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Schroeder, John

Publications and source records attributed to Schroeder, John.

13 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Large-eddy simulation of an atmospheric bore and associated gravity wave effects on wind farm performance in the southern Great Plains

Gravity waves are a common occurrence in the atmosphere, with a variety of generation mechanisms. Their impact on wind farms has only recently gained attention, with most studies focused on wind farm-induced gravity waves. In this study, the interaction between a wind farm and gravity waves generated by an atmospheric bore event is assessed using multiscale large-eddy simulations. The atmospheric bore is created by a thunderstorm downdraft from a nocturnal mesoscale convective system (MCS). The associated gravity waves impact the wind resource and power production at a nearby wind farm during the American Wake Experiment (AWAKEN) in the US southern Great Plains. A two-domain nested setup (Δx=300 and 20 m) is used in the Weather Research and Forecasting (WRF) model, forced with data from the High-Resolution Rapid Refresh model, to capture both the formation of the bore and its interaction with individual wind turbines. The MCS is resolved on the large outer domain, where the structure of the bore and the associated gravity waves are found to be especially sensitive to parameterized microphysics processes. On the finer inner domain, gravity wave interactions with individual wind turbines are resolved; wake dynamics are captured using a generalized actuator disk parameterization in WRF. The gravity waves are found to have a strong effect on the atmosphere above the wind farm; however, the effect of the waves is more nuanced closer to the surface where there is additional turbulence, both ambient and wake-generated. Notably, the gravity waves modulate the mesoscale environment by weakening and dissipating the preexisting low-level jet, which reduces hub-height wind speed and hence the simulated power output, which is confirmed by the observed supervisory control and data acquisition (SCADA) power data. Additionally, the gravity waves induce local wind direction variations correlated with fluctuations in pressure, which lead to fluctuations in the simulated power output as various turbines within the farm are subjected to waking from nearby turbines.

17 WIND ENERGY↗
DOE OSTI2024

Land-based wind plant wake characterization using dual-Doppler radar measurements at AWAKEN

Wind plant wakes have been shown to persist for tens of kilometers downstream in offshore environments, reducing the power output of neighboring plants, but their behavior on land remains relatively unexplored through observation. This study capitalizes on the unique and extensive field data collected for the American WAKE ExperimeNt (AWAKEN) project underway in northern Oklahoma. X-band dual-Doppler radars deployed at this site measure wind speed and direction at 25-m and 2-min resolution within a 30-km range, capturing the interactions between three neighboring wind plants. These measurements show that the wake of one wind plant extends at least 15 km downstream under easterly wind and stable atmospheric conditions. Though the wake wind speed increases within the first 10 km, it plateaus at 90% of the freestream wind speed. The spanwise velocity distribution within the wake initially shows the clear signature of the wind plant layout, which is smoothed as it propagates downstream, indicating spanwise momentum transfer is a key mechanism in wind plant wake development and recovery. These findings have important implications for wind plant siting decisions and resource assessments, and provide insights into atmospheric interactions at the wind plant scale.

17 WIND ENERGY↗
DOE OSTI2022

Design of the American Wake Experiment (AWAKEN) field campaign

The American WAKE experimeNt (AWAKEN) is a multi-institutional collaborative field campaign, starting in March 2022, that will gather an unprecedented data set including both atmospheric observations and wind plant operational data. This comprehensive data set will be used to characterize the wind plant performance and turbine loading in different operational and atmospheric conditions and validate the use of different wind plant control strategies and simulation frameworks. An extensive field campaign like AWAKEN requires proper coordination and long-term planning to be successful. In this paper, we review the major activities planned during AWAKEN to provide information for current and future project partners. Specifically, we provide information about the project sites, their planned instruments, and how these will relate to the scientific objectives of the overall AWAKEN project.

17 WIND ENERGY↗
DOE OSTI2017

Reliability Study: On-Site Electrical System, 1998-2015

This report documents an analysis of the reliability of on-site electrical systems at U.S. commercial nuclear plants during the period 1998-2015. The study contains both individual component studies and system studies. The component studies are focused on key electrical components including circuit breakers, battery chargers, buses, batteries, and transformers. Data from the range of 1998 to 2015 were gathered, reviewed, and statistically evaluated for impacts on reliability as a function of relevant parameters: manufacturer, system, operating environment, inspection/testing regimen, operating range (voltages, amperes), setpoints, and other factors. The system studies identify seven operating nuclear power plants/units that represent different designs of offsite power sources and interconnecting power circuit paths, develop electrical single line diagrams and detailed fault tree models for the representing designs, and evaluate the electrical system reliability using the reliability data obtained from the component studies.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2017

Final Technical Report: The Incubation of Next-Generation Radar Technologies to Lower the Cost of Wind Energy

The National Wind Institute (NWI) at Texas Tech University (TTU) has had an impressive and well documented 46-year history of wind related research activities (http://www.depts.ttu.edu/nwi/). In 2011 with funding from the United States Department of Energy (DOE), an NWI team applied radar technologies and techniques to document the complex flows occurring across a wind plant. The resulting efforts yielded measurements that exceeded the capabilities of commercial lidar technologies with respect to maximum range, range resolution and scan speed. The NWI team was also the first to apply dual-Doppler synthesis and objective analysis techniques to resolve the full horizontal wind field (i.e. not just the line-of-sight wind speeds) to successfully define turbine inflow and wake flows across large segments of wind plants. While these successes advanced wind energy interests, the existing research radar platforms were designed to serve a diversity of meteorological applications, not specifically wind energy. Because of this broader focus and the design choices made during their development, the existing radars experienced technical limitations that inhibited their commercial viability and wide spread adoption. This DOE project enabled the development of a new radar prototype specifically designed for the purpose of documenting wind farm complex flows. Relative to other “off the shelf” radar technologies, the specialized transmitter and receiver chains were specifically designed to enhance data availability in non-precipitating atmospheres. The new radar prototype was integrated at TTU using components from various suppliers across the world, and installed at the Reese Technology Center in May 2016. Following installation, functionality and performance testing were completed, and subsequent comparative analysis indicated that the new prototype greatly enhances data availability by a factor of 3.5-50 in almost all atmospheric conditions. The new prototype also provided enhanced signal quality in clear air (i.e. non-precipitating) environments, mitigated atmospheric attenuation, and extended the useful range of data collection to beyond 30km in cooperative atmospheric conditions. Additionally, the new DOE-X prototype appears to benefit from Bragg scattering when the thermal stratification of the atmosphere is strong (i.e. nocturnal hours). This result was not possible in any capacity with the previous technology. Combined, these developments represent the achievement of all project objectives, advance the Technical Readiness Level (TRL) to a level of 7, and open the door for more widespread adoption and usage in the wind energy sector. At the same time, radar induced artifacts from multi-trip echoes and ground targets increased with the new technology, and these required additional attention for some applications. Commercialization activity accelerated in parallel with the DOE funded project, as SmartWind Technologies, L.L.C., was contracted to provide two new radar systems to DONG Energy to monitor the Westermost Rough wind plant off the east coast of the United Kingdom. These new early stage commercial radars systems were closely related to the DOE prototype, but maintain more robust ancillary support systems. The radars were installed during the summer of 2016, and have been operational since that time. Additionally, commercially funded advancements have since been made in processing sophistication to mitigate the previously identified radar artifacts. TTU and SmartWind Technologies stand ready to provide public and private partners focused on wind plant optimization with this new capability. Ancillary interests have also been identified as the initial deployments of the technology have shown the ability to identify and track avian and drone activity, opening up multi-purpose operational opportunities.

17 WIND ENERGY↗
DOE OSTI2017

Apparatus and method for using radar to evaluate wind flow fields for wind energy applications

The present invention provides an apparatus and method for obtaining data to determine one or more characteristics of a wind flow field using one or more radars. Data is collected from the one or more radars, and analyzed to determine the one or more characteristics of the wind flow field. The one or more radars are positioned to have a portion of the wind flow field within a scanning sector of the one or more radars.

17 WIND ENERGY↗
DOE OSTI2016

System and method for evaluating wind flow fields using remote sensing devices

The present invention provides a system and method for obtaining data to determine one or more characteristics of a wind field using a first remote sensing device and a second remote sensing device. Coordinated data is collected from the first and second remote sensing devices and analyzed to determine the one or more characteristics of the wind field. The first remote sensing device is positioned to have a portion of the wind field within a first scanning sector of the first remote sensing device. The second remote sensing device is positioned to have the portion of the wind field disposed within a second scanning sector of the second remote sensing device.

17 WIND ENERGY↗
DOE OSTI2016

Risk Assessment in Event Evaluation P-302

Incidents at locations such as nuclear power plants, waste repositories, and medical treatment facilities occur at many different times and under a variety of situations. Even the most modern, well run organizations may experience events that are precursors to more serious situations. Currently, the U.S. Nuclear Regulatory Commission evaluates a variety of such events at commercial nuclear plants via the Significance Determination Process (SDP), Management Directive 8.3, and the Accident Sequence Precursor (ASP) program. In these programs, the analyst calculates a conditional risk measure (e.g., conditional core damage probability) for an initiating event situation or an unplanned equipment outage. This calculation is called an “event evaluation.” An “event evaluation” uses a probabilistic risk assessment model to obtain a risk measure that is conditional on the situation which existed during an incident. The Risk Assessment in Event Evaluation material is intended to address how this evaluation is performed using modern risk analysis tools.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2014

Event Tree Success Branch Modeling Approaches in SAPHIRE/SPAR

Standardized Plant Analysis Risk (SPAR) models are a set of linked fault tree/event tree PRA models that have been used by the Nuclear Regulatory Commission (NRC) to evaluate the risk of operations at U.S. nuclear power plants since 1990s. The models use the Systems Analysis Programs for Hands-on Integrated Reliability Evaluations (SAPHIRE) code developed by the NRC and Idaho National Laboratory (INL). Currently Version 8, SAPHIRE is a powerful software with advanced features to perform separated or integrated Level 1, Level 2, internal events, external events, at-power, and low power shutdown PRA [1]. One of its features is the availability of three different approaches to model the success branch of a top event in event tree: delete term, complement of system logic, and developed event. However, improper choosing and modeling success branch might yield unexpected and incorrect results. This paper will discuss the two most often used success branch modeling approaches, delete term and developed event, and provide recommendations for using proper approaches in different models. A potential SAPHIRE code enhancement is also proposed to address the adverse impact brought by the developed event approach.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2014

The Wind Forecast Improvement Project (WFIP): A Public/Private Partnership for Improving Short Term Wind Energy Forecasts and Quantifying the Benefits of Utility Operations. The Southern Study Area, Final Report

This Final Report presents a comprehensive description, findings, and conclusions for the Wind Forecast Improvement Project (WFIP) -- Southern Study Area (SSA) work led by AWS Truepower (AWST). This multi-year effort, sponsored by the Department of Energy (DOE) and National Oceanographic and Atmospheric Administration (NOAA), focused on improving short-term (15-minute - 6 hour) wind power production forecasts through the deployment of an enhanced observation network of surface and remote sensing instrumentation and the use of a state-of-the-art forecast modeling system. Key findings from the SSA modeling and forecast effort include: 1. The AWST WFIP modeling system produced an overall 10 - 20% improvement in wind power production forecasts over the existing Baseline system, especially during the first three forecast hours; 2. Improvements in ramp forecast skill, particularly for larger up and down ramps; 3. The AWST WFIP data denial experiments showed mixed results in the forecasts incorporating the experimental network instrumentation; however, ramp forecasts showed significant benefit from the additional observations, indicating that the enhanced observations were key to the model systems’ ability to capture phenomena responsible for producing large short-term excursions in power production; 4. The OU CAPS ARPS simulations showed that the additional WFIP instrument data had a small impact on their 3-km forecasts that lasted for the first 5-6 hours, and increasing the vertical model resolution in the boundary layer had a greater impact, also in the first 5 hours; and 5. The TTU simulations were inconclusive as to which assimilation scheme (3DVAR versus EnKF) provided better forecasts, and the additional observations resulted in some improvement to the forecasts in the first 1 - 3 hours.

17 WIND ENERGY↗
DOE OSTI2014

The Great Plains Wind Power Test Facility

This multi-year, multi-faceted project was focused on the continued development of a nationally-recognized facility for the testing, characterization, and improvement of grid-connected wind turbines, integrated wind-water desalination systems, and related educational and outreach topics. The project involved numerous faculty and graduate students from various engineering departments, as well as others from the departments of Geosciences (in particular the Atmospheric Science Group) and Economics. It was organized through the National Wind Institute (NWI), which serves as an intellectual hub for interdisciplinary and transdisciplinary research, commercialization and education related to wind science, wind energy, wind engineering and wind hazard mitigation at Texas Tech University (TTU). Largely executed by an academic based team, the project resulted in approximately 38 peer-reviewed publications, 99 conference presentations, the development/expansion of several experimental facilities, and two provisional patents.

17 WIND ENERGY↗