spectrometer (see Figure 1) occupies minimal volume and consumes minimal power. Designed for upper atmosphere/ionosphere investigations at Earth altitudes above 100 km, the spectrometer operates by detecting the angular and energy distributions of neutral atoms/molecules and ions in two mutually perpendicular planes. In this configuration, the two detection planes actually cross at the spectrometer center. It is possible to merge two SDEAs so they share a common optical axis and alternate measurements between two perpendicular planes, and reduce the number of ion sources from two to one. This minimizes the volume and footprint significantly and reduces the ion source power by a factor of two. The area of the entrance aperture affects the number of ions detected/second and also determines the energy resolution. Thermionic emitters require heater power of about 100 mW to produce 1 mA of electron beam current. Typically, electron energy is about 100 eV and requires a 100-V supply for electron acceleration to supply an additional 100 mW of power. Thus, ion source power is at most 200 mW. If two ion sources were to be used, the ion source power would be, at most, 400 mW. Detector power, deflection voltage power, and microcontroller and other functions require less than 150 mW. A WTS (wind/ temperature spectrometer) with two separate optical axes would consume about 650 mW, while the crossed SDEA described here consumes about 350 mW. The entrance aperture has a diameter of 0.004 in. (0.10 mm) to provide the required energy resolution between 0.05 and 0.15. This design (see Figure 2) provides a WTS occupying a volume less than 40 cm(sup 3), on a footprint of diameter about 1.5 in. (38 mm). The Crossed SDEA offers many advantages in the measurements of neutral wind and ion drifts in the Earth's thermosphere. As such, it will be useful in future commercial satellites dedicated to monitoring the ionosphere with a view to improving the integrity and predictability of GPS operations.

Herrero, Federico A.↗

DOE OSTI2025

Architectural Approaches for Integrating ADMS and DERMS: Challenges, Comparisons, and Real-World Use Cases

The electrical distribution landscape is rapidly transforming due to the proliferation of distributed energy resources (DERs) such as solar panels, wind turbines, battery storage systems, combined heat and power units, and electric vehicles, introducing variability and uncontrollability that traditional grid operators are ill-equipped to manage. This transformation is further accelerated by advancements in Information and Communication Technology infrastructure that connects control centers with end devices, demanding automation and a deeper understanding of new technologies by utility personnel. Advanced grid control techniques using system-level optimization, Artificial Intelligence, and Machine Learning at the enterprise level and distributed level are evolving to address these issues. There is also an opportunity to utilize the enormous data created by these new DER technologies in the grid. Advanced Distribution Management Systems (ADMS) and Distributed Energy Resource Management Systems (DERMS) are critical in addressing these challenges by automating grid operations and enhancing reliability. Given the relatively recent development of ADMS and DERMS, and the still relatively low level of ADMS and DERMS deployment in the industry, there is a notable deficiency in the comprehensive understanding of the challenges and benefits associated with these new technologies, especially with their complementary natures and integration architectures. This paper aims to bridge the knowledge gap in ADMS and DERMS integration, presenting three distinct integration architectures currently available, and discussing the challenges and benefits of each architecture to guide utilities, industry professionals, and researchers in optimizing grid management and decision-making processes for a resilient and efficient energy future.

24 POWER TRANSMISSION AND DISTRIBUTION↗