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Sample records for radar wind profiler

  1. ARM: 915-MHz Radar Wind Profiler: Wind Moments, operating in...

    Office of Scientific and Technical Information (OSTI)

    915-MHz Radar Wind Profiler: Wind Moments, operating in low power mode Title: ARM: 915-MHz Radar Wind Profiler: Wind Moments, operating in low power mode 915-MHz Radar Wind ...

  2. ARM: 1290-MHz Radar Wind Profiler, precipitation moments data...

    Office of Scientific and Technical Information (OSTI)

    1290-MHz Radar Wind Profiler, precipitation moments data Title: ARM: 1290-MHz Radar Wind Profiler, precipitation moments data 1290-MHz Radar Wind Profiler, precipitation moments ...

  3. Merged and corrected 915 MHz Radar Wind Profiler moments (Dataset...

    Office of Scientific and Technical Information (OSTI)

    Merged and corrected 915 MHz Radar Wind Profiler moments Title: Merged and corrected 915 MHz Radar Wind Profiler moments The radar wind profiler (RWP) present at the SGP central ...

  4. ARM: 1290-MHz Beam-Steered Radar Wind Profiler: Precipitation...

    Office of Scientific and Technical Information (OSTI)

    Precipitation Datastream Title: ARM: 1290-MHz Beam-Steered Radar Wind Profiler: Precipitation Datastream 1290-MHz Beam-Steered Radar Wind Profiler: Precipitation Datastream ...

  5. ARM: 1290-MHz Beam-Steered Radar Wind Profiler: Wind and Moment...

    Office of Scientific and Technical Information (OSTI)

    Wind and Moment Averages Title: ARM: 1290-MHz Beam-Steered Radar Wind Profiler: Wind and Moment Averages 1290-MHz Beam-Steered Radar Wind Profiler: Wind and Moment Averages ...

  6. ARM: Spectra from 1290-MHz Beam-Steered Radar Wind Profiler ...

    Office of Scientific and Technical Information (OSTI)

    wind mode Title: ARM: Spectra from 1290-MHz Beam-Steered Radar Wind Profiler (BSRWP) operating in low-low wind mode Spectra from 1290-MHz Beam-Steered Radar Wind Profiler (BSRWP) ...

  7. ARM: Spectra from 1290-MHz Beam-Steered Radar Wind Profiler ...

    Office of Scientific and Technical Information (OSTI)

    wind mode Title: ARM: Spectra from 1290-MHz Beam-Steered Radar Wind Profiler (BSRWP) operating in low wind mode Spectra from 1290-MHz Beam-Steered Radar Wind Profiler (BSRWP) ...

  8. ARM: Spectra from 1290-MHz Beam-Steered Radar Wind Profiler ...

    Office of Scientific and Technical Information (OSTI)

    Title: ARM: Spectra from 1290-MHz Beam-Steered Radar Wind Profiler (BSRWP) operating in low-low precipitation mode Spectra from 1290-MHz Beam-Steered Radar Wind Profiler (BSRWP) ...

  9. ARM: Spectra from 1290-MHz Beam-Steered Radar Wind Profiler ...

    Office of Scientific and Technical Information (OSTI)

    Title: ARM: Spectra from 1290-MHz Beam-Steered Radar Wind Profiler (BSRWP) operating in low precipitation mode Spectra from 1290-MHz Beam-Steered Radar Wind Profiler (BSRWP) ...

  10. 915-MHz Radar Wind Profiler (915RWP) Handbook

    SciTech Connect (OSTI)

    Coulter, R

    2005-01-01

    The 915 MHz radar wind profiler/radio acoustic sounding system (RWP/RASS) measures wind profiles and backscattered signal strength between (nominally) 0.1 km and 5 km and virtual temperature profiles between 0.1 km and 2.5 km. It operates by transmitting electromagnetic energy into the atmosphere and measuring the strength and frequency of backscattered energy. Virtual temperatures are recovered by transmitting an acoustic signal vertically and measuring the electromagnetic energy scattered from the acoustic wavefront. Because the propagation speed of the acoustic wave is proportional to the square root of the virtual temperature of the air, the virtual temperature can be recovered by measuring the Doppler shift of the scattered electromagnetic wave.

  11. ARM: Spectra from 1290-MHz Beam-Steered Radar Wind Profiler (BSRWP) operating in low-low precipitation mode

    SciTech Connect (OSTI)

    Timothy Martin; Paytsar Muradyan; Richard Coulter

    2014-01-28

    Spectra from 1290-MHz Beam-Steered Radar Wind Profiler (BSRWP) operating in low-low precipitation mode

  12. Merged and corrected 915 MHz Radar Wind Profiler moments

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    Jonathan Helmus,Virendra Ghate, Frederic Tridon

    2014-06-25

    The radar wind profiler (RWP) present at the SGP central facility operates at 915 MHz and was reconfigured in early 2011, to collect key sets of measurements for precipitation and boundary layer studies. The RWP is configured to run in two main operating modes: a precipitation (PR) mode with frequent vertical observations and a boundary layer (BL) mode that is similar to what has been traditionally applied to RWPs. To address issues regarding saturation of the radar signal, range resolution and maximum range, the RWP PR mode is set to operate with two different pulse lengths, termed as short pulse (SP) and long pulse (LP). Please refer to the RWP handbook (Coulter, 2012) for further information. Data from the RWP PR-SP and PR-LP modes have been extensively used to study deep precipitating clouds, especially their dynamical structure as the RWP data does not suffer from signal attenuation during these conditions (Giangrande et al., 2013). Tridon et al. (2013) used the data collected during the Mid-latitude Continental Convective Cloud Experiment (MC3E) to improve the estimation of noise floor of the RWP recorded Doppler spectra.

  13. ARM - PI Product - Merged and corrected 915 MHz Radar Wind Profiler...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    ProductsMerged and corrected 915 MHz Radar Wind Profiler moments ARM Data Discovery Browse Data Comments? We would love to hear from you Send us a note below or call us at ...

  14. ARM - Field Campaign - Radar Wind Profiler for Cloud Forecasting at BNL

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    govCampaignsRadar Wind Profiler for Cloud Forecasting at BNL Campaign Links Field Campaign Report ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Campaign : Radar Wind Profiler for Cloud Forecasting at BNL 2013.07.15 - 2015.08.06 Lead Scientist : Michael Jensen For data sets, see below. Abstract In support of recent activities funded by the DOE Energy Efficiency and Renewable Energy (EERE) to produce short-term

  15. Radar Wind Profiler for Cloud Forecasting at Brookhaven National...

    Office of Scientific and Technical Information (OSTI)

    forecasts for solar-energy applications and 2) to provide vertical profiling capabilities for the study of dynamics (i.e., vertical velocity) and hydrometeors in winter storms. ...

  16. Installation and Initial Operation of DOE's 449-MHz Wind Profiling Radars on the U.S. West Coast

    SciTech Connect (OSTI)

    Flaherty, Julia E.; Shaw, William J.; Morris, Victor R.; Wilczak, J. M.; White, A. B.; Ayers, Tom; Jordan, Jim; King, Clark W.

    2015-10-30

    The U.S. Department of Energy (DOE), in collaboration with the National Oceanic and Atmospheric Administration (NOAA), has recently completed the installation of three new wind profiling radars on the Washington and Oregon coasts. These systems operate at a frequency of 449 MHz and provide mean wind profiles to a height of roughly 8 km, with the maximum measurement height depending on time-varying atmospheric conditions. This is roughly half the depth of the troposphere at these latitudes. Each system is also equipped with a radio acoustic sounding system (RASS), which provides a measure of the temperature profile to heights of approximately 2 km. Other equipment deployed alongside the radar includes a surface meteorological station and GPS for column water vapor. This project began in fiscal year 2014, starting with equipment procurements and site selection. In addition, environmental reviews, equipment assembly and testing, site access agreements, and infrastructure preparations have been performed. Finally, with equipment deployment with data collection and dissemination, the primary tasks of this project have been completed. The three new wind profiling radars have been deployed at airports near Coos Bay, OR, and Astoria, OR, and at an industrial park near Forks, WA. Data are available through the NOAA Earth Systems Research Laboratory Data Display website, and will soon be made available through the DOE Atmosphere to Electrons data archive and portal as well.

  17. Federal Interagency Wind Turbine Radar Interference Mitigation...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Federal Interagency Wind Turbine Radar Interference Mitigation Strategy Federal Interagency Wind Turbine Radar Interference Mitigation Strategy Cover of the Federal Interagency ...

  18. Federal Interagency Wind Turbine Radar Interference Mitigation...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Interagency Wind Turbine Radar Interference Mitigation Strategy January 2016 This report ... First, the authors would like to thank the entire Wind Turbine Radar Interference Working ...

  19. Federal Interagency Wind Turbine Radar Interference Mitigation...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Interagency Wind Turbine Radar Interference Mitigation Strategy January 2016 This report ... from the advice and comments of two wind industry and trade association ...

  20. Wind Turbine Radar Interference Mitigation Working Group Releases...

    Broader source: Energy.gov (indexed) [DOE]

    Wind Turbine Radar Interference Mitigation Working Group to address these challenges. This new report lays out the plan for how the working group will address wind turbine radar ...

  1. INTERAGENCY FIELD TEST & EVALUATION OF WIND TURBINE - RADAR INTERFEREN...

    Office of Environmental Management (EM)

    INTERAGENCY FIELD TEST & EVALUATION OF WIND TURBINE - RADAR INTERFERENCE MITIGATION TECHNOLOGIES INTERAGENCY FIELD TEST & EVALUATION OF WIND TURBINE - RADAR INTERFERENCE MITIGATION ...

  2. Wind Turbine Radar Interference Mitigation Working Group Releases New Report

    Office of Energy Efficiency and Renewable Energy (EERE)

    While wind energy presents many benefits, spinning wind turbines can interfere with weather, air traffic control, and air surveillance radar systems. As advances in wind technology enable turbines...

  3. Siting: Wind Turbine/Radar Interference Mitigation (TSPEAR &...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    ... Wind TurbineRadar Interference Mitigation (TSPEAR & IFT&E) HomeStationary PowerEnergy Conversion EfficiencyWind EnergySiting and Barrier MitigationSiting: Wind TurbineRadar ...

  4. Federal Interagency Wind Turbine Radar Interference Mitigation Strategy

    Broader source: Energy.gov [DOE]

    Wind development located within the line of sight of radar systems can cause clutter and interference, which at some radars has resulted in significant performance degradation. As wind turbines...

  5. Texas Tech University mobile doppler radars provide unique wind...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    ... Texas Tech University mobile doppler radars provide unique wind measurements to multi-instrument DOE Field Campaign HomeWind Energy, Wind NewsTexas Tech University mobile doppler ...

  6. Radar-cross-section reduction of wind turbines. part 1.

    SciTech Connect (OSTI)

    Brock, Billy C.; Loui, Hung; McDonald, Jacob J.; Paquette, Joshua A.; Calkins, David A.; Miller, William K.; Allen, Steven E.; Clem, Paul Gilbert; Patitz, Ward E.

    2012-03-05

    In recent years, increasing deployment of large wind-turbine farms has become an issue of growing concern for the radar community. The large radar cross section (RCS) presented by wind turbines interferes with radar operation, and the Doppler shift caused by blade rotation causes problems identifying and tracking moving targets. Each new wind-turbine farm installation must be carefully evaluated for potential disruption of radar operation for air defense, air traffic control, weather sensing, and other applications. Several approaches currently exist to minimize conflict between wind-turbine farms and radar installations, including procedural adjustments, radar upgrades, and proper choice of low-impact wind-farm sites, but each has problems with limited effectiveness or prohibitive cost. An alternative approach, heretofore not technically feasible, is to reduce the RCS of wind turbines to the extent that they can be installed near existing radar installations. This report summarizes efforts to reduce wind-turbine RCS, with a particular emphasis on the blades. The report begins with a survey of the wind-turbine RCS-reduction literature to establish a baseline for comparison. The following topics are then addressed: electromagnetic model development and validation, novel material development, integration into wind-turbine fabrication processes, integrated-absorber design, and wind-turbine RCS modeling. Related topics of interest, including alternative mitigation techniques (procedural, at-the-radar, etc.), an introduction to RCS and electromagnetic scattering, and RCS-reduction modeling techniques, can be found in a previous report.

  7. Mitigating Wind-Radar Interference | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Mitigating Wind-Radar Interference Mitigating Wind-Radar Interference April 1, 2013 - 12:54pm Addthis This is an excerpt from the First Quarter 2013 edition of the Wind Program R&D Newsletter. The U.S. Department of Energy (DOE) and federal agency partners recently completed the final operational field test in a 2-year initiative to accelerate the deployment of the most promising new technologies for mitigating radar interference caused by the physical and electromagnetic effects of wind

  8. Evaluation of Single-Doppler Radar Wind Retrievals in Flat and Complex Terrain

    SciTech Connect (OSTI)

    Newsom, Rob K.; Berg, Larry K.; Pekour, Mikhail S.; Fast, Jerome D.; Xu, Qin; Zhang, Pengfei; Yang, Qing; Shaw, William J.; Flaherty, Julia E.

    2014-08-01

    The accuracy of winds derived from NEXRAD level II data is assessed by comparison with independent observations from 915 MHz radar wind profilers. The evaluation is carried out at two locations with very different terrain characteristics. One site is located in an area of complex terrain within the State Line Wind Energy Center in northeast Oregon. The other site is located in an area of flat terrain on the east-central Florida coast. The National Severe Storm Laboratorys 2DVar algorithm is used to retrieve wind fields from the KPDT (Pendleton OR) and KMLB (Melbourne FL) NEXRAD radars. Comparisons between the 2DVar retrievals and the radar profilers were conducted over a period of about 6 months and at multiple height levels at each of the profiler sites. Wind speed correlations at most observation height levels fell in the range from 0.7 to 0.8, indicating that the retrieved winds followed temporal fluctuations in the profiler-observed winds reasonably well. The retrieved winds, however, consistently exhibited slow biases in the range of1 to 2 ms-1. Wind speed difference distributions were broad with standard deviations in the range from 3 to 4 ms-1. Results from the Florida site showed little change in the wind speed correlations and difference standard deviations with altitude between about 300 and 1400 m AGL. Over this same height range, results from the Oregon site showed a monotonic increase in the wind speed correlation and a monotonic decrease in the wind speed difference standard deviation with increasing altitude. The poorest overall agreement occurred at the lowest observable level (~300 m AGL) at the Oregon site, where the effects of the complex terrain were greatest.

  9. ARM: X-Band Scanning ARM Cloud Radar (XSACR) Cross-Wind RHI Scan...

    Office of Scientific and Technical Information (OSTI)

    Cross-Wind RHI Scan Title: ARM: X-Band Scanning ARM Cloud Radar (XSACR) Cross-Wind RHI Scan X-Band Scanning ARM Cloud Radar (XSACR) Cross-Wind RHI Scan Authors: Dan Nelson ; Joseph ...

  10. Federal Interagency Wind Turbine Radar Interference Mitigation Strategy

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Interagency Wind Turbine Radar Interference Mitigation Strategy January 2016 This report is being disseminated by the U.S. Department of Energy (DOE). As such, this document was prepared in compliance with Section 515 of the Treasury and General Government Appropriations Act for fiscal year 2001 (public law 106-554) and information quality guidelines issued by DOE. Though this report does not constitute "influential" information, as that term is defined in DOE's information quality

  11. 915 MHz Wind Profiler for Cloud Forecasting at Brookhaven National...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Wind Profiler for Cloud Forecasting at Brookhaven National Laboratory M Jensen MJ ... Wind Profiler for Cloud Forecasting at Brookhaven National Laboratory M Jensen, ...

  12. 915 MHz Wind Profiler for Cloud Forecasting at Brookhaven National...

    Office of Scientific and Technical Information (OSTI)

    U.S. DEPARTMENT OF HP IENERGY Office of Science DOESC-ARM-15-024 915-MHz Wind Profiler ... M Jensen et al., March 2016, DOESC-ARM-15-024 915-MHz Wind Profiler for Cloud Forecasting ...

  13. ARM: ABLE: minisodar (mini - sound det. and ranging) wind profiles...

    Office of Scientific and Technical Information (OSTI)

    ABLE: minisodar (mini - sound det. and ranging) wind profiles, 100-200 m, avg Title: ARM: ABLE: minisodar (mini - sound det. and ranging) wind profiles, 100-200 m, avg ABLE: ...

  14. Sandia National Laboratories Develops Tool for Evaluating Wind Turbine-Radar Impacts

    Broader source: Energy.gov [DOE]

    The TSPEAR toolkit supports energy developers that wish to design, analyze, track the progress of wind energy projects. Initially designed to support wind energy development by assessing the interaction between turbines and constraining factors, such as the NAS radar systems, TSPEAR is partially populated with information from existing databases and can integrate custom models and tools used throughout the development process.

  15. Siting: Wind Turbine/Radar Interference Mitigation (TSPEAR &...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Stationary Power Energy Conversion Efficiency Solar Energy Wind Energy Water Power ... Laboratory PV Regional Test Centers Scaled Wind Farm Technology Facility Climate & Earth ...

  16. IMPROVED CAPABILITIES FOR SITING WIND FARMS AND MITIGATING IMPACTS ON RADAR OBSERVATIONS

    SciTech Connect (OSTI)

    Chiswell, S.

    2010-01-15

    The development of efficient wind energy production involves challenges in technology and interoperability with other systems critical to the national mission. Wind turbines impact radar measurements as a result of their large reflectivity cross section as well as through the Doppler phase shift of their rotating blades. Wind farms can interfere with operational radar in multiple contexts, with degradation impacts on: weather detection such as tornado location, wind shear, and precipitation monitoring; tracking of airplanes where air traffic control software can lose the tracks of aircraft; and in identification of other low flying targets where a wind farm located close to a border might create a dead zone for detecting intruding objects. Objects in the path of an electromagnetic wave affect its propagation characteristics. This includes actual blockage of wave propagation by large individual objects and interference in wave continuity due to diffraction of the beam by individual or multiple objects. As an evolving industry, and the fastest growing segment of the energy sector, wind power is poised to make significant contributions in future energy generation requirements. The ability to develop comprehensive strategies for designing wind turbine locations that are mutually beneficial to both the wind industry that is dependent on production, and radar sites which the nation relies on, is critical to establishing reliable and secure wind energy. The mission needs of the Department of Homeland Security (DHS), Department of Defense (DOD), Federal Aviation Administration (FAA), and National Oceanographic and Atmospheric Administration (NOAA) dictate that the nation's radar systems remain uninhibited, to the maximum extent possible, by man-made obstructions; however, wind turbines can and do impact the surveillance footprint for monitoring airspace both for national defense as well as critical weather conditions which can impact life and property. As a result, a

  17. INTERAGENCY FIELD TEST & EVALUATION OF WIND TURBINE – RADAR INTERFERENCE MITIGATION TECHNOLOGIES

    Broader source: Energy.gov [DOE]

    These documents include a final report on the Interagency Field Test & Evaluation (IFT&E) program and summaries of three field tests designed to measure the impact of wind turbines on current air surveillance radars and the effectiveness of private sector technologies in mitigating that interference.

  18. IFT&E Industry Report Wind Turbine-Radar Interference Test Summary.

    SciTech Connect (OSTI)

    Karlson, Benjamin; LeBlanc, Bruce Philip; Minster, David G; Estill, Milford; Miller, Bryan Edward; Busse, Franz; Keck, Chris; Sullivan, Jonathan; Brigada, David; Parker, Lorri; Younger, Richard; Biddle, Jason

    2014-10-01

    Wind turbines have grown in size and capacity with today's average turbine having a power capacity of around 1.9 MW, reaching to heights of over 495 feet from ground to blade tip, and operating with speeds at the tip of the blade up to 200 knots. When these machines are installed within the line-of-sight of a radar system, they can cause significant clutter and interference, detrimentally impacting the primary surveillance radar (PSR) performance. The Massachusetts Institute of Technology's Lincoln Laboratory (MIT LL) and Sandia National Laboratories (SNL) were co-funded to conduct field tests and evaluations over two years in order to: I. Characterize the impact of wind turbines on existing Program-of-Record (POR) air surveillance radars; II. Assess near-term technologies proposed by industry that have the potential to mitigate the interference from wind turbines on radar systems; and III. Collect data and increase technical understanding of interference issues to advance development of long-term mitigation strategies. MIT LL and SNL managed the tests and evaluated resulting data from three flight campaigns to test eight mitigation technologies on terminal (short) and long-range (60 nmi and 250 nmi) radar systems. Combined across the three flight campaigns, more than 460 of hours of flight time were logged. This paper summarizes the Interagency Field Test & Evaluation (IFT&E) program and publicly- available results from the tests. It will also discuss the current wind turbine-radar interference evaluation process within the government and a proposed process to deploy mitigation technologies.

  19. MOWII Webinar on Laufer Wind: Radar-Activated Obstruction Lighting

    Broader source: Energy.gov [DOE]

    Join the Maine Ocean and Wind Industry Initiative (MOWII) for a webinar exploring Laufer Wind’s Aircraft Detection System, designed to turn aviation warning lights on only when aircraft are in the...

  20. Making Wind Energy Predictable: New Profilers Provide Hourly Forecasts |

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Department of Energy Making Wind Energy Predictable: New Profilers Provide Hourly Forecasts Making Wind Energy Predictable: New Profilers Provide Hourly Forecasts May 11, 2016 - 6:48pm Addthis Balancing the power grid is an art-or at least a scientific study in chaos-and the Energy Department is hoping wind energy can take a greater role in the act. Yet, the intermittency of wind-sometimes it's blowing, sometimes it's not-makes adding it smoothly to the nation's electrical grid a challenge.

  1. Upstream Measurements of Wind Profiles with Doppler Lidar for Improved Wind Energy Integration

    SciTech Connect (OSTI)

    Rodney Frehlich

    2012-10-30

    New upstream measurements of wind profiles over the altitude range of wind turbines will be produced using a scanning Doppler lidar. These long range high quality measurements will provide improved wind power forecasts for wind energy integration into the power grid. The main goal of the project is to develop the optimal Doppler lidar operating parameters and data processing algorithms for improved wind energy integration by enhancing the wind power forecasts in the 30 to 60 minute time frame, especially for the large wind power ramps. Currently, there is very little upstream data at large wind farms, especially accurate wind profiles over the full height of the turbine blades. The potential of scanning Doppler lidar will be determined by rigorous computer modeling and evaluation of actual Doppler lidar data from the WindTracer system produced by Lockheed Martin Coherent Technologies, Inc. of Louisville, Colorado. Various data products will be investigated for input into numerical weather prediction models and statistically based nowcasting algorithms. Successful implementation of the proposed research will provide the required information for a full cost benefit analysis of the improved forecasts of wind power for energy integration as well as the added benefit of high quality wind and turbulence information for optimal control of the wind turbines at large wind farms.

  2. Comparison of optically measured and radar-derived horizontal neutral winds. Master's thesis

    SciTech Connect (OSTI)

    Christie, M.S.

    1990-01-01

    Nighttime thermospheric winds for Sondrestrom, Greenland from 11 nights between 1983 and 1988, have been compared to learn about the O(+)-O collision cross section and the high-latitude atomic oxygen density. The horizontal winds in the magnetic meridian were derived indirectly from incoherent-scatter radar (ISR) measurements on ion velocities antiparallel to the magnetic field and directly from Fabry-Perot interferometer (FPI) measurements of Doppler shifts of the (6300-A) emission of atomic oxygen. In deriving the radar winds, the O(+)-O collision cross section, was scaled by a factor of f what was varied from 0.5 to 5.1. On the basis of several arguments the altitude of the 6300-A emission was assumed to be 230 km. The best agreement between the ISR and FPI winds was obtained when f was increased substantially, to between 1.7 and 3.4. If the average peak emission altitude were higher, these factors would be larger; if it were lower, they would be somewhat smaller. However, if the average altitude were substantially lower it would have been more difficult to have obtained agreement between the two techniques.

  3. Measurements of Wind and Turbulence Profiles with Scanning Doppler Lidar for Wind Energy Applications

    SciTech Connect (OSTI)

    Frehlich, R.; Kelley, N.

    2008-03-01

    High-quality profiles of mean and turbulent statistics of the wind field upstream of a wind farm can be produced using a scanning Doppler lidar. Careful corrections for the spatial filtering of the wind field by the lidar pulse produce turbulence estimates equivalent to point sensors but with the added advantage of a larger sampling volume to increase the statistical accuracy of the estimates. For a well-designed lidar system, this permits accurate estimates of the key turbulent statistics over various subdomains and with sufficiently short observation times to monitor rapid changes in conditions. These features may be ideally suited for optimal operation of wind farms and also for improved resource assessment of potential sites.

  4. On the measurement of wind speeds in tornadoes with a portable CW/FM-CW Doppler radar

    SciTech Connect (OSTI)

    Bluestein, H.B. . School of Meteorology); Unruh, W.P. )

    1991-01-01

    Both the formation mechanism and structure of tornadoes are not yet well understood. The Doppler radar is probably the best remote-sensing instrument at present for determining the wind field in tornadoes. Although much has been learned about the non-supercell tornado from relatively close range using Doppler radars at fixed sites, close-range measurements in supercell tornadoes are relatively few. Doppler radar can increase significantly the number of high-resolution, sub-cloud base measurements of both the tornado vortex and its parent vortex in supercells, with simultaneous visual documentation. The design details and operation of the CW/FM-CW Doppler radar developed at the Los Alamos National Laboratory and used by storm-intercept teams at the Univ. of Oklahoma are described elsewhere. The radar transmits 1 W at 3 cm, and can be switched back and forth between CW and FM-CW modes. In the FM-CW mode the sweep repetition frequency is 15.575 kHz and the sweep width 1.9 MHz; the corresponding maximum unambiguous range and velocity, and range resolution are 5 km, {plus minus} 115 m s{sup {minus}1}, and 78 m respectively. The bistatic antennas, which have half-power beamwidths of 5{degree}, are easily pointed wit the aid of a boresighted VCR. FM-CW Data are recorded on the VCR, while voice documentation is recorded on the audio tape; video is recorded on another VCR. The radar and antennas are easily mounted on a tripod, and can be set up by three people in a minute or two. The purpose of this paper is to describe the signal processing techniques used to determine the Doppler spectrum in the FM-CW mode and a method of its interpretation in real time, and to present data gathered in a tornadic storm in 1990. 15 refs., 7 figs.

  5. Wind News

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    ... laboratory mission technologies and ... By admin| ... participating in the Wind Turbine Radar Interference ... Association AWEA WindPower 2015 event in Orlando, Florida. ...

  6. Cloud Effects on Radiative Heating Rate Profiles over Darwin using ARM and A-train Radar/Lidar Observations

    SciTech Connect (OSTI)

    Thorsen, Tyler J.; Fu, Qiang; Comstock, Jennifer M.

    2013-06-11

    Observations of clouds from the ground-based U.S. Department of Energy Atmospheric Radiation Measurement program (ARM) and satellite-based A-train are used to compute cloud radiative forcing profiles over the ARM Darwin, Australia site. Cloud properties are obtained from both radar (the ARM Millimeter Cloud Radar (MMCR) and the CloudSat satellite in the A-train) and lidar (the ARM Micropulse lidar (MPL) and the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite in the A-train) observations. Cloud microphysical properties are taken from combined radar and lidar retrievals for ice clouds and radar only or lidar only retrievals for liquid clouds. Large, statistically significant differences of up to 1.43 K/day exist between the mean ARM and A-train net cloud radiative forcing profiles. The majority of the difference in cloud radiative forcing profiles is shown to be due to a large difference in the cloud fraction above 12 km. Above this altitude the A-train cloud fraction is significantly larger because more clouds are detected by CALIPSO than by the ground-based MPL. It is shown that the MPL is unable to observe as many high clouds as CALIPSO due to being more frequently attenuated and a poorer sensitivity even in otherwise clear-sky conditions. After accounting for cloud fraction differences and instrument sampling differences due to viewing platform we determined that differences in cloud radiative forcing due to the retrieved ice cloud properties is relatively small. This study demonstrates that A-train observations are better suited for the calculation cloud radiative forcing profiles. In addition, we find that it is necessary to supplement CloudSat with CALIPSO observations to obtain accurate cloud radiative forcing profiles since a large portion of clouds at Darwin are detected by CALIPSO only.

  7. Making Wind Energy Predictable: New Profilers Provide Hourly...

    Broader source: Energy.gov (indexed) [DOE]

    It is possible, however, to get better at predicting it, which is what the Energy Department's Wind Forecast Improvement Project (WFIP) seeks to accomplish. Under the second phase ...

  8. Depth profiling analysis of solar wind helium collected in diamond-like carbon film from Genesis

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Bajo, Ken-ichi; Olinger, Chad T.; Jurewicz, Amy J.G.; Burnett, Donald S.; Sakaguchi, Isao; Suzuki, Taku; Itose, Satoru; Ishihara, Morio; Uchino, Kiichiro; Wieler, Rainer; et al

    2015-10-01

    The distribution of solar-wind ions in Genesis mission collectors, as determined by depth profiling analysis, constrains the physics of ion solid interactions involving the solar wind. Thus, they provide an experimental basis for revealing ancient solar activities represented by solar-wind implants in natural samples. We measured the first depth profile of ⁴He in a collector; the shallow implantation (peaking at <20 nm) required us to use sputtered neutral mass spectrometry with post-photoionization by a strong field. The solar wind He fluence calculated using depth profiling is ~8.5 x 10¹⁴ cm⁻². The shape of the solar wind ⁴He depth profile ismore » consistent with TRIM simulations using the observed ⁴He velocity distribution during the Genesis mission. It is therefore likely that all solar-wind elements heavier than H are completely intact in this Genesis collector and, consequently, the solar particle energy distributions for each element can be calculated from their depth profiles. Ancient solar activities and space weathering of solar system objects could be quantitatively reproduced by solar particle implantation profiles.« less

  9. Imaging doppler lidar for wind turbine wake profiling

    SciTech Connect (OSTI)

    Bossert, David J.

    2015-11-19

    An imaging Doppler lidar (IDL) enables the measurement of the velocity distribution of a large volume, in parallel, and at high spatial resolution in the wake of a wind turbine. Because the IDL is non-scanning, it can be orders of magnitude faster than conventional coherent lidar approaches. Scattering can be obtained from naturally occurring aerosol particles. Furthermore, the wind velocity can be measured directly from Doppler shifts of the laser light, so the measurement can be accomplished at large standoff and at wide fields-of-view.

  10. Siting: Wind Turbine/Radar Interference Mitigation (TSPEAR & IFT&E)

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Sandia Energy Energy Search Icon Sandia Home Locations Contact Us Employee Locator Energy & Climate Secure & Sustainable Energy Future Stationary Power Energy Conversion Efficiency Solar Energy Wind Energy Water Power Supercritical CO2 Geothermal Natural Gas Safety, Security & Resilience of the Energy Infrastructure Energy Storage Nuclear Power & Engineering Grid Modernization Battery Testing Nuclear Energy Defense Waste Management Programs Advanced Nuclear Energy Nuclear Energy

  11. ARM - Field Campaign - 915 MHz Wind Profiler for Cloud Forecasting at BNL

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    govCampaigns915 MHz Wind Profiler for Cloud Forecasting at BNL Campaign Links Field Campaign Report ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Campaign : 915 MHz Wind Profiler for Cloud Forecasting at BNL 2011.05.31 - 2012.05.31 Lead Scientist : Michael Jensen For data sets, see below. Abstract In support of the installation of a 37 MW solar array on the grounds of Brookhaven National Laboratory (BNL), a study

  12. Temporal variability of the trade wind inversion: Measured with a boundary layer vertical profiler. Master's thesis

    SciTech Connect (OSTI)

    Grindinger, C.M.

    1992-05-01

    This study uses Hawaiian Rainband Project (HaRP) data, from the summer of 1991, to show a boundary layer wind profiler can be used to measure the trade wind inversion. An algorithm has been developed for the profiler that objectively measures the depth of the moist oceanic boundary layer. The Hilo inversion, measured by radiosonde, is highly correlated with the moist oceanic boundary layer measured by the profiler at Paradise Park. The inversion height on windward Hawaii is typically 2253 + or - 514 m. The inversion height varies not only on a daily basis, but on less than an hourly basis. It has a diurnal, as well as a three to four day cycle. There appears to be no consistent relationship between inversion height and precipitation. Currently, this profiler is capable of making high frequency (12 minute) measurements of the inversion base variation, as well as other features.

  13. Description of the Columbia Basin Wind Energy Study (CBWES)

    SciTech Connect (OSTI)

    Berg, Larry K.; Pekour, Mikhail S.; Nelson, Danny A.

    2012-10-01

    The purpose of this Technical Report is to provide background information about the Columbia Basin Wind Energy Study (CBWES). This study, which was supported by the U.S. Department of Energy’s Wind and Water Power Program, was conducted from 16 November 2010 through 21 March 2012 at a field site in northeastern Oregon. The primary goal of the study was to provide profiles of wind speed and wind direction over the depth of the boundary layer in an operating wind farm located in an area of complex terrain. Measurements from propeller and vane anemometers mounted on a 62 m tall tower, Doppler Sodar, and Radar Wind Profiler were combined into a single data product to provide the best estimate of the winds above the site during the first part of CBWES. An additional goal of the study was to provide measurements of Turbulence Kinetic Energy (TKE) near the surface. To address this specific goal, sonic anemometers were mounted at two heights on the 62 m tower on 23 April 2011. Prior to the deployment of the sonic anemometers on the tall tower, a single sonic anemometer was deployed on a short tower 3.1 m tall that was located just to the south of the radar wind profiler. Data from the radar wind profiler, as well as the wind profile data product are available from the Atmospheric Radiation Measurements (ARM) Data Archive (http://www.arm.gov/data/campaigns). Data from the sonic anemometers are available from the authors.

  14. doe sc arm 16 025 The Radar Wind Profiler for Cloud Forecasting...

    Office of Scientific and Technical Information (OSTI)

    National Laboratory CONUS Continental United States DOE U.S. Department of Energy GoAmazon 201415 Green Ocean Amazon 201415 IR infrared km kilometer LI lifted index MHz megahertz ...

  15. ARM: Millimeter Wavelength Cloud Radar (MMCR): monitoring data...

    Office of Scientific and Technical Information (OSTI)

    Country of Publication: United States Availability: ORNL Language: English Subject: 54 Environmental Sciences Horizontal wind; Radar Doppler; Radar reflectivity; Vertical velocity ...

  16. Sandia Energy - Sandia Develops Tool to Evaluate Wind-Turbine...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Radar Impacts Previous Next Sandia Develops Tool to Evaluate Wind-TurbineRadar Impacts Our nation relies upon a network of radars across the country to support the...

  17. Examination of objective analysis precision using wind profiler and radiosonde network data

    SciTech Connect (OSTI)

    Mace, G.G.; Ackerman, T.P.

    1996-04-01

    One of the principal research strategies that has emerged from the science team of the Atmospheric Radiation Measurement (ARM) Program is the use of a single column model (SCM). The basic assumption behind the SCM approach is that a cloud and radiation parameterization embedded in a general circulation model can be effectively tested and improved by extracting that column parameterization from the general circulation model and then driving this single column at the lateral boundaries of the column with diagnosed large-scale atmospheric forcing. A second and related assumption is that the large-scale atmospheric state, and hence the associated forcing, can be characterized directly from observations. One of the primary reasons that the Southern Great Plains (SGP) site is located in Lamont, Oklahoma, is because Lamont is at the approximate center of the NOM Wind Profiler Demonstration Array (WPDA). The assumption was that hourly average wind profiles provided by the 7 wind profilers (one Lamont and six surrounding it in a hexagon) coupled with radiosonde launches every three hours at 5 sites (Lamont plus four of the six profiler locations forming the hexagon) would be sufficient to characterize accurately the large-scale forcing at the site and thereby provide the required forcing for the SCM. The goal of this study was to examine these three assumptions.

  18. ARM - Midlatitude Continental Convective Clouds Experiment (MC3E): Multi-Frequency Profilers, S-band Radar (williams-s_band)

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    Williams, Christopher

    2012-11-06

    This data was collected by the NOAA 449-MHz and 2.8-GHz profilers in support of the Department of Energy (DOE) and NASA sponsored Mid-latitude Continental Convective Cloud Experiment (MC3E). The profiling radars were deployed in Northern Oklahoma at the DOE Atmospheric Radiation Mission (ARM) Southern Great Plans (SGP) Central Facility from 22 April through 6 June 2011. NOAA deployed three instruments: a Parsivel disdrometer, a 2.8-GHz profiler, and a 449-MHz profiler. The parasivel provided surface estimates of the raindrop size distribution and is the reference used to absolutely calibrate the 2.8 GHz profiler. The 2.8-GHz profiler provided unattenuated reflectivity profiles of the precipitation. The 449-MHz profiler provided estimates of the vertical air motion during precipitation from near the surface to just below the freezing level. By using the combination of 2.8-GHz and 449-MHz profiler observations, vertical profiles of raindrop size distributions can be retrieved. The profilers are often reference by their frequency band: the 2.8-GHz profiler operates in the S-band and the 449-MHz profiler operates in the UHF band. The raw observations are available as well as calibrated spectra and moments. This document describes how the instruments were deployed, how the data was collected, and the format of the archived data.

  19. Sandia National Laboratories Develops Tool for Evaluating Wind...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Sandia National Laboratories Develops Tool for Evaluating Wind Turbine-Radar Impacts Sandia National Laboratories Develops Tool for Evaluating Wind Turbine-Radar Impacts September ...

  20. Depth profiling analysis of solar wind helium collected in diamond-like carbon film from Genesis

    SciTech Connect (OSTI)

    Bajo, Ken-ichi; Olinger, Chad T.; Jurewicz, Amy J.G.; Burnett, Donald S.; Sakaguchi, Isao; Suzuki, Taku; Itose, Satoru; Ishihara, Morio; Uchino, Kiichiro; Wieler, Rainer; Yurimoto, Hisayoshi

    2015-10-01

    The distribution of solar-wind ions in Genesis mission collectors, as determined by depth profiling analysis, constrains the physics of ion solid interactions involving the solar wind. Thus, they provide an experimental basis for revealing ancient solar activities represented by solar-wind implants in natural samples. We measured the first depth profile of ⁴He in a collector; the shallow implantation (peaking at <20 nm) required us to use sputtered neutral mass spectrometry with post-photoionization by a strong field. The solar wind He fluence calculated using depth profiling is ~8.5 x 10¹⁴ cm⁻². The shape of the solar wind ⁴He depth profile is consistent with TRIM simulations using the observed ⁴He velocity distribution during the Genesis mission. It is therefore likely that all solar-wind elements heavier than H are completely intact in this Genesis collector and, consequently, the solar particle energy distributions for each element can be calculated from their depth profiles. Ancient solar activities and space weathering of solar system objects could be quantitatively reproduced by solar particle implantation profiles.

  1. Comments on: Texas Tech University mobile doppler radars provide...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    texas-tech-university-mobile-doppler-radars-provide-unique-wind-measurements-to-multi-instrument-doe-field-campaign...

  2. Impact of Increasing Distributed Wind Power and Wind Turbine Siting on Rural Distribution Feeder Voltage Profiles: Preprint

    SciTech Connect (OSTI)

    Allen, A.; Zhang, Y. C.; Hodge, B. M.

    2013-09-01

    Many favorable wind energy resources in North America are located in remote locations without direct access to the transmission grid. Building transmission lines to connect remotely-located wind power plants to large load centers has become a barrier to increasing wind power penetration in North America. By connecting utility-sized megawatt-scale wind turbines to the distribution system, wind power supplied to consumers could be increased greatly. However, the impact of including megawatt-scale wind turbines on distribution feeders needs to be studied. The work presented here examined the impact that siting and power output of megawatt-scale wind turbines have on distribution feeder voltage. This is the start of work to present a general guide to megawatt-scale wind turbine impact on the distribution feeder and finding the amount of wind power that can be added without adversely impacting the distribution feeder operation, reliability, and power quality.

  3. Determination of radar MTF

    SciTech Connect (OSTI)

    Chambers, D.

    1994-11-15

    The ultimate goal of the Current Meter Array (CMA) is to be able to compare the current patterns detected with the array with radar images of the water surface. The internal wave current patterns modulate the waves on the water surface giving a detectable modulation of the radar cross-section (RCS). The function relating the RCS modulations to the current patterns is the Modulation Transfer Function (MTF). By comparing radar images directly with co-located CMA measurements the MTF can be determined. In this talk radar images and CMA measurements from a recent experiment at Loch Linnhe, Scotland, will be used to make the first direct determination of MTF for an X and S band radar at low grazing angles. The technical problems associated with comparing radar images to CMA data will be explained and the solution method discussed. The results suggest the both current and strain rate contribute equally to the radar modulation for X band. For S band, the strain rate contributes more than the current. The magnitude of the MTF and the RCS modulations are consistent with previous estimates when the wind is blowing perpendicular to the radar look direction.

  4. Scanning ARM Cloud Radars. Part II: Data Quality Control and Processing

    SciTech Connect (OSTI)

    Kollias, Pavlos; Jo, Ieng; Borque, Paloma; Tatarevic, Aleksandra; Lamer, Katia; Bharadwaj, Nitin; Widener, Kevin B.; Johnson, Karen L.; Clothiaux, Eugene E.

    2014-03-01

    The Scanning ARM Cloud Radars (SACRs) are the primary instruments for documenting the four-dimensional structure and evolution of clouds within a 20-30 km radius from the ARM fixed and mobile sites. Here, the post-processing of the calibrated SACR measurements is discussed. First, a feature mask algorithm that objectively determines the presence of significant radar returns is described. The feature mask algorithm is based on the statistical properties of radar receiver noise. It accounts for atmospheric emission and is applicable even for SACR profiles with few or no signal-free range gates. Using the nearest-in-time atmospheric sounding, the SACR radar reflectivities are corrected for gaseous attenuation (water vapor and oxygen) using a line-by-line absorption model. Despite having a high pulse repetition frequency, the SACR has a narrow Nyquist velocity limit and thus Doppler velocity folding is commonly observed. An unfolding algorithm that makes use of a first guess for the true Doppler velocity using horizontal wind measurements from the nearest sounding is described. The retrieval of the horizontal wind profile from the HS-RHI SACR scan observations and/or nearest sounding is described. The retrieved horizontal wind profile can be used to adaptively configure SACR scan strategies that depend on wind direction. Several remaining challenges are discussed, including the removal of insect and second-trip echoes. The described algorithms significantly enhance SACR data quality and constitute an important step towards the utilization of SACR measurements for cloud research.

  5. Smart Phone Technologies Reduce Risks to Eagles from Wind Turbines...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    ... Eagles are Making Wind Turbines Safer for Birds PNNL Reviews Wildlife-Interaction Monitoring for Offshore Wind Farms - Technology Hybrids Show Best Potential Mitigating Wind-Radar ...

  6. MODELING THE Fe K LINE PROFILES IN TYPE I ACTIVE GALACTIC NUCLEI WITH A COMPTON-THICK DISK WIND

    SciTech Connect (OSTI)

    Tatum, M. M.; Turner, T. J.; Sim, S. A.; Miller, L.; Reeves, J. N.; Patrick, A. R.; Long, K. S.

    2012-06-20

    We have modeled a small sample of Seyfert galaxies that were previously identified as having simple X-ray spectra with little intrinsic absorption. The sources in this sample all contain moderately broad components of Fe K-shell emission and are ideal candidates for testing the applicability of a Compton-thick accretion disk wind model to active galactic nucleus (AGN) emission components. Viewing angles through the wind allow the observer to see the absorption signature of the gas, whereas face-on viewing angles allow the observer to see the scattered light from the wind. We find that the Fe K emission line profiles are well described with a model of a Compton-thick accretion disk wind of solar abundances, arising tens to hundreds of gravitational radii from the central black hole. Further, the fits require a neutral component of Fe K{alpha} emission that is too narrow to arise from the inner part of the wind, and likely comes from a more distant reprocessing region. Our study demonstrates that a Compton-thick wind can have a profound effect on the observed X-ray spectrum of an AGN, even when the system is not viewed through the flow.

  7. Proposed ground-based incoherent Doppler lidar with iodine filter discriminator for atmospheric wind profiling

    SciTech Connect (OSTI)

    Liu, Z.S.; Chen, W.B.; Hair, J.W.; She, C.Y.

    1996-12-31

    A new incoherent lidar for measuring atmospheric wind using iodine molecular filter is proposed. A unique feature of the proposed lidar lies in its capability for simultaneous measurement of aerosol mixing ratio, with which the radial wind can be determined uniquely from lidar return. A preliminary laboratory experiment using a dye laser at 589 nm and a rotating wheel has been performed demonstrating the feasibility of the proposed wind measurement.

  8. Science Goals for the ARM Recovery Act Radars

    SciTech Connect (OSTI)

    JH Mather

    2012-05-29

    field. These additional microphysical measurements would allow detailed cloud properties to be derived even in the presence of light precipitation. It is important to couple these detailed measurements of cloud microphysics to vertical motion on the cloud scale to couple microphysics with meteorological processes. Vertically pointing Doppler radars provide the vertical motion of cloud particles but, to separate particle motion from air motion, a wind profiler is required. The American Recovery and Reinvestment Act provided the means to address these needs and implement a multi-frequency suite of radars, including scanning radars, at each of the ARM sites. In addition, Doppler lidars have been deployed at several sites. With these new measurement capabilities, ARM has the measurement capabilities to tackle the problems of improving microphysical profile descriptions and evaluating the relationship between our current narrow-field-of view, zenith perspective on clouds to a description of the full 3D cloud field and its temporal evolution.

  9. TTU Advanced Doppler Radar

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    TTU Advanced Doppler Radar - Sandia Energy Energy Search Icon Sandia Home Locations Contact Us Employee Locator Energy & Climate Secure & Sustainable Energy Future Stationary Power Energy Conversion Efficiency Solar Energy Wind Energy Water Power Supercritical CO2 Geothermal Natural Gas Safety, Security & Resilience of the Energy Infrastructure Energy Storage Nuclear Power & Engineering Grid Modernization Battery Testing Nuclear Energy Defense Waste Management Programs Advanced

  10. Scanning ARM Cloud Radars Part II: Data Quality Control and Processing

    SciTech Connect (OSTI)

    Kollias, Pavlos; Jo, Ieng; Borque, Paloma; Tatarevic, Aleksandra; Lamer, Katia; Bharadwaj, Nitin; Widener, Kevin B.; Johnson, Karen; Clothiaux, Eugene E.

    2014-03-01

    The Scanning ARM Cloud Radars (SACRs) are the primary instruments for documenting the four-dimensional structure and evolution of clouds within a 20-30 km radius from the ARM fixed and mobile sites. Here, the post-processing of the calibrated SACR measurements is discussed. First, a feature mask algorithm that objectively determines the presence of significant radar returns is described. The feature mask algorithm is based on the statistical properties of radar receiver noise. It accounts for atmospheric emission and is applicable even for SACR profiles with few or no signal-free range gates. Using the nearest-in-time atmospheric sounding, the SACR radar reflectivities are corrected for gaseous attenuation (water vapor and oxygen) using a line-by-line absorption model. Despite having a high pulse repetition frequency, the SACR has a narrow Nyquist velocity limit and thus Doppler velocity folding is commonly observed. An unfolding algorithm that makes use of a first guess for the true Doppler velocity using horizontal wind measurements from the nearest sounding is described. The retrieval of the horizontal wind profile from the Hemispherical Sky Range Height Indicator SACR scan observations and/or nearest sounding is described. The retrieved horizontal wind profile can be used to adaptively configure SACR scan strategies that depend on wind direction. Several remaining challenges are discussed, including the removal of insect and second-trip echoes. The described algorithms significantly enhance SACR data quality and constitute an important step towards the utilization of SACR measurements for cloud research.

  11. Symposium on Lower Tropospheric Profiling: Needs and Technologies, 1st, Boulder, CO, May 31-June 3, 1988, Papers

    SciTech Connect (OSTI)

    Dabberdt, W.F.; Hardesty, R.M.

    1989-10-01

    Papers on lower tropospheric profiling are presented, covering topics such as horizontal resolution needs for adequate lower tropospheric profiling with atmospheric systems forced by horizontal gradients in surface heating, meteorological data requirements for modeling air quality uncertainties, and kinematic quantities derived from a triangle of VHF Doppler wind profilers. Other topics include the intercomparison of wind measurements from two acoustic Doppler sodars, a laser Doppler radar, and in situ sensors, studying precipitation processes in the troposphere with an FM-CW radar, Doppler lidar measurements of profiles of turbulence and momentum flux, and airborne Doppler lidar measurements of the extended California sea breeze. Additional subjects include DIAL tropospheric ozone measurement using a Nd:YAG laser and the Raman shifting technique, design considerations for a network of thermodynamic profilers, nonredundant frequencies for ground-based microwave radiometric temperature profiling, and the sounding range of a 1-m wavelength radio acoustic sounder.

  12. Wind profiles on the stoss slope of sand dunes: Implications for eolian sand transport

    SciTech Connect (OSTI)

    Frank, A.; Kocurek, G. (Univ. of Texas, Austin, TX (United States). Dept. of Geological Sciences)

    1993-04-01

    Starting with the work of R.A. Bagnold it has been recognized that the shear stress exerted by the wind on sand grains is the driving force for eolian sand transport. Calculation of accurate rates of sand transport is essential for prediction of migration rates of sand dunes in modern environments as well as reconstructing paleoclimates (wind speed and direction) from eolian deposits. Because a sand dune is a streamlined obstacle in the path of the wind, continuity necessitates that the flow field is compressed over the windward side of a dune and shear stress should progressively increase up the slope as the flow accelerates. However, airflow measurements over 14 dunes (at White Sands, New Mexico; Algodones, CA; and Padre Island, TX) show that compression of the flow field occurs very close to the surface and as a consequence, the overlying flow actually shows an overall decrease in shear stress up the slope. Measurements commonly collected in the overlying zone are not representative of the near-surface, sand-driving wind. Furthermore, near-surface compression of the flow field implies that a pressure gradient exists that would render the current transport models inappropriate for sloping surfaces that dominate natural sandy desert terrains.

  13. Wind Power Today, 2010, Wind and Water Power Program (WWPP) | Department of

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Energy Wind Power Today, 2010, Wind and Water Power Program (WWPP) Wind Power Today, 2010, Wind and Water Power Program (WWPP) Wind Power Today is an annual publication that provides an overview of the wind energy research conducted by the U.S. Department of Energy Wind and Water Power Program. 47531.pdf (6.07 MB) More Documents & Publications Federal Interagency Wind Turbine Radar Interference Mitigation Strategy Wind Program Accomplishments Final Report DE-EE0005380 - Assessment of

  14. 2012 ARPA-E Energy Innovation Summit: Profiling General Compression: A River of Wind

    SciTech Connect (OSTI)

    Marcus, David; Ingersoll, Eric

    2012-02-29

    The third annual ARPA-E Energy Innovation Summit was held in Washington D.C. in February, 2012. The event brought together key players from across the energy ecosystem - researchers, entrepreneurs, investors, corporate executives, and government officials - to share ideas for developing and deploying the next generation of energy technologies. A few videos were selected for showing during the Summit to attendees. These 'performer videos' highlight innovative research that is ongoing and related to the main topics of the Summit's sessions. Featured in this video are David Marcus, Founder of General Compression, and Eric Ingersoll, CEO of General Compression. General Compression, with the help of ARPA-E funding, has created an advanced air compression process which can store and release more than a weeks worth of the energy generated by wind turbines.

  15. 2012 ARPA-E Energy Innovation Summit: Profiling General Compression: A River of Wind

    ScienceCinema (OSTI)

    Marcus, David; Ingersoll, Eric

    2012-03-21

    The third annual ARPA-E Energy Innovation Summit was held in Washington D.C. in February, 2012. The event brought together key players from across the energy ecosystem - researchers, entrepreneurs, investors, corporate executives, and government officials - to share ideas for developing and deploying the next generation of energy technologies. A few videos were selected for showing during the Summit to attendees. These 'performer videos' highlight innovative research that is ongoing and related to the main topics of the Summit's sessions. Featured in this video are David Marcus, Founder of General Compression, and Eric Ingersoll, CEO of General Compression. General Compression, with the help of ARPA-E funding, has created an advanced air compression process which can store and release more than a weeks worth of the energy generated by wind turbines.

  16. WINDExchange Webinar: Overcoming Wind Siting Challenges III:...

    Office of Environmental Management (EM)

    and Land Use June 17, 2015 3:00PM to 4:00PM EDT As a follow-up to the February webinar on wind power siting challenges and the April webinar on radar and wind energy projects,...

  17. Environmental Impacts and Siting of Wind Projects | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Research & Development » Environmental Impacts and Siting of Wind Projects Environmental Impacts and Siting of Wind Projects A trained falcon, equipped with a GPS and a VHF tracker, gathers radar data that is helping scientists improve bird detection technologies at wind facilities. A trained falcon, equipped with a GPS and a VHF tracker, gathers radar data that is helping scientists improve bird detection technologies at wind facilities. The Wind Program works to remove barriers to wind

  18. DOE Science Showcase - Wind Power

    Office of Scientific and Technical Information (OSTI)

    Profiling General Compression: A River of Wind, ScienceCinema, multimedia Solar and Wind Energy Resource Assessment (SWERA) Data from the National Renewable Energy Library and ...

  19. ARM - Measurement - Radar Doppler

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    quality assurance purposes. ARM Instruments CSAPR : C-Band ARM Precipitation Radar DL : Doppler Lidar KAZR : Ka ARM Zenith Radar KASACR : Ka-Band Scanning ARM Cloud Radar MWACR :...

  20. Profiling

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Profiling your application with Intel VTune at NERSC --- 1 --- VTune background and availability * Focus: O n---node p erformance a nalysis - Sampling a nd t race---based p rofiling - Performance c ounter i ntegra8on - Memory b andwidth a nalysis - On---node p arallelism: vectoriza8on a nd t hreading * Pre---defined a nalysis e xperiments * GUI a nd c ommand---line i nterface ( good f or h eadless collec?on a nd l ater a nalysis) * NERSC a vailability ( as t he vtune m odule) - Edison ( Dual 1

  1. Investigating wind turbine impacts on near-wake flow using profiling Lidar data and large-eddy simulations with an actuator disk model

    SciTech Connect (OSTI)

    Mirocha, Jeffrey D.; Rajewski, Daniel A.; Marjanovic, Nikola; Lundquist, Julie K.; Kosovic, Branko; Draxl, Caroline; Churchfield, Matthew J.

    2015-08-27

    In this study, wind turbine impacts on the atmospheric flow are investigated using data from the Crop Wind Energy Experiment (CWEX-11) and large-eddy simulations (LESs) utilizing a generalized actuator disk (GAD) wind turbine model. CWEX-11 employed velocity-azimuth display (VAD) data from two Doppler lidar systems to sample vertical profiles of flow parameters across the rotor depth both upstream and in the wake of an operating 1.5 MW wind turbine. Lidar and surface observations obtained during four days of July 2011 are analyzed to characterize the turbine impacts on wind speed and flow variability, and to examine the sensitivity of these changes to atmospheric stability. Significant velocity deficits (VD) are observed at the downstream location during both convective and stable portions of four diurnal cycles, with large, sustained deficits occurring during stable conditions. Variances of the streamwise velocity component, σu, likewise show large increases downstream during both stable and unstable conditions, with stable conditions supporting sustained small increases of σu , while convective conditions featured both larger magnitudes and increased variability, due to the large coherent structures in the background flow. Two representative case studies, one stable and one convective, are simulated using LES with a GAD model at 6 m resolution to evaluate the compatibility of the simulation framework with validation using vertically profiling lidar data in the near wake region. Virtual lidars were employed to sample the simulated flow field in a manner consistent with the VAD technique. Simulations reasonably reproduced aggregated wake VD characteristics, albeit with smaller magnitudes than observed, while σu values in the wake are more significantly underestimated. The results illuminate the limitations of using a GAD in combination with coarse model resolution in the simulation of near wake physics, and validation thereof using VAD data.

  2. Investigating wind turbine impacts on near-wake flow using profiling Lidar data and large-eddy simulations with an actuator disk model

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Mirocha, Jeffrey D.; Rajewski, Daniel A.; Marjanovic, Nikola; Lundquist, Julie K.; Kosovic, Branko; Draxl, Caroline; Churchfield, Matthew J.

    2015-08-27

    In this study, wind turbine impacts on the atmospheric flow are investigated using data from the Crop Wind Energy Experiment (CWEX-11) and large-eddy simulations (LESs) utilizing a generalized actuator disk (GAD) wind turbine model. CWEX-11 employed velocity-azimuth display (VAD) data from two Doppler lidar systems to sample vertical profiles of flow parameters across the rotor depth both upstream and in the wake of an operating 1.5 MW wind turbine. Lidar and surface observations obtained during four days of July 2011 are analyzed to characterize the turbine impacts on wind speed and flow variability, and to examine the sensitivity of thesemore » changes to atmospheric stability. Significant velocity deficits (VD) are observed at the downstream location during both convective and stable portions of four diurnal cycles, with large, sustained deficits occurring during stable conditions. Variances of the streamwise velocity component, σu, likewise show large increases downstream during both stable and unstable conditions, with stable conditions supporting sustained small increases of σu , while convective conditions featured both larger magnitudes and increased variability, due to the large coherent structures in the background flow. Two representative case studies, one stable and one convective, are simulated using LES with a GAD model at 6 m resolution to evaluate the compatibility of the simulation framework with validation using vertically profiling lidar data in the near wake region. Virtual lidars were employed to sample the simulated flow field in a manner consistent with the VAD technique. Simulations reasonably reproduced aggregated wake VD characteristics, albeit with smaller magnitudes than observed, while σu values in the wake are more significantly underestimated. The results illuminate the limitations of using a GAD in combination with coarse model resolution in the simulation of near wake physics, and validation thereof using VAD data.« less

  3. Wind Energy Markets, 2. edition

    SciTech Connect (OSTI)

    2007-11-15

    The report provides an overview of the global market for wind energy, including a concise look at wind energy development in key markets including installations, government incentives, and market trends. Topics covered include: an overview of wind energy including the history of wind energy production and the current market for wind energy; key business drivers of the wind energy market; barriers to the growth of wind energy; key wind energy trends and recent developments; the economics of wind energy, including cost, revenue, and government subsidy components; regional and national analyses of major wind energy markets; and, profiles of key wind turbine manufacturers.

  4. Interagency Field Test Evaluates Co-operation of Turbines and Radar |

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Department of Energy Interagency Field Test Evaluates Co-operation of Turbines and Radar Interagency Field Test Evaluates Co-operation of Turbines and Radar May 1, 2012 - 2:56pm Addthis The Department of Energy and federal agency partners recently completed the first in a series of three radar technology field tests and demonstrations. The Interagency Field Test and Evaluation of Wind-Radar Mitigation Technologies is an $8 million demonstration initiative co-funded by the Energy Department,

  5. Ka-Band ARM Zenith Radar (KAZR) Instrument Handbook

    SciTech Connect (OSTI)

    Widener, K; Bharadwaj, N; Johnson, K

    2012-03-06

    The Ka-band ARM zenith radar (KAZR) is a zenith-pointing Doppler cloud radar operating at approximately 35 GHz. The KAZR is an evolutionary follow-on radar to ARM's widely successful millimeter-wavelength cloud radar (MMCR). The main purpose of the KAZR is to provide vertical profiles of clouds by measuring the first three Doppler moments: reflectivity, radial Doppler velocity, and spectra width. At the sites where the dual-polarization measurements are made, the Doppler moments for the cross-polarization channel are also available. In addition to the moments, velocity spectra are also continuously recorded for each range gate.

  6. The Wind Forecast Improvement Project (WFIP). A Public-Private Partnership Addressing Wind Energy Forecast Needs

    SciTech Connect (OSTI)

    Wilczak, James M.; Finley, Cathy; Freedman, Jeff; Cline, Joel; Bianco, L.; Olson, J.; Djalaova, I.; Sheridan, L.; Ahlstrom, M.; Manobianco, J.; Zack, J.; Carley, J.; Benjamin, S.; Coulter, R. L.; Berg, Larry K.; Mirocha, Jeff D.; Clawson, K.; Natenberg, E.; Marquis, M.

    2015-10-30

    The Wind Forecast Improvement Project (WFIP) is a public-private research program, the goals of which are to improve the accuracy of short-term (0-6 hr) wind power forecasts for the wind energy industry and then to quantify the economic savings that accrue from more efficient integration of wind energy into the electrical grid. WFIP was sponsored by the U.S. Department of Energy (DOE), with partners that include the National Oceanic and Atmospheric Administration (NOAA), private forecasting companies (WindLogics and AWS Truepower), DOE national laboratories, grid operators, and universities. WFIP employed two avenues for improving wind power forecasts: first, through the collection of special observations to be assimilated into forecast models to improve model initial conditions; and second, by upgrading NWP forecast models and ensembles. The new observations were collected during concurrent year-long field campaigns in two high wind energy resource areas of the U.S. (the upper Great Plains, and Texas), and included 12 wind profiling radars, 12 sodars, 184 instrumented tall towers and over 400 nacelle anemometers (provided by private industry), lidar, and several surface flux stations. Results demonstrate that a substantial improvement of up to 14% relative reduction in power root mean square error (RMSE) was achieved from the combination of improved NOAA numerical weather prediction (NWP) models and assimilation of the new observations. Data denial experiments run over select periods of time demonstrate that up to a 6% relative improvement came from the new observations. The use of ensemble forecasts produced even larger forecast improvements. Based on the success of WFIP, DOE is planning follow-on field programs.

  7. ARM - Radar Backgrounder

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Tuesday, A24B-02: Use of Dual Frequency Doppler Radar to Infer Cloud and Precipitation Properties and Air Motion Statistics. Science Team: Mike Jensen, Brookhaven National ...

  8. Differences between nonprecipitating tropical and trade wind marine shallow cumuli

    SciTech Connect (OSTI)

    Ghate, Virendra P.; Miller, Mark A.; Zhu, Ping

    2015-11-13

    In this study, marine nonprecipitating cumulus topped boundary layers (CTBLs) observed in a tropical and in a trade wind region are contrasted based on their cloud macrophysical, dynamical, and radiative structures. Data from the Atmospheric Radiation Measurement (ARM) observational site previously operating at Manus Island, Papua New Guinea, and data collected during the deployment of ARM Mobile Facility at the island of Graciosa, in the Azores, were used in this study. The tropical marine CTBLs were deeper, had higher surface fluxes and boundary layer radiative cooling, but lower wind speeds compared to their trade wind counterparts. The radiative velocity scale was 50%-70% of the surface convective velocity scale at both locations, highlighting the prominent role played by radiation in maintaining turbulence in marine CTBLs. Despite greater thicknesses, the chord lengths of tropical cumuli were on average lower than those of trade wind cumuli, and as a result of lower cloud cover, the hourly averaged (cloudy and clear) liquid water paths of tropical cumuli were lower than the trade wind cumuli. At both locations ~70% of the cloudy profiles were updrafts, while the average amount of updrafts near cloud base stronger than 1 m s–1 was ~22% in tropical cumuli and ~12% in the trade wind cumuli. The mean in-cloud radar reflectivity within updrafts and mean updraft velocity was higher in tropical cumuli than the trade wind cumuli. Despite stronger vertical velocities and a higher number of strong updrafts, due to lower cloud fraction, the updraft mass flux was lower in the tropical cumuli compared to the trade wind cumuli. The observations suggest that the tropical and trade wind marine cumulus clouds differ significantly in their macrophysical and dynamical structures

  9. Differences between nonprecipitating tropical and trade wind marine shallow cumuli

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Ghate, Virendra P.; Miller, Mark A.; Zhu, Ping

    2015-11-13

    In this study, marine nonprecipitating cumulus topped boundary layers (CTBLs) observed in a tropical and in a trade wind region are contrasted based on their cloud macrophysical, dynamical, and radiative structures. Data from the Atmospheric Radiation Measurement (ARM) observational site previously operating at Manus Island, Papua New Guinea, and data collected during the deployment of ARM Mobile Facility at the island of Graciosa, in the Azores, were used in this study. The tropical marine CTBLs were deeper, had higher surface fluxes and boundary layer radiative cooling, but lower wind speeds compared to their trade wind counterparts. The radiative velocity scalemore » was 50%-70% of the surface convective velocity scale at both locations, highlighting the prominent role played by radiation in maintaining turbulence in marine CTBLs. Despite greater thicknesses, the chord lengths of tropical cumuli were on average lower than those of trade wind cumuli, and as a result of lower cloud cover, the hourly averaged (cloudy and clear) liquid water paths of tropical cumuli were lower than the trade wind cumuli. At both locations ~70% of the cloudy profiles were updrafts, while the average amount of updrafts near cloud base stronger than 1 m s–1 was ~22% in tropical cumuli and ~12% in the trade wind cumuli. The mean in-cloud radar reflectivity within updrafts and mean updraft velocity was higher in tropical cumuli than the trade wind cumuli. Despite stronger vertical velocities and a higher number of strong updrafts, due to lower cloud fraction, the updraft mass flux was lower in the tropical cumuli compared to the trade wind cumuli. The observations suggest that the tropical and trade wind marine cumulus clouds differ significantly in their macrophysical and dynamical structures« less

  10. Coastal Ohio Wind Project

    SciTech Connect (OSTI)

    Gorsevski, Peter; Afjeh, Abdollah; Jamali, Mohsin; Bingman, Verner

    2014-04-04

    reduced the wake size and enhanced the vortices in the flow downstream of the turbine-tower compared with the tower alone case. Mean and rms velocity distributions from hot wire anemometer data confirmed that in a downwind configuration, the wake of the tower dominates the flow, thus the flow fields of a tower alone and tower-turbine combinations are nearly the same. For the upwind configuration, the mean velocity shows a narrowing of the wake compared with the tower alone case. The downwind configuration wake persisted longer than that of an upwind configuration; however, it was not possible to quantify this difference because of the size limitation of the wind tunnel downstream of the test section. The water tunnel studies demonstrated that the scale model studies could be used to adequately produce accurate motions to model the motions of a wind turbine platform subject to large waves. It was found that the important factors that affect the platform is whether the platform is submerged or surface piercing. In the former, the loads on the platform will be relatively reduced whereas in the latter case, the structure pierces the wave free surface and gains stiffness and stability. The other important element that affects the movement of the platform is depth of the sea in which the wind turbine will be installed. Furthermore, the wildlife biology component evaluated migratory patterns by different monitoring systems consisting of marine radar, thermal IR camera and acoustic recorders. The types of radar used in the project are weather surveillance radar and marine radar. The weather surveillance radar (1988 Doppler), also known as Next Generation Radar (NEXRAD), provides a network of weather stations in the US. Data generated from this network were used to understand general migratory patterns, migratory stopover habitats, and other patterns caused by the effects of weather conditions. At a local scale our marine radar was used to complement the datasets from NEXRAD and

  11. Search for: All records | Data Explorer

    Office of Scientific and Technical Information (OSTI)

    Merged and corrected 915 MHz Radar Wind Profiler moments Jonathan Helmus,Virendra Ghate, Frederic Tridon The radar wind profiler (RWP) present at the SGP central facility operates ...

  12. ARM - Instrument - rwp

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    us at 1-888-ARM-DATA. Send Instrument : Radar Wind Profiler (RWP) Instrument Categories Atmospheric Profiling General Overview The radar wind profilerradio acoustic sounding ...

  13. WINDExchange Webinar: Overcoming Wind Siting Challenges III: Public Acceptance and Land Use

    Broader source: Energy.gov [DOE]

    As a follow-up to the February webinar on wind power siting challenges and the April webinar on radar and wind energy projects, moderator Patrick Gilman from the Energy Department and technical...

  14. West Winds Wind Farm | Open Energy Information

    Open Energy Info (EERE)

    Winds Wind Farm Jump to: navigation, search Name West Winds Wind Farm Facility West Winds Sector Wind energy Facility Type Commercial Scale Wind Facility Status In Service Owner...

  15. CONSTRAINTS ON POROSITY AND MASS LOSS IN O-STAR WINDS FROM THE MODELING OF X-RAY EMISSION LINE PROFILE SHAPES

    SciTech Connect (OSTI)

    Leutenegger, Maurice A.; Sundqvist, Jon O.; Owocki, Stanley P.

    2013-06-10

    We fit X-ray emission line profiles in high resolution XMM-Newton and Chandra grating spectra of the early O supergiant {zeta} Pup with models that include the effects of porosity in the stellar wind. We explore the effects of porosity due to both spherical and flattened clumps. We find that porosity models with flattened clumps oriented parallel to the photosphere provide poor fits to observed line shapes. However, porosity models with isotropic clumps can provide acceptable fits to observed line shapes, but only if the porosity effect is moderate. We quantify the degeneracy between porosity effects from isotropic clumps and the mass-loss rate inferred from the X-ray line shapes, and we show that only modest increases in the mass-loss rate ({approx}< 40%) are allowed if moderate porosity effects (h{sub {infinity}} {approx}< R{sub *}) are assumed to be important. Large porosity lengths, and thus strong porosity effects, are ruled out regardless of assumptions about clump shape. Thus, X-ray mass-loss rate estimates are relatively insensitive to both optically thin and optically thick clumping. This supports the use of X-ray spectroscopy as a mass-loss rate calibration for bright, nearby O stars.

  16. Downhole pulse radar

    DOE Patents [OSTI]

    Chang, Hsi-Tien

    1989-01-01

    A borehole logging tool generates a fast rise-time, short duration, high peak-power radar pulse having broad energy distribution between 30 MHz and 300 MHz through a directional transmitting and receiving antennas having barium titanate in the electromagnetically active region to reduce the wavelength to within an order of magnitude of the diameter of the antenna. Radar returns from geological discontinuities are sampled for transmission uphole.

  17. Downhole pulse radar

    DOE Patents [OSTI]

    Chang, Hsi-Tien

    1987-09-28

    A borehole logging tool generates a fast rise-time, short duration, high peak-power radar pulse having broad energy distribution between 30 MHz and 300 MHz through a directional transmitting and receiving antennas having barium titanate in the electromagnetically active region to reduce the wavelength to within an order of magnitude of the diameter of the antenna. Radar returns from geological discontinuities are sampled for transmission uphole. 7 figs.

  18. ARM - Measurement - Radar polarization

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    polarization ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Measurement : Radar polarization The temporal and geometric behavior of the electric field vector of an electromagnetic wave transmitted or received by a radar system, e.g. elliptical polarization, differential reflectivity, phase shift, co-polar correlation coefficient, linear depolarization ratio. Categories Cloud Properties Instruments The above

  19. DOE Science Showcase - Wind Power | OSTI, US Dept of Energy,...

    Office of Scientific and Technical Information (OSTI)

    Profiling General Compression: A River of Wind, ScienceCinema, multimedia Solar and Wind Energy Resource Assessment (SWERA) Data from the National Renewable Energy Library and ...

  20. ARM Scanning Radar

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    (fixed elevation) 3. Sector scan (for cloud tracking) 4. Staring mode 3D-Cloud Products Case Study - Marine Stratocumulus 75 o Horizontal Wind Height In-cloud horizontal wind and...

  1. Wind Integration

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Wind Generation - ScheduledActual Balancing Reserves - Deployed Near Real-time Wind Animation Wind Projects under Review Growth Forecast Fact Sheets Working together to address...

  2. The Wind Integration National Dataset (WIND) toolkit (Presentation)

    SciTech Connect (OSTI)

    Caroline Draxl: NREL

    2014-01-01

    Regional wind integration studies require detailed wind power output data at many locations to perform simulations of how the power system will operate under high penetration scenarios. The wind datasets that serve as inputs into the study must realistically reflect the ramping characteristics, spatial and temporal correlations, and capacity factors of the simulated wind plants, as well as being time synchronized with available load profiles.As described in this presentation, the WIND Toolkit fulfills these requirements by providing a state-of-the-art national (US) wind resource, power production and forecast dataset.

  3. Prairie Winds Wind Farm | Open Energy Information

    Open Energy Info (EERE)

    Wind Farm Jump to: navigation, search Name Prairie Winds Wind Farm Facility Prairie Winds Sector Wind energy Facility Type Commercial Scale Wind Facility Status In Service Owner...

  4. Impulse radar studfinder

    DOE Patents [OSTI]

    McEwan, T.E.

    1995-10-10

    An impulse radar studfinder propagates electromagnetic pulses and detects reflected pulses from a fixed range. Unmodulated pulses, about 200 ps wide, are emitted. A large number of reflected pulses are sampled and averaged. Background reflections are subtracted. Reflections from wall studs or other hidden objects are detected and displayed using light emitting diodes. 9 figs.

  5. Impulse radar studfinder

    DOE Patents [OSTI]

    McEwan, Thomas E. (Livermore, CA)

    1995-01-01

    An impulse radar studfinder propagates electromagnetic pulses and detects reflected pulses from a fixed range. Unmodulated pulses, about 200 ps wide, are emitted. A large number of reflected pulses are sampled and averaged. Background reflections are subtracted. Reflections from wall studs or other hidden objects are detected and displayed using light emitting diodes.

  6. Radar Friendly Blades

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Search Icon Sandia Home Locations Contact Us Employee ... Energy Conversion Efficiency Solar Energy Wind Energy Water ... Resonant-absorber material test panels were fabricated using ...

  7. TTU Advanced Doppler Radar

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Solar Energy Wind Energy Water Power Supercritical CO2 Geothermal Natural Gas Safety, Security & Resilience of the Energy Infrastructure Energy Storage Nuclear Power & Engineering ...

  8. A Doppler lidar for measuring winds in the middle atmosphere

    SciTech Connect (OSTI)

    Chanin, M.L.; Garnier, A.; Hauchecorne, A.; Porteneuve, J. )

    1989-11-01

    The possibility of measuring winds in the middle atmosphere with a Doppler lidar has just been demonstrated. It is aimed at studying the wave-mean flow interaction, when used is association with the Rayleigh lidar providing density and temperature profiles and their fluctuations. The new Doppler lidar relies on the Rayleigh scattering from air molecules is designed to cover the height range 25-60 km, a region where radars cannot operate. The Doppler shift to the backscattered echo is measured by inter-comparing the signal detected through each of the two high-resolution, narrow band-pass Fabry-Perot interferometers tuned on either side of the emitted laser line.

  9. Advancements in Wind Integration Study Data Modeling: The Wind Integration National Dataset (WIND) Toolkit; Preprint

    SciTech Connect (OSTI)

    Draxl, C.; Hodge, B. M.; Orwig, K.; Jones, W.; Searight, K.; Getman, D.; Harrold, S.; McCaa, J.; Cline, J.; Clark, C.

    2013-10-01

    Regional wind integration studies in the United States require detailed wind power output data at many locations to perform simulations of how the power system will operate under high-penetration scenarios. The wind data sets that serve as inputs into the study must realistically reflect the ramping characteristics, spatial and temporal correlations, and capacity factors of the simulated wind plants, as well as be time synchronized with available load profiles. The Wind Integration National Dataset (WIND) Toolkit described in this paper fulfills these requirements. A wind resource dataset, wind power production time series, and simulated forecasts from a numerical weather prediction model run on a nationwide 2-km grid at 5-min resolution will be made publicly available for more than 110,000 onshore and offshore wind power production sites.

  10. ARM Southern Great Plains

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    System Radiometer Calibration Facility Equipment Repair Lab Main Office Raman Lidar Doppler Lidar and Radar Wind Profiler Ka-Band Scanning ARM Cloud Radar Ka-Zenith Radar...

  11. Search for: All records | Data Explorer

    Office of Scientific and Technical Information (OSTI)

    ARM: 1290-MHz Radar Wind ProfilerRASS (RWP1290): wind spectra Timothy Martin ; Paytsar Muradyan ; Richard Coulter 1290-MHz Radar Wind ProfilerRASS (RWP1290): wind spectra View ...

  12. Just where exactly is the radar? (a.k.a. the radar antenna phase...

    Office of Scientific and Technical Information (OSTI)

    Just where exactly is the radar? (a.k.a. the radar antenna phase center). Citation Details In-Document Search Title: Just where exactly is the radar? (a.k.a. the radar antenna ...

  13. Laser radar VI; Proceedings of the Meeting, Los Angeles, CA, Jan. 23-25, 1991

    SciTech Connect (OSTI)

    Becherer, R.J.

    1991-01-01

    Topics presented include lidar wind shear detection for commercial aircraft, centroid tracking of range-Doppler images, an analytic approach to centroid performance analysis, simultaneous active/passive IR vehicle detection, and resolution limits for high-resolution imaging lidar. Also presented are laser velocimetry applications, the application of laser radar to autonomous spacecraft landing, 3D laser radar simulation for autonomous spacecraft landing, and ground based CW atmospheric Doppler lidar performamce modeling.

  14. The lidar dark band: An oddity of the radar bright band analogy

    SciTech Connect (OSTI)

    Sassen, K.

    1996-04-01

    Although much has sbeen learned from independent radar and lidar studies of atmospheric precipitations, occasionally supported by aircraft profiling, what has been lacking is combined optical, microwave, and insitu observations of the melting layer. Fortunately, the rainshowers on April 21, 1994, during the Remote Cloud Sensing intensive obervations Period (RCSIOP) at the Southern Great Plains Cloud and radiation Testbed (CART) site provided an opportunity for coordinated dual-wavelength University of Utah Polarization Diversity Lidar, University of Massachusetts Cloud Profiling Radar System Doppler Radar, and the University of North Dakota Citation aircraft measurements.

  15. Imaging synthetic aperture radar

    DOE Patents [OSTI]

    Burns, Bryan L.; Cordaro, J. Thomas

    1997-01-01

    A linear-FM SAR imaging radar method and apparatus to produce a real-time image by first arranging the returned signals into a plurality of subaperture arrays, the columns of each subaperture array having samples of dechirped baseband pulses, and further including a processing of each subaperture array to obtain coarse-resolution in azimuth, then fine-resolution in range, and lastly, to combine the processed subapertures to obtain the final fine-resolution in azimuth. Greater efficiency is achieved because both the transmitted signal and a local oscillator signal mixed with the returned signal can be varied on a pulse-to-pulse basis as a function of radar motion. Moreover, a novel circuit can adjust the sampling location and the A/D sample rate of the combined dechirped baseband signal which greatly reduces processing time and hardware. The processing steps include implementing a window function, stabilizing either a central reference point and/or all other points of a subaperture with respect to doppler frequency and/or range as a function of radar motion, sorting and compressing the signals using a standard fourier transforms. The stabilization of each processing part is accomplished with vector multiplication using waveforms generated as a function of radar motion wherein these waveforms may be synthesized in integrated circuits. Stabilization of range migration as a function of doppler frequency by simple vector multiplication is a particularly useful feature of the invention; as is stabilization of azimuth migration by correcting for spatially varying phase errors prior to the application of an autofocus process.

  16. ARM: X-Band Scanning ARM Cloud Radar (X-SACR) Side-Looking Radar...

    Office of Scientific and Technical Information (OSTI)

    Availability: ORNL Language: English Subject: 54 Environmental Sciences Cloud particle size distribution; Hydrometeor fall velocity; Radar polarization; Radar reflectivity Dataset ...

  17. Wind Simulation

    Energy Science and Technology Software Center (OSTI)

    2008-12-31

    The Software consists of a spreadsheet written in Microsoft Excel that provides an hourly simulation of a wind energy system, which includes a calculation of wind turbine output as a power-curve fit of wind speed.

  18. Offshore Wind

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    ... HomeStationary PowerEnergy Conversion EfficiencyWind EnergyOffshore Wind Offshore Wind Tara Camacho-Lopez 2016-0... March 2014, Barcelona, Spain, PO 225. Griffith, D.T., and ...

  19. Python-ARM Radar Toolkit

    Energy Science and Technology Software Center (OSTI)

    2013-03-17

    The Python-ARM Radar Toolkit (Py-ART) is a collection of radar quality control and retrieval codes which all work on two unifying Python objects: the PyRadar and PyGrid objects. By building ingests to several popular radar formats and then abstracting the interface Py-ART greatly simplifies data processing over several other available utilities. In addition Py-ART makes use of Numpy arrays as its primary storage mechanism enabling use of existing and extensive community software tools.

  20. wind energy

    National Nuclear Security Administration (NNSA)

    5%2A en Pantex to Become Wind Energy Research Center http:nnsa.energy.govfieldofficesnponpopressreleasespantex-become-wind-energy-research-center

  1. EIA - Renewable Electricity State Profiles

    U.S. Energy Information Administration (EIA) Indexed Site

    Kansas Renewable Electricity Profile 2010 Kansas profile Table 1. Summary Renewable Electric Power Industry Statistics (2010) Primary Renewable Energy Capacity Source Wind Primary Renewable Energy Generation Source Wind Capacity (megawatts) Value Percent of State Total Total Net Summer Electricity Capacity 12,543 100.0 Total Net Summer Renewable Capacity 1,082 8.6 Geothermal - - Hydro Conventional 3 * Solar - - Wind 1,072 8.5 Wood/Wood Waste - - MSW/Landfill Gas 7 0.1 Other Biomass - -

  2. EIA - Renewable Electricity State Profiles

    U.S. Energy Information Administration (EIA) Indexed Site

    Wyoming Renewable Electricity Profile 2010 Wyoming profile Table 1. Summary Renewable Electric Power Industry Statistics (2010) Primary Renewable Energy Capacity Source Wind Primary Renewable Energy Generation Source Wind Capacity (megawatts) Value Percent of State Total Total Net Summer Electricity Capacity 7,986 100.0 Total Net Summer Renewable Capacity 1,722 21.6 Geothermal - - Hydro Conventional 307 3.8 Solar - - Wind 1,415 17.7 Wood/Wood Waste - - MSW/Landfill Gas - - Other Biomass - -

  3. EIA - Renewable Electricity State Profiles

    Gasoline and Diesel Fuel Update (EIA)

    Kansas Renewable Electricity Profile 2010 Kansas profile Table 1. Summary Renewable Electric Power Industry Statistics (2010) Primary Renewable Energy Capacity Source Wind Primary Renewable Energy Generation Source Wind Capacity (megawatts) Value Percent of State Total Total Net Summer Electricity Capacity 12,543 100.0 Total Net Summer Renewable Capacity 1,082 8.6 Geothermal - - Hydro Conventional 3 * Solar - - Wind 1,072 8.5 Wood/Wood Waste - - MSW/Landfill Gas 7 0.1 Other Biomass - -

  4. EIA - Renewable Electricity State Profiles

    Gasoline and Diesel Fuel Update (EIA)

    Wyoming Renewable Electricity Profile 2010 Wyoming profile Table 1. Summary Renewable Electric Power Industry Statistics (2010) Primary Renewable Energy Capacity Source Wind Primary Renewable Energy Generation Source Wind Capacity (megawatts) Value Percent of State Total Total Net Summer Electricity Capacity 7,986 100.0 Total Net Summer Renewable Capacity 1,722 21.6 Geothermal - - Hydro Conventional 307 3.8 Solar - - Wind 1,415 17.7 Wood/Wood Waste - - MSW/Landfill Gas - - Other Biomass - -

  5. Removing interfering clutter associated with radar pulses that an airborne radar receives from a radar transponder

    DOE Patents [OSTI]

    Ormesher, Richard C.; Axline, Robert M.

    2008-12-02

    Interfering clutter in radar pulses received by an airborne radar system from a radar transponder can be suppressed by developing a representation of the incoming echo-voltage time-series that permits the clutter associated with predetermined parts of the time-series to be estimated. These estimates can be used to estimate and suppress the clutter associated with other parts of the time-series.

  6. Validation of a radar doppler spectra simulator using measurements from the ARM cloud radars

    SciTech Connect (OSTI)

    Remillard, J.; Luke, E.; Kollias, P.

    2010-03-15

    The use of forward models as an alternative approach to compare models with observations contains advantages and challenges. Radar Doppler spectra simulators are not new; their application in high- resolution models with bin microphysics schemes could help to compare model output with the Doppler spectra recorded from the vertically pointing cloud radars at the ARM Climate Research Facility sites. The input parameters to a Doppler spectra simulator are both microphysical (e.g., particle size, shape, phase, and number concentration) and dynamical (e.g., resolved wind components and sub-grid turbulent kinetic energy). Libraries for spherical and non-spherical particles are then used to compute the backscattering cross-section and fall velocities, while the turbulence is parameterized as a Gaussian function with a prescribed width. The Signal-to-Noise Ratio (SNR) is used to determine the amount of noise added throughout the spectrum, and the spectral smoothing due to spectral averages is included to reproduce the averaging realized by cloud radars on successive returns. Thus, realistic Doppler spectra are obtained, and several parameters that relate to the morphological characteristics of the synthetically generated spectra are computed. Here, the results are compared to the new ARM microARSCL data products in an attempt to validate the simulator. Drizzling data obtained at the SGP site by the MMCR and the AMF site at Azores using the WACR are used to ensure the liquid part and the turbulence representation part of the simulator are properly accounted in the forward model.

  7. Millimeter Wave Cloud Radar (MMCR) Handbook

    SciTech Connect (OSTI)

    KB Widener; K Johnson

    2005-01-30

    The millimeter cloud radar (MMCR) systems probe the extent and composition of clouds at millimeter wavelengths. The MMCR is a zenith-pointing radar that operates at a frequency of 35 GHz. The main purpose of this radar is to determine cloud boundaries (e.g., cloud bottoms and tops). This radar will also report radar reflectivity (dBZ) of the atmosphere up to 20 km. The radar possesses a doppler capability that will allow the measurement of cloud constituent vertical velocities.

  8. ARM - Field Campaign - Cloud Radar IOP

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    of aerosol properties during clear-sky conditions. The ETL Radar Meteorology and Oceanography Division will field their NOAAK scanning cloud radar near the new ARM millimeter...

  9. Doppler radar flowmeter

    DOE Patents [OSTI]

    Petlevich, Walter J.; Sverdrup, Edward F.

    1978-01-01

    A Doppler radar flowmeter comprises a transceiver which produces an audio frequency output related to the Doppler shift in frequency between radio waves backscattered from particulate matter carried in a fluid and the radiated radio waves. A variable gain amplifier and low pass filter are provided for amplifying and filtering the transceiver output. A frequency counter having a variable triggering level is also provided to determine the magnitude of the Doppler shift. A calibration method is disclosed wherein the amplifier gain and frequency counter trigger level are adjusted to achieve plateaus in the output of the frequency counter and thereby allow calibration without the necessity of being able to visually observe the flow.

  10. Wind Measurements from Arc Scans with Doppler Wind Lidar

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Wang, H.; Barthelmie, R. J.; Clifton, Andy; Pryor, S. C.

    2015-11-25

    When defining optimal scanning geometries for scanning lidars for wind energy applications, we found that it is still an active field of research. Our paper evaluates uncertainties associated with arc scan geometries and presents recommendations regarding optimal configurations in the atmospheric boundary layer. The analysis is based on arc scan data from a Doppler wind lidar with one elevation angle and seven azimuth angles spanning 30° and focuses on an estimation of 10-min mean wind speed and direction. When flow is horizontally uniform, this approach can provide accurate wind measurements required for wind resource assessments in part because of itsmore » high resampling rate. Retrieved wind velocities at a single range gate exhibit good correlation to data from a sonic anemometer on a nearby meteorological tower, and vertical profiles of horizontal wind speed, though derived from range gates located on a conical surface, match those measured by mast-mounted cup anemometers. Uncertainties in the retrieved wind velocity are related to high turbulent wind fluctuation and an inhomogeneous horizontal wind field. Moreover, the radial velocity variance is found to be a robust measure of the uncertainty of the retrieved wind speed because of its relationship to turbulence properties. It is further shown that the standard error of wind speed estimates can be minimized by increasing the azimuthal range beyond 30° and using five to seven azimuth angles.« less

  11. Wind Measurements from Arc Scans with Doppler Wind Lidar

    SciTech Connect (OSTI)

    Wang, H.; Barthelmie, R. J.; Clifton, Andy; Pryor, S. C.

    2015-11-25

    When defining optimal scanning geometries for scanning lidars for wind energy applications, we found that it is still an active field of research. Our paper evaluates uncertainties associated with arc scan geometries and presents recommendations regarding optimal configurations in the atmospheric boundary layer. The analysis is based on arc scan data from a Doppler wind lidar with one elevation angle and seven azimuth angles spanning 30° and focuses on an estimation of 10-min mean wind speed and direction. When flow is horizontally uniform, this approach can provide accurate wind measurements required for wind resource assessments in part because of its high resampling rate. Retrieved wind velocities at a single range gate exhibit good correlation to data from a sonic anemometer on a nearby meteorological tower, and vertical profiles of horizontal wind speed, though derived from range gates located on a conical surface, match those measured by mast-mounted cup anemometers. Uncertainties in the retrieved wind velocity are related to high turbulent wind fluctuation and an inhomogeneous horizontal wind field. Moreover, the radial velocity variance is found to be a robust measure of the uncertainty of the retrieved wind speed because of its relationship to turbulence properties. It is further shown that the standard error of wind speed estimates can be minimized by increasing the azimuthal range beyond 30° and using five to seven azimuth angles.

  12. DOE Science Showcase - Wind Power | OSTI, US Dept of Energy Office...

    Office of Scientific and Technical Information (OSTI)

    Summit: Profiling General Compression: A River of Wind, ScienceCinema, multimedia Solar and Wind Energy Resource Assessment (SWERA) Data from the National Renewable Energy ...

  13. First observations of tracking clouds using scanning ARM cloud radars

    SciTech Connect (OSTI)

    Borque, Paloma; Giangrande, Scott; Kollias, Pavlos

    2014-12-01

    Tracking clouds using scanning cloud radars can help to document the temporal evolution of cloud properties well before large drop formation (‘‘first echo’’). These measurements complement cloud and precipitation tracking using geostationary satellites and weather radars. Here, two-dimensional (2-D) Along-Wind Range Height Indicator (AW-RHI) observations of a population of shallow cumuli (with and without precipitation) from the 35-GHz scanning ARM cloud radar (SACR) at the DOE Atmospheric Radiation Measurements (ARM) program Southern Great Plains (SGP) site are presented. Observations from the ARM SGP network of scanning precipitation radars are used to provide the larger scale context of the cloud field and to highlight the advantages of the SACR to detect the numerous, small, non-precipitating cloud elements. A new Cloud Identification and Tracking Algorithm (CITA) is developed to track cloud elements. In CITA, a cloud element is identified as a region having a contiguous set of pixels exceeding a preset reflectivity and size threshold. The high temporal resolution of the SACR 2-D observations (30 sec) allows for an area superposition criteria algorithm to match cloud elements at consecutive times. Following CITA, the temporal evolution of cloud element properties (number, size, and maximum reflectivity) is presented. The vast majority of the designated elements during this cumulus event were short-lived non-precipitating clouds having an apparent life cycle shorter than 15 minutes. The advantages and disadvantages of cloud tracking using an SACR are discussed.

  14. First observations of tracking clouds using scanning ARM cloud radars

    SciTech Connect (OSTI)

    Borque, Paloma; Giangrande, Scott; Kollias, Pavlos

    2014-12-01

    Tracking clouds using scanning cloud radars can help to document the temporal evolution of cloud properties well before large drop formation (first echo). These measurements complement cloud and precipitation tracking using geostationary satellites and weather radars. Here, two-dimensional (2-D) Along-Wind Range Height Indicator (AW-RHI) observations of a population of shallow cumuli (with and without precipitation) from the 35-GHz scanning ARM cloud radar (SACR) at the DOE Atmospheric Radiation Measurements (ARM) program Southern Great Plains (SGP) site are presented. Observations from the ARM SGP network of scanning precipitation radars are used to provide the larger scale context of the cloud field and to highlight the advantages of the SACR to detect the numerous, small, non-precipitating cloud elements. A new Cloud Identification and Tracking Algorithm (CITA) is developed to track cloud elements. In CITA, a cloud element is identified as a region having a contiguous set of pixels exceeding a preset reflectivity and size threshold. The high temporal resolution of the SACR 2-D observations (30 sec) allows for an area superposition criteria algorithm to match cloud elements at consecutive times. Following CITA, the temporal evolution of cloud element properties (number, size, and maximum reflectivity) is presented. The vast majority of the designated elements during this cumulus event were short-lived non-precipitating clouds having an apparent life cycle shorter than 15 minutes. The advantages and disadvantages of cloud tracking using an SACR are discussed.

  15. Cloud radar Doppler spectra in drizzling stratiform clouds: 1. Forward modeling and remote sensing applications

    SciTech Connect (OSTI)

    Kollias, P.; Luke, E.; Rmillard, J.; Szyrmer, W.

    2011-07-02

    Several aspects of spectral broadening and drizzle growth in shallow liquid clouds remain not well understood. Detailed, cloud-scale observations of microphysics and dynamics are essential to guide and evaluate corresponding modeling efforts. Profiling, millimeter-wavelength (cloud) radars can provide such observations. In particular, the first three moments of the recorded cloud radar Doppler spectra, the radar reflectivity, mean Doppler velocity, and spectrum width, are often used to retrieve cloud microphysical and dynamical properties. Such retrievals are subject to errors introduced by the assumptions made in the inversion process. Here, we introduce two additional morphological parameters of the radar Doppler spectrum, the skewness and kurtosis, in an effort to reduce the retrieval uncertainties. A forward model that emulates observed radar Doppler spectra is constructed and used to investigate these relationships. General, analytical relationships that relate the five radar observables to cloud and drizzle microphysical parameters and cloud turbulence are presented. The relationships are valid for cloud-only, cloud mixed with drizzle, and drizzle-only particles in the radar sampling volume and provide a seamless link between observations and cloud microphysics and dynamics. The sensitivity of the five observed parameters to the radar operational parameters such as signal-to-noise ratio and Doppler spectra velocity resolution are presented. The predicted values of the five observed radar parameters agree well with the output of the forward model. The novel use of the skewness of the radar Doppler spectrum as an early qualitative predictor of drizzle onset in clouds is introduced. It is found that skewness is a parameter very sensitive to early drizzle generation. In addition, the significance of the five parameters of the cloud radar Doppler spectrum for constraining drizzle microphysical retrievals is discussed.

  16. Cisco Wind Energy Wind Farm | Open Energy Information

    Open Energy Info (EERE)

    Cisco Wind Energy Wind Farm Jump to: navigation, search Name Cisco Wind Energy Wind Farm Facility Cisco Wind Energy Sector Wind energy Facility Type Commercial Scale Wind Facility...

  17. Wind Easements

    Broader source: Energy.gov [DOE]

    The statutes authorizing the creation of wind easements include several provisions to protect property owners. For example, a wind easement may not make the property owner liable for any property...

  18. Wind Farm

    Broader source: Energy.gov [DOE]

    The wind farm in Greensburg, Kansas, was completed in spring 2010, and consists of ten 1.25 megawatt (MW) wind turbines that supply enough electricity to power every house, business, and municipal...

  19. Wind Power

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Wind Power As the accompanying map of New Mexico shows, the best wind power generation potential near WIPP is along the Delaware Mountain ridge line of the southern Guadalupe Mountains, about 50-60 miles southwest. The numeric grid values indicate wind potential, with a range from 1 (poor) to 7 (superb). Just inside Texas in the southern Guadalupe Mountains, the Delaware Mountain Wind Power Facility in Culbertson County, Texas currently generates over 30 MW, and could be expanded to a 250 MW

  20. ARM - Instrument Datastreams

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    ... 2015.12.01 1290rwpwindcon 1290-MHz Radar Wind ProfilerRASS (RWP1290): wind consensus data 2007.03.19 2015.12.01 1290rwpwindmom 1290-MHz Radar Wind ProfilerRASS ...

  1. Ground Penetrating Radar, Barrow, Alaska

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    John Peterson

    2015-03-06

    This is 500 MHz Ground Penetrating Radar collected along the AB Line in Intensive Site 1 beginning in October 2012 and collected along L2 in Intensive Site 0 beginning in September 2011. Both continue to the present.

  2. Avian use of Norris Hill Wind Resource Area, Montana

    SciTech Connect (OSTI)

    Harmata, A.; Podruzny, K.; Zelenak, J.

    1998-07-01

    This document presents results of a study of avian use and mortality in and near a proposed wind resource area in southwestern Montana. Data collected in autumn 1995 through summer 1996 represented preconstruction condition; it was compiled, analyzed, and presented in a format such that comparison with post-construction data would be possible. The primary emphasis of the study was recording avian migration in and near the wind resource area using state-of-the-art marine surveillance radar. Avian use and mortality were investigated during the breeding season by employing traditional avian sampling methods, radiotelemetry, radar, and direct visual observation. 61 figs., 34 tabs.

  3. Island based radar and microwave radiometer measurements of stratus cloud parameters during the Atlantic Stratocumulus Transition Experiment (ASTEX)

    SciTech Connect (OSTI)

    Frisch, A.S.; Fairall, C.W.; Snider, J.B.; Lenshow, D.H.; Mayer, S.D.

    1996-04-01

    During the Atlantic Stratocumulus Transition Experiment (ASTEX) in June 1992, simultaneous measurements were made with a vertically pointing cloud sensing radar and a microwave radiometer. The radar measurements are used to estimate stratus cloud drizzle and turbulence parameters. In addition, with the microwave radiometer measurements of reflectivity, we estimated the profiles of cloud liquid water and effective radius. We used radar data for computation of vertical profiles of various drizzle parameters such as droplet concentration, modal radius, and spread. A sample of these results is shown in Figure 1. In addition, in non-drizzle clouds, with the radar and radiometer we can estimate the verticle profiles of stratus cloud parameters such as liquid water concentration and effective radius. This is accomplished by assuming a droplet distribution with droplet number concentration and width constant with height.

  4. Radar-Derived Characteristics of Precipitation in South East Queensland

    SciTech Connect (OSTI)

    Peter, Justin R; May, Peter T; Potts, Rodney J; Collis, Scott M.; Manton, Michael J; Wilson, Louise

    2015-10-01

    Statistics of radar-retrievals of precipitation are presented. A K-means clustering algorithm is applied to an historical record of radiosonde measurements which identified three major synoptic regimes; a dry, stable regime with mainly westerly winds prevalent during winter, a moist south easterly trade wind regime and a moist northerly regime both prevalent during summer. These are referred to as westerly, trade wind and northerly regimes, respectively. Cell statistics are calculated using an objective cell identification and tracking methodology on data obtained from a nearby S-band radar. Cell statistics are investigated for the entire radar observational period and also during sub-periods corresponding to the three major synoptic regimes. The statistics investigated are cell initiation location, area, rainrate, volume, height, height of the maximum reflectivity, volume greater than 40 dBZ and storm speed and direction. Cells are found predominantly along the elevated topography. The cell statistics reveal that storms which form in the dry, stable westerly regime are of comparable size to the deep cells which form in the northerly regime, larger than those in the trade regime and, furthermore, have the largest rainrate. However, they occur less frequently and have shorter lifetimes than cells in the other regimes. Diurnal statistics of precipitation area and rainrate exhibit early morning and mid afternoon peaks, although the areal coverage lags the rainrate by several hours indicative of a transition from convective to stratiform precipitation. The probability distributions of cell area, rainrate, volume, height and height of the maximum re ectivity are found to follow lognormal distributions.

  5. EIA - Renewable Electricity State Profiles

    U.S. Energy Information Administration (EIA) Indexed Site

    West Virginia Renewable Electricity Profile 2010 West Virginia profile Table 1. Summary Renewable Electric Power Industry Statistics (2010) Primary Renewable Energy Capacity Source Wind Primary Renewable Energy Generation Source Hydro Conventional Capacity (megawatts) Value Percent of State Total Total Net Summer Electricity Capacity 16,495 100.0 Total Net Summer Renewable Capacity 715 4.3 Geothermal - - Hydro Conventional 285 1.7 Solar - - Wind 431 2.6 Wood/Wood Waste - - MSW/Landfill Gas - -

  6. EIA - Renewable Electricity State Profiles

    Gasoline and Diesel Fuel Update (EIA)

    West Virginia Renewable Electricity Profile 2010 West Virginia profile Table 1. Summary Renewable Electric Power Industry Statistics (2010) Primary Renewable Energy Capacity Source Wind Primary Renewable Energy Generation Source Hydro Conventional Capacity (megawatts) Value Percent of State Total Total Net Summer Electricity Capacity 16,495 100.0 Total Net Summer Renewable Capacity 715 4.3 Geothermal - - Hydro Conventional 285 1.7 Solar - - Wind 431 2.6 Wood/Wood Waste - - MSW/Landfill Gas - -

  7. Wind Workshop

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Department of Energy Wind Turbine Manufacturing Transforms with Three-Dimensional Printing Wind Turbine Manufacturing Transforms with Three-Dimensional Printing May 19, 2016 - 12:57pm Addthis From medical devices to airplane components, three-dimensional (3-D) printing (also called additive manufacturing) is transforming the manufacturing industry. Now, research that supports the Energy Department's Atmosphere to Electrons (A2e) initiative is applying 3-D-printing processes to create wind

  8. Wind News

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Secure & Sustainable Energy Future Stationary Power Energy Conversion Efficiency Solar Energy Wind Energy Water Power Supercritical CO2 Geothermal Natural Gas Safety, Security & ...

  9. Wind Energy

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Stationary Power/Energy Conversion Efficiency/Wind Energy Wind Energy Tara Camacho-Lopez 2016-08-30T20:56:10+00:00 Increasing the viability of wind energy technology by applying research to improve wind turbine performance and reliability http://windworkshops.sandia.gov/ Rotor Innovation Advancing rotor technology such that they capture more energy, more reliably, with relatively lower system loads-all at a lower end cost. SWiFT Facility & Testing Improving the performance and reducing the

  10. Wind Power Forecasting Data

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Operations Call 2012 Retrospective Reports 2012 Retrospective Reports 2011 Smart Grid Wind Integration Wind Integration Initiatives Wind Power Forecasting Wind Projects Email...

  11. NREL: Wind Research - Wind Career Map Shows Wind Industry Career...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Wind Career Map Shows Wind Industry Career Opportunities, Paths A screenshot of the wind career map showing the various points on a chart that show different careers in the wind...

  12. How Radar Works | Open Energy Information

    Open Energy Info (EERE)

    Radar Works Jump to: navigation, search OpenEI Reference LibraryAdd to library Web Site: How Radar Works Author Institute For Geophysics Published Institute For Geophysics, 2013...

  13. Obstacle penetrating dynamic radar imaging system

    DOE Patents [OSTI]

    Romero, Carlos E.; Zumstein, James E.; Chang, John T.; Leach, Jr.. Richard R.

    2006-12-12

    An obstacle penetrating dynamic radar imaging system for the detection, tracking, and imaging of an individual, animal, or object comprising a multiplicity of low power ultra wideband radar units that produce a set of return radar signals from the individual, animal, or object, and a processing system for said set of return radar signals for detection, tracking, and imaging of the individual, animal, or object. The system provides a radar video system for detecting and tracking an individual, animal, or object by producing a set of return radar signals from the individual, animal, or object with a multiplicity of low power ultra wideband radar units, and processing said set of return radar signals for detecting and tracking of the individual, animal, or object.

  14. GMTI radar minimum detectable velocity.

    SciTech Connect (OSTI)

    Richards, John Alfred

    2011-04-01

    Minimum detectable velocity (MDV) is a fundamental consideration for the design, implementation, and exploitation of ground moving-target indication (GMTI) radar imaging modes. All single-phase-center air-to-ground radars are characterized by an MDV, or a minimum radial velocity below which motion of a discrete nonstationary target is indistinguishable from the relative motion between the platform and the ground. Targets with radial velocities less than MDV are typically overwhelmed by endoclutter ground returns, and are thus not generally detectable. Targets with radial velocities greater than MDV typically produce distinct returns falling outside of the endoclutter ground returns, and are thus generally discernible using straightforward detection algorithms. This document provides a straightforward derivation of MDV for an air-to-ground single-phase-center GMTI radar operating in an arbitrary geometry.

  15. Scanning ARM Cloud Radar Handbook

    SciTech Connect (OSTI)

    Widener, K; Bharadwaj, N; Johnson, K

    2012-06-18

    The scanning ARM cloud radar (SACR) is a polarimetric Doppler radar consisting of three different radar designs based on operating frequency. These are designated as follows: (1) X-band SACR (X-SACR); (2) Ka-band SACR (Ka-SACR); and (3) W-band SACR (W-SACR). There are two SACRs on a single pedestal at each site where SACRs are deployed. The selection of the operating frequencies at each deployed site is predominantly determined by atmospheric attenuation at the site. Because RF attenuation increases with atmospheric water vapor content, ARM's Tropical Western Pacific (TWP) sites use the X-/Ka-band frequency pair. The Southern Great Plains (SGP) and North Slope of Alaska (NSA) sites field the Ka-/W-band frequency pair. One ARM Mobile Facility (AMF1) has a Ka/W-SACR and the other (AMF2) has a X/Ka-SACR.

  16. Stetson Wind Expansion Wind Farm | Open Energy Information

    Open Energy Info (EERE)

    Stetson Wind Expansion Wind Farm Jump to: navigation, search Name Stetson Wind Expansion Wind Farm Facility Stetson Wind Expansion Sector Wind energy Facility Type Commercial Scale...

  17. State Fair Wind Energy Education Center Wind Farm | Open Energy...

    Open Energy Info (EERE)

    Fair Wind Energy Education Center Wind Farm Jump to: navigation, search Name State Fair Wind Energy Education Center Wind Farm Facility Wind Energy Education Center Sector Wind...

  18. Wind Power Partners '94 Wind Farm | Open Energy Information

    Open Energy Info (EERE)

    4 Wind Farm Jump to: navigation, search Name Wind Power Partners '94 Wind Farm Facility Wind Power Partners '94 Sector Wind energy Facility Type Commercial Scale Wind Facility...

  19. Wethersfield Wind Power Wind Farm | Open Energy Information

    Open Energy Info (EERE)

    Wethersfield Wind Power Wind Farm Jump to: navigation, search Name Wethersfield Wind Power Wind Farm Facility Wethersfield Wind Power Sector Wind energy Facility Type Commercial...

  20. Portsmouth Abbey School Wind Turbine Wind Farm | Open Energy...

    Open Energy Info (EERE)

    Abbey School Wind Turbine Wind Farm Jump to: navigation, search Name Portsmouth Abbey School Wind Turbine Wind Farm Facility Portsmouth Abbey School Wind Turbine Sector Wind energy...

  1. Harbec Plastic Wind Turbine Wind Farm | Open Energy Information

    Open Energy Info (EERE)

    Harbec Plastic Wind Turbine Wind Farm Jump to: navigation, search Name Harbec Plastic Wind Turbine Wind Farm Facility Harbec Plastic Wind Turbine Sector Wind energy Facility Type...

  2. Radar operation in a hostile electromagnetic environment

    SciTech Connect (OSTI)

    Doerry, Armin Walter

    2014-03-01

    Radar ISR does not always involve cooperative or even friendly targets. An adversary has numerous techniques available to him to counter the effectiveness of a radar ISR sensor. These generally fall under the banner of jamming, spoofing, or otherwise interfering with the EM signals required by the radar sensor. Consequently mitigation techniques are prudent to retain efficacy of the radar sensor. We discuss in general terms a number of mitigation techniques.

  3. NREL: Wind Research - Offshore Wind Research

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    NREL's Offshore Wind Testing Capabilities 35 years of wind turbine testing experience ... Testing Applying 35 years of wind turbine testing expertise, NREL has developed ...

  4. NREL: Wind Research - Small Wind Turbine Development

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Small Wind Turbine Development A photo of Southwest Windpower's Skystream wind turbine in front of a home. PIX14936 Southwest Windpower's Skystream wind turbine. A photo of the ...

  5. NREL: Wind Research - Offshore Wind Resource Characterization

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Wind Resource Characterization Map of the United States, showing the wind potential of offshore areas across the country. Enlarge image US offshore wind speed estimates at 90-m ...

  6. DOE/SC-ARM-15-035 Enhanced Soundings for Local Coupling Studies...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Atmospheric temperature, moisture, and wind profiles: Microwave radiometer (MWR) Doppler lidar (DL) 915 MHz radar wind profiler (RWP) Atmospheric emitted radiance...

  7. Google Archives by Fiscal Year — Wind and Water

    Broader source: Energy.gov [DOE]

    From the EERE Web Statistics Archive: Wind and Water Power Technologies Office, retired Google Analytics profiles for the sites by fiscal year.

  8. WIND VARIABILITY IN BZ CAMELOPARDALIS

    SciTech Connect (OSTI)

    Honeycutt, R. K.; Kafka, S.; Robertson, J. W. E-mail: skafka@dtm.ciw.edu

    2013-02-01

    Sequences of spectra of the nova-like cataclysmic variable (CV) BZ Cam were acquired on nine nights in 2005-2006 in order to study the time development of episodes of wind activity known to occur frequently in this star. We confirm the results of Ringwald and Naylor that the P-Cygni absorption components of the lines mostly evolve from higher expansion velocity to lower velocity as an episode progresses. We also commonly find blueshifted emission components in the H{alpha} line profile, whose velocities and durations strongly suggest that they are also due to the wind. Curiously, Ringwald and Naylor reported common occurrences of redshifted H{alpha} emission components in their BZ Cam spectra. We have attributed these emission components in H{alpha} to occasions when gas concentrations in the bipolar wind (both front side and back side) become manifested as emission lines as they move beyond the disk's outer edge. We also suggest, based on changes in the P-Cygni profiles during an episode, that the progression from larger to smaller expansion velocities is due to the higher velocity portions of a wind concentration moving beyond the edge of the continuum light of the disk first, leaving a net redward shift of the remaining absorption profile. We derive a new orbital ephemeris for BZ Cam, using the radial velocity of the core of the He I {lambda}5876 line, finding P = 0.15353(4). Using this period, the wind episodes in BZ Cam are found to be concentrated near the inferior conjunction of the emission line source. This result helps confirm that the winds in nova-like CVs are often phase dependent, in spite of the puzzling implication that such winds lack axisymmetry. We argue that the radiation-driven wind in BZ Cam receives an initial boost by acting on gas that has been lifted above the disk by the interaction of the accretion stream with the disk, thereby imposing flickering timescales onto the wind events, as well as leading to an orbital modulation of the wind

  9. EIA - Renewable Electricity State Profiles

    U.S. Energy Information Administration (EIA) Indexed Site

    Colorado Renewable Electricity Profile 2010 Colorado profile Table 1. Summary Renewable Electric Power Industry Statistics (2010) Primary Renewable Energy Capacity Source Wind Primary Renewable Energy Generation Source Wind Capacity (megawatts) Value Percent of State Total Total Net Summer Electricity Capacity 13,777 100.0 Total Net Summer Renewable Capacity 2,010 14.6 Geothermal - - Hydro Conventional 662 4.8 Solar 41 0.3 Wind 1,294 9.4 Wood/Wood Waste - - MSW/Landfill Gas 3 * Other Biomass 10

  10. EIA - Renewable Electricity State Profiles

    U.S. Energy Information Administration (EIA) Indexed Site

    Illinois Renewable Electricity Profile 2010 Illinois profile Table 1. Summary Renewable Electric Power Industry Statistics (2010) Primary Renewable Energy Capacity Source Wind Primary Renewable Energy Generation Source Wind Capacity (megawatts) Value Percent of State Total Total Net Summer Electricity Capacity 44,127 100.0 Total Net Summer Renewable Capacity 2,112 4.8 Geothermal - - Hydro Conventional 34 0.1 Solar 9 * Wind 1,946 4.4 Wood/Wood Waste - - MSW/Landfill Gas 123 0.3 Other Biomass - -

  11. EIA - Renewable Electricity State Profiles

    U.S. Energy Information Administration (EIA) Indexed Site

    Indiana Renewable Electricity Profile 2010 Indiana profile Table 1. Summary Renewable Electric Power Industry Statistics (2010) Primary Renewable Energy Capacity Source Wind Primary Renewable Energy Generation Source Wind Capacity (megawatts) Value Percent of State Total Total Net Summer Electricity Capacity 27,638 100.0 Total Net Summer Renewable Capacity 1,452 5.3 Geothermal - - Hydro Conventional 60 0.2 Solar - - Wind 1,340 4.8 Wood/Wood Waste - - MSW/Landfill Gas 53 0.2 Other Biomass s *

  12. EIA - Renewable Electricity State Profiles

    U.S. Energy Information Administration (EIA) Indexed Site

    Iowa Renewable Electricity Profile 2010 Iowa profile Table 1. Summary Renewable Electric Power Industry Statistics (2010) Primary Renewable Energy Capacity Source Wind Primary Renewable Energy Generation Source Wind Capacity (megawatts) Value Percent of State Total Total Net Summer Electricity Capacity 14,592 100.0 Total Net Summer Renewable Capacity 3,728 25.5 Geothermal - - Hydro Conventional 144 1.0 Solar - - Wind 3,569 24.5 Wood/Wood Waste - - MSW/Landfill Gas 11 0.1 Other Biomass 3 *

  13. EIA - Renewable Electricity State Profiles

    U.S. Energy Information Administration (EIA) Indexed Site

    Minnesota Renewable Electricity Profile 2010 Minnesota profile Table 1. Summary Renewable Electric Power Industry Statistics (2010) Primary Renewable Energy Capacity Source Wind Primary Renewable Energy Generation Source Wind Capacity (megawatts) Value Percent of State Total Total Net Summer Electricity Capacity 14,715 100.0 Total Net Summer Renewable Capacity 2,588 17.6 Geothermal - - Hydro Conventional 193 1.3 Solar - - Wind 2,009 13.7 Wood/Wood Waste 177 1.2 MSW/Landfill Gas 134 0.9 Other

  14. EIA - Renewable Electricity State Profiles

    U.S. Energy Information Administration (EIA) Indexed Site

    Mexico Renewable Electricity Profile 2010 New Mexico profile Table 1. Summary Renewable Electric Power Industry Statistics (2010) Primary Renewable Energy Capacity Source Wind Primary Renewable Energy Generation Source Wind Capacity (megawatts) Value Percent of State Total Total Net Summer Electricity Capacity 8,130 100.0 Total Net Summer Renewable Capacity 818 10.1 Geothermal - - Hydro Conventional 82 1.0 Solar 30 0.4 Wind 700 8.6 Wood/Wood Waste - - MSW/Landfill Gas - - Other Biomass 6 0.1

  15. EIA - Renewable Electricity State Profiles

    U.S. Energy Information Administration (EIA) Indexed Site

    Dakota Renewable Electricity Profile 2010 North Dakota profile Table 1. Summary Renewable Electric Power Industry Statistics (2010) Primary Renewable Energy Capacity Source Wind Primary Renewable Energy Generation Source Wind Capacity (megawatts) Value Percent of State Total Total Net Summer Electricity Capacity 6,188 100.0 Total Net Summer Renewable Capacity 1,941 31.4 Geothermal - - Hydro Conventional 508 8.2 Solar - - Wind 1,423 23.0 Wood/Wood Waste - - MSW/Landfill Gas - - Other Biomass 10

  16. EIA - Renewable Electricity State Profiles

    U.S. Energy Information Administration (EIA) Indexed Site

    Oklahoma Renewable Electricity Profile 2010 Oklahoma profile Table 1. Summary Renewable Electric Power Industry Statistics (2010) Primary Renewable Energy Capacity Source Wind Primary Renewable Energy Generation Source Wind Capacity (megawatts) Value Percent of State Total Total Net Summer Electricity Capacity 21,022 100.0 Total Net Summer Renewable Capacity 2,412 11.5 Geothermal - - Hydro Conventional 858 4.1 Solar - - Wind 1,480 7.0 Wood/Wood Waste 58 0.3 MSW/Landfill Gas 16 0.1 Other Biomass

  17. EIA - Renewable Electricity State Profiles

    U.S. Energy Information Administration (EIA) Indexed Site

    Texas Renewable Electricity Profile 2010 Texas profile Table 1. Summary Renewable Electric Power Industry Statistics (2010) Primary Renewable Energy Capacity Source Wind Primary Renewable Energy Generation Source Wind Capacity (megawatts) Value Percent of State Total Total Net Summer Electricity Capacity 108,258 100.0 Total Net Summer Renewable Capacity 10,985 10.1 Geothermal - - Hydro Conventional 689 0.6 Solar 14 * Wind 9,952 9.2 Wood/Wood Waste 215 0.2 MSW/Landfill Gas 88 0.1 Other Biomass 28

  18. EIA - Renewable Electricity State Profiles

    Gasoline and Diesel Fuel Update (EIA)

    Colorado Renewable Electricity Profile 2010 Colorado profile Table 1. Summary Renewable Electric Power Industry Statistics (2010) Primary Renewable Energy Capacity Source Wind Primary Renewable Energy Generation Source Wind Capacity (megawatts) Value Percent of State Total Total Net Summer Electricity Capacity 13,777 100.0 Total Net Summer Renewable Capacity 2,010 14.6 Geothermal - - Hydro Conventional 662 4.8 Solar 41 0.3 Wind 1,294 9.4 Wood/Wood Waste - - MSW/Landfill Gas 3 * Other Biomass 10

  19. EIA - Renewable Electricity State Profiles

    Gasoline and Diesel Fuel Update (EIA)

    Illinois Renewable Electricity Profile 2010 Illinois profile Table 1. Summary Renewable Electric Power Industry Statistics (2010) Primary Renewable Energy Capacity Source Wind Primary Renewable Energy Generation Source Wind Capacity (megawatts) Value Percent of State Total Total Net Summer Electricity Capacity 44,127 100.0 Total Net Summer Renewable Capacity 2,112 4.8 Geothermal - - Hydro Conventional 34 0.1 Solar 9 * Wind 1,946 4.4 Wood/Wood Waste - - MSW/Landfill Gas 123 0.3 Other Biomass - -

  20. EIA - Renewable Electricity State Profiles

    Gasoline and Diesel Fuel Update (EIA)

    Indiana Renewable Electricity Profile 2010 Indiana profile Table 1. Summary Renewable Electric Power Industry Statistics (2010) Primary Renewable Energy Capacity Source Wind Primary Renewable Energy Generation Source Wind Capacity (megawatts) Value Percent of State Total Total Net Summer Electricity Capacity 27,638 100.0 Total Net Summer Renewable Capacity 1,452 5.3 Geothermal - - Hydro Conventional 60 0.2 Solar - - Wind 1,340 4.8 Wood/Wood Waste - - MSW/Landfill Gas 53 0.2 Other Biomass s *

  1. EIA - Renewable Electricity State Profiles

    Gasoline and Diesel Fuel Update (EIA)

    Iowa Renewable Electricity Profile 2010 Iowa profile Table 1. Summary Renewable Electric Power Industry Statistics (2010) Primary Renewable Energy Capacity Source Wind Primary Renewable Energy Generation Source Wind Capacity (megawatts) Value Percent of State Total Total Net Summer Electricity Capacity 14,592 100.0 Total Net Summer Renewable Capacity 3,728 25.5 Geothermal - - Hydro Conventional 144 1.0 Solar - - Wind 3,569 24.5 Wood/Wood Waste - - MSW/Landfill Gas 11 0.1 Other Biomass 3 *

  2. EIA - Renewable Electricity State Profiles

    Gasoline and Diesel Fuel Update (EIA)

    Minnesota Renewable Electricity Profile 2010 Minnesota profile Table 1. Summary Renewable Electric Power Industry Statistics (2010) Primary Renewable Energy Capacity Source Wind Primary Renewable Energy Generation Source Wind Capacity (megawatts) Value Percent of State Total Total Net Summer Electricity Capacity 14,715 100.0 Total Net Summer Renewable Capacity 2,588 17.6 Geothermal - - Hydro Conventional 193 1.3 Solar - - Wind 2,009 13.7 Wood/Wood Waste 177 1.2 MSW/Landfill Gas 134 0.9 Other

  3. EIA - Renewable Electricity State Profiles

    Gasoline and Diesel Fuel Update (EIA)

    Mexico Renewable Electricity Profile 2010 New Mexico profile Table 1. Summary Renewable Electric Power Industry Statistics (2010) Primary Renewable Energy Capacity Source Wind Primary Renewable Energy Generation Source Wind Capacity (megawatts) Value Percent of State Total Total Net Summer Electricity Capacity 8,130 100.0 Total Net Summer Renewable Capacity 818 10.1 Geothermal - - Hydro Conventional 82 1.0 Solar 30 0.4 Wind 700 8.6 Wood/Wood Waste - - MSW/Landfill Gas - - Other Biomass 6 0.1

  4. EIA - Renewable Electricity State Profiles

    Gasoline and Diesel Fuel Update (EIA)

    Dakota Renewable Electricity Profile 2010 North Dakota profile Table 1. Summary Renewable Electric Power Industry Statistics (2010) Primary Renewable Energy Capacity Source Wind Primary Renewable Energy Generation Source Wind Capacity (megawatts) Value Percent of State Total Total Net Summer Electricity Capacity 6,188 100.0 Total Net Summer Renewable Capacity 1,941 31.4 Geothermal - - Hydro Conventional 508 8.2 Solar - - Wind 1,423 23.0 Wood/Wood Waste - - MSW/Landfill Gas - - Other Biomass 10

  5. EIA - Renewable Electricity State Profiles

    Gasoline and Diesel Fuel Update (EIA)

    Oklahoma Renewable Electricity Profile 2010 Oklahoma profile Table 1. Summary Renewable Electric Power Industry Statistics (2010) Primary Renewable Energy Capacity Source Wind Primary Renewable Energy Generation Source Wind Capacity (megawatts) Value Percent of State Total Total Net Summer Electricity Capacity 21,022 100.0 Total Net Summer Renewable Capacity 2,412 11.5 Geothermal - - Hydro Conventional 858 4.1 Solar - - Wind 1,480 7.0 Wood/Wood Waste 58 0.3 MSW/Landfill Gas 16 0.1 Other Biomass

  6. EIA - Renewable Electricity State Profiles

    Gasoline and Diesel Fuel Update (EIA)

    Texas Renewable Electricity Profile 2010 Texas profile Table 1. Summary Renewable Electric Power Industry Statistics (2010) Primary Renewable Energy Capacity Source Wind Primary Renewable Energy Generation Source Wind Capacity (megawatts) Value Percent of State Total Total Net Summer Electricity Capacity 108,258 100.0 Total Net Summer Renewable Capacity 10,985 10.1 Geothermal - - Hydro Conventional 689 0.6 Solar 14 * Wind 9,952 9.2 Wood/Wood Waste 215 0.2 MSW/Landfill Gas 88 0.1 Other Biomass 28

  7. Danielson Wind | Open Energy Information

    Open Energy Info (EERE)

    Wind Jump to: navigation, search Name Danielson Wind Facility Danielson Wind Sector Wind energy Facility Type Commercial Scale Wind Facility Status In Service Developer Juhl Wind...

  8. Kawailoa Wind | Open Energy Information

    Open Energy Info (EERE)

    Wind Jump to: navigation, search Name Kawailoa Wind Facility Kawailoa Wind Sector Wind energy Facility Type Commercial Scale Wind Facility Status In Service Owner First Wind...

  9. Palouse Wind | Open Energy Information

    Open Energy Info (EERE)

    Wind Jump to: navigation, search Name Palouse Wind Facility Palouse Wind Sector Wind energy Facility Type Commercial Scale Wind Facility Status In Service Owner First Wind...

  10. Harbor Wind | Open Energy Information

    Open Energy Info (EERE)

    Wind Jump to: navigation, search Name Harbor Wind Facility Harbor Wind Sector Wind energy Facility Type Commercial Scale Wind Facility Status In Service Owner Harbor Wind LLC...

  11. Kahuku Wind | Open Energy Information

    Open Energy Info (EERE)

    Kahuku Wind Jump to: navigation, search Name Kahuku Wind Facility Kahuku Wind Sector Wind energy Facility Type Commercial Scale Wind Facility Status In Service Owner First Wind...

  12. Wiota Wind | Open Energy Information

    Open Energy Info (EERE)

    Wiota Wind Jump to: navigation, search Name Wiota Wind Facility Wiota Wind Sector Wind energy Facility Type Community Wind Facility Status In Service Owner Wiota Wind Energy LLC...

  13. Bravo Wind | Open Energy Information

    Open Energy Info (EERE)

    Bravo Wind Jump to: navigation, search Name Bravo Wind Facility Bravo Wind Sector Wind energy Facility Type Commercial Scale Wind Facility Status Proposed Developer Bravo Wind LLC...

  14. Auwahi Wind | Open Energy Information

    Open Energy Info (EERE)

    Auwahi Wind Jump to: navigation, search Name Auwahi Wind Facility Auwahi Wind Sector Wind energy Facility Type Commercial Scale Wind Facility Status In Service Owner BP Wind Energy...

  15. Traer Wind | Open Energy Information

    Open Energy Info (EERE)

    Traer Wind Jump to: navigation, search Name Traer Wind Facility Traer Wind Sector Wind energy Facility Type Community Wind Facility Status In Service Owner Norsemen Wind Energy LLC...

  16. Sheffield Wind | Open Energy Information

    Open Energy Info (EERE)

    Wind Jump to: navigation, search Name Sheffield Wind Facility Sheffield Wind Sector Wind energy Facility Type Commercial Scale Wind Facility Status In Service Owner First Wind...

  17. Rollins Wind | Open Energy Information

    Open Energy Info (EERE)

    Wind Jump to: navigation, search Name Rollins Wind Facility Rollins Wind Sector Wind energy Facility Type Commercial Scale Wind Facility Status In Service Owner First Wind...

  18. Non-Economic Obstacles to Wind Deployment: Issues and Regional Differences (Presentation)

    SciTech Connect (OSTI)

    Baring-Gould, I.

    2014-05-01

    This presentation provides an overview of national obstacles to wind deployment, with regional assessments. A special mention of offshore projects and distributed wind projects is provided. Detailed maps examine baseline capacity, military and flight radar, golden and bald eagle habitat, bat habitat, whooping crane habitat, and public lands. Regional deployment challenges are also discussed.

  19. Wyoming Wind Power Project (generation/wind)

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Wind Power > Generation Hydro Power Wind Power Monthly GSP BPA White Book Dry Year Tools Firstgov Wyoming Wind Power Project (Foote Creek Rim I and II) Thumbnail image of wind...

  20. Synthetic aperture radar capabilities in development

    SciTech Connect (OSTI)

    Miller, M.

    1994-11-15

    The Imaging and Detection Program (IDP) within the Laser Program is currently developing an X-band Synthetic Aperture Radar (SAR) to support the Joint US/UK Radar Ocean Imaging Program. The radar system will be mounted in the program`s Airborne Experimental Test-Bed (AETB), where the initial mission is to image ocean surfaces and better understand the physics of low grazing angle backscatter. The Synthetic Aperture Radar presentation will discuss its overall functionality and a brief discussion on the AETB`s capabilities. Vital subsystems including radar, computer, navigation, antenna stabilization, and SAR focusing algorithms will be examined in more detail.

  1. Offshore Wind Power USA

    Broader source: Energy.gov [DOE]

    The Offshore Wind Power USA conference provides the latest offshore wind market updates and forecasts.

  2. ARM: Ka-Band Scanning ARM Cloud Radar (KASACR) Zenith Pointing...

    Office of Scientific and Technical Information (OSTI)

    Language: English Subject: 54 Environmental Sciences Atmospheric turbulence; Cloud particle size distribution; Hydrometeor fall velocity; Radar Doppler; Radar polarization; Radar ...

  3. Wind Energy

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Wind Energy The DTU SpinnerLidar installed in the nacelle of the SWiFT facility A1 turbine Permalink Gallery First Wake Data Captured During Wake Steering Experiment at the SWiFT Facility News, Renewable Energy, SWIFT, Wind Energy, Wind News First Wake Data Captured During Wake Steering Experiment at the SWiFT Facility Researchers at Sandia National Laboratories and the National Renewable Energy Laboratory (NREL) have met a major project milestone as part of the Department of Energy Atmosphere

  4. First observations of tracking clouds using scanning ARM cloud radars

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Borque, Paloma; Giangrande, Scott; Kollias, Pavlos

    2014-12-01

    Tracking clouds using scanning cloud radars can help to document the temporal evolution of cloud properties well before large drop formation (‘‘first echo’’). These measurements complement cloud and precipitation tracking using geostationary satellites and weather radars. Here, two-dimensional (2-D) Along-Wind Range Height Indicator (AW-RHI) observations of a population of shallow cumuli (with and without precipitation) from the 35-GHz scanning ARM cloud radar (SACR) at the DOE Atmospheric Radiation Measurements (ARM) program Southern Great Plains (SGP) site are presented. Observations from the ARM SGP network of scanning precipitation radars are used to provide the larger scale context of the cloud fieldmore » and to highlight the advantages of the SACR to detect the numerous, small, non-precipitating cloud elements. A new Cloud Identification and Tracking Algorithm (CITA) is developed to track cloud elements. In CITA, a cloud element is identified as a region having a contiguous set of pixels exceeding a preset reflectivity and size threshold. The high temporal resolution of the SACR 2-D observations (30 sec) allows for an area superposition criteria algorithm to match cloud elements at consecutive times. Following CITA, the temporal evolution of cloud element properties (number, size, and maximum reflectivity) is presented. The vast majority of the designated elements during this cumulus event were short-lived non-precipitating clouds having an apparent life cycle shorter than 15 minutes. The advantages and disadvantages of cloud tracking using an SACR are discussed.« less

  5. WINDExchange: Selling Wind Power

    Wind Powering America (EERE)

    Market Sectors Printable Version Bookmark and Share Utility-Scale Wind Distributed Wind Motivations for Buying Wind Power Buying Wind Power Selling Wind Power Selling Wind Power Owners of wind turbines interconnected directly to the transmission or distribution grid, or that produce more power than the host consumes, can sell wind power as well as other generation attributes. Wind-Generated Electricity Electricity generated by wind turbines can be used to cover on-site energy needs

  6. Session: Avian migration and implications for wind power development in the Eastern United States

    SciTech Connect (OSTI)

    Mabey, Sarah; Cooper, Brian

    2004-09-01

    This session at the Wind Energy and Birds/Bats workshop consisted of two presentations followed by a discussion/question and answer period. The session was arranged to convey what is known about avian migration, particularly in the eastern US. The first presentation ''Migration Ecology: Issues of Scale and Behavior'' by Sarah Mabey frames the issue of migratory bird interactions with wind energy facilities from an ecological perspective: when, where, and why are migrant bird species vulnerable to wind turbine collision. The second presentation ''Radar Studies of Nocturnal Migration at Wind Sites in the Eastern US'' by Brian Cooper reported on radar studies conducted at wind sites in the eastern US, including Mount Storm, Clipper Wind, and others.

  7. Remote Cloud Sensing Intensive Observation Period (RCS-IOP) millimeter-wave radar calibration and data intercomparison

    SciTech Connect (OSTI)

    Sekelsky, S.M.; Firda, J.M.; McIntosh, R.E.

    1996-04-01

    During April 1994, the University of Massachusetts (UMass) and the Pennsylvania State University (Penn State) fielded two millimeter-wave atmospheric radars in the Atmospheric Radiation Measurement Remote Cloud Sensing Intensive Operation Period (RCS-IOP) experiment. The UMass Cloud Profiling Radar System (CPRS) operates simultaneously at 33.12 GHz and 94.92 GHz through a single antenna. The Penn State radar operates at 93.95 GHz and has separate transmitting and receiving antennas. The two systems were separated by approximately 75 meters and simultaneously observed a variety of cloud types at verticle incidence over the course of the experiment. This abstract presents some initial results from our calibration efforts. An absolute calibration of the UMass radar was made from radar measurements of a trihedral corner reflector, which has a known radar cross-section. A relative calibration of between the Penn State and UMass radars is made from the statistical comparison of zenith pointing measurements of low altitude liquid clouds. Attenuation is removed with the aid of radiosonde data, and the difference in the calibration between the UMass and Penn State radars is determined by comparing the ratio of 94-GHz and 95-GHz reflectivity values to a model that accounts for parallax effects of the two antennas used in the Penn State system.

  8. Two terminal micropower radar sensor

    DOE Patents [OSTI]

    McEwan, T.E.

    1995-11-07

    A simple, low power ultra-wideband radar motion sensor/switch configuration connects a power source and load to ground. The switch is connected to and controlled by the signal output of a radar motion sensor. The power input of the motion sensor is connected to the load through a diode which conducts power to the motion sensor when the switch is open. A storage capacitor or rechargeable battery is connected to the power input of the motion sensor. The storage capacitor or battery is charged when the switch is open and powers the motion sensor when the switch is closed. The motion sensor and switch are connected between the same two terminals between the source/load and ground. 3 figs.

  9. Two terminal micropower radar sensor

    DOE Patents [OSTI]

    McEwan, Thomas E.

    1995-01-01

    A simple, low power ultra-wideband radar motion sensor/switch configuration connects a power source and load to ground. The switch is connected to and controlled by the signal output of a radar motion sensor. The power input of the motion sensor is connected to the load through a diode which conducts power to the motion sensor when the switch is open. A storage capacitor or rechargeable battery is connected to the power input of the motion sensor. The storage capacitor or battery is charged when the switch is open and powers the motion sensor when the switch is closed. The motion sensor and switch are connected between the same two terminals between the source/load and ground.

  10. Social Acceptance of Wind: A Brief Overview (Presentation)

    SciTech Connect (OSTI)

    Lantz, E.

    2015-01-01

    This presentation discusses concepts and trends in social acceptance of wind energy, profiles recent research findings, and discussions mitigation strategies intended to resolve wind power social acceptance challenges as informed by published research and the experiences of individuals participating in the International Energy Agencies Working Group on Social Acceptance of Wind Energy

  11. Radar channel balancing with commutation

    SciTech Connect (OSTI)

    Doerry, Armin Walter

    2014-02-01

    When multiple channels are employed in a pulse-Doppler radar, achieving and maintaining balance between the channels is problematic. In some circumstances the channels may be commutated to achieve adequate balance. Commutation is the switching, trading, toggling, or multiplexing of the channels between signal paths. Commutation allows modulating the imbalance energy away from the balanced energy in Doppler, where it can be mitigated with filtering.

  12. Milford Wind Corridor Phase I (Clipper) Wind Farm | Open Energy...

    Open Energy Info (EERE)

    Clipper) Wind Farm Jump to: navigation, search Name Milford Wind Corridor Phase I (Clipper) Wind Farm Facility Milford Wind Corridor Phase I (Clipper) Sector Wind energy Facility...

  13. A Comparison of ARM Cloud Radar Profiles with MMF Simulated Radar...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    It has been used as a tool in evaluating global climate and weather models (Hewitson and Crane 1994, 1996; Tennant 2003) including cloud properties (Jakob et al. 2003, 2004). Why ...

  14. Heating Profiles Derived From Cm-wavelength Radar During TWP...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    heating Dry monsoon (10.5 mm day -1 ) - Weaker events with a large shallow convection component and lower level heating Break period (8.5 mm day -1 ) - Mostly deep convection...

  15. JD Wind 6 Wind Farm | Open Energy Information

    Open Energy Info (EERE)

    JD Wind 6 Wind Farm Jump to: navigation, search Name JD Wind 6 Wind Farm Facility JD Wind 6 Sector Wind energy Facility Type Commercial Scale Wind Facility Status In Service Owner...

  16. JD Wind 7 Wind Farm | Open Energy Information

    Open Energy Info (EERE)

    JD Wind 7 Wind Farm Jump to: navigation, search Name JD Wind 7 Wind Farm Facility JD Wind 7 Sector Wind energy Facility Type Commercial Scale Wind Facility Status In Service Owner...

  17. Metro Wind LLC Wind Farm | Open Energy Information

    Open Energy Info (EERE)

    Wind LLC Wind Farm Jump to: navigation, search Name Metro Wind LLC Wind Farm Facility Metro Wind LLC Sector Wind energy Facility Type Commercial Scale Wind Facility Status In...

  18. Michigan Wind II Wind Farm | Open Energy Information

    Open Energy Info (EERE)

    II Wind Farm Jump to: navigation, search Name Michigan Wind II Wind Farm Facility Michigan Wind II Wind Farm Sector Wind energy Facility Type Commercial Scale Wind Facility Status...

  19. Radar range measurements in the atmosphere.

    SciTech Connect (OSTI)

    Doerry, Armin Walter

    2013-02-01

    The earth's atmosphere affects the velocity of propagation of microwave signals. This imparts a range error to radar range measurements that assume the typical simplistic model for propagation velocity. This range error is a function of atmospheric constituents, such as water vapor, as well as the geometry of the radar data collection, notably altitude and range. Models are presented for calculating atmospheric effects on radar range measurements, and compared against more elaborate atmospheric models.

  20. Characterization of Radar Boundary Layer Data Collected During the 2001 Multi-Frequency Radar IOP

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Characterization of Radar Boundary Layer Data Collected During the 2001 Multi-Frequency Radar IOP A. Khandwalla, N. Majurec, and S. M. Sekelsky University of Massachusetts Amherst, Massachusetts C. R. Williams and K. S. Gage National Oceanic and Atmospheric Administration Aeronomy Laboratory Boulder, Colorado Introduction Ground-based radar measurements of insect clutter at Ka-band (35 GHz) and W-band (95 GHz) were collected over an extended period during the 2001 multi-frequency radar (MFR)

  1. Garnet Wind | Open Energy Information

    Open Energy Info (EERE)

    Wind Jump to: navigation, search Name Garnet Wind Facility Garnet Wind Sector Wind energy Facility Type Commercial Scale Wind Facility Status In Service Owner Azusa Light & Water...

  2. Lime Wind | Open Energy Information

    Open Energy Info (EERE)

    Wind Jump to: navigation, search Name Lime Wind Facility Lime Wind Sector Wind energy Facility Type Commercial Scale Wind Facility Status In Service Owner Joseph Millworks Inc...

  3. Fairhaven Wind | Open Energy Information

    Open Energy Info (EERE)

    Wind Jump to: navigation, search Name Fairhaven Wind Facility Fairhaven Wind Sector Wind energy Facility Type Community Wind Facility Status In Service Owner Solaya Energy Palmer...

  4. Scituate Wind | Open Energy Information

    Open Energy Info (EERE)

    Wind Jump to: navigation, search Name Scituate Wind Facility Scituate Wind Sector Wind energy Facility Type Community Wind Facility Status In Service Owner Solaya Energy ...

  5. Pacific Wind | Open Energy Information

    Open Energy Info (EERE)

    Wind Jump to: navigation, search Name Pacific Wind Facility Pacific Wind Sector Wind energy Facility Type Commercial Scale Wind Facility Status In Service Owner enXco Developer...

  6. Galactic Wind | Open Energy Information

    Open Energy Info (EERE)

    Wind Jump to: navigation, search Name Galactic Wind Facility Galactic Wind Sector Wind energy Facility Type Commercial Scale Wind Facility Status In Service Owner Epic Systems...

  7. Rockland Wind | Open Energy Information

    Open Energy Info (EERE)

    Wind Jump to: navigation, search Name Rockland Wind Facility Rockland Wind Sector Wind energy Facility Type Commercial Scale Wind Facility Status In Service Developer Ridgeline...

  8. Greenfield Wind | Open Energy Information

    Open Energy Info (EERE)

    Jump to: navigation, search Name Greenfield Wind Facility Greenfield Wind Sector Wind energy Facility Type Community Wind Facility Status In Service Owner Greenfield Wind Power...

  9. Willmar Wind | Open Energy Information

    Open Energy Info (EERE)

    Wind Jump to: navigation, search Name Willmar Wind Facility Willmar Wind Sector Wind energy Facility Type Commercial Scale Wind Facility Status In Service Owner Willmar...

  10. NREL: Innovation Impact - Wind

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Wind Energy Menu Home Home Solar Solar Wind Wind Analysis Analysis Bioenergy Bioenergy Buildings Buildings Transportation Transportation Manufacturing Manufacturing Energy Systems ...

  11. Energy 101: Wind Turbines

    ScienceCinema (OSTI)

    None

    2013-05-29

    See how wind turbines generate clean electricity from the power of the wind. Highlighted are the various parts and mechanisms of a modern wind turbine.

  12. Wind Program News

    SciTech Connect (OSTI)

    2012-01-06

    Stay current on the news about the wind side of the Wind and Water Power Program and important wind energy events around the U.S.

  13. Wind turbine

    DOE Patents [OSTI]

    Cheney, Jr., Marvin C.

    1982-01-01

    A wind turbine of the type having an airfoil blade (15) mounted on a flexible beam (20) and a pitch governor (55) which selectively, torsionally twists the flexible beam in response to wind turbine speed thereby setting blade pitch, is provided with a limiter (85) which restricts unwanted pitch change at operating speeds due to torsional creep of the flexible beam. The limiter allows twisting of the beam by the governor under excessive wind velocity conditions to orient the blades in stall pitch positions, thereby preventing overspeed operation of the turbine. In the preferred embodiment, the pitch governor comprises a pendulum (65,70) which responds to changing rotor speed by pivotal movement, the limiter comprising a resilient member (90) which engages an end of the pendulum to restrict further movement thereof, and in turn restrict beam creep and unwanted blade pitch misadjustment.

  14. Ultra-wideband radar motion sensor

    DOE Patents [OSTI]

    McEwan, T.E.

    1994-11-01

    A motion sensor is based on ultra-wideband (UWB) radar. UWB radar range is determined by a pulse-echo interval. For motion detection, the sensors operate by staring at a fixed range and then sensing any change in the averaged radar reflectivity at that range. A sampling gate is opened at a fixed delay after the emission of a transmit pulse. The resultant sampling gate output is averaged over repeated pulses. Changes in the averaged sampling gate output represent changes in the radar reflectivity at a particular range, and thus motion. 15 figs.

  15. ARM - Evaluation Product - Corrected Precipitation Radar Moments...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    ProductsCorrected Precipitation Radar Moments in Antenna Coordinates Documentation Use the Data File Inventory tool to view data availability at the file level. Comments? We would...

  16. Correcting radar range measurements for atmospheric propagation...

    Office of Scientific and Technical Information (OSTI)

    Title: Correcting radar range measurements for atmospheric propagation effects. Abstract not provided. Authors: Doerry, Armin Walter Publication Date: 2013-12-01 OSTI Identifier: ...

  17. Balancing radar receiver channels with commutation. (Conference...

    Office of Scientific and Technical Information (OSTI)

    Title: Balancing radar receiver channels with commutation. Abstract not provided. Authors: Doerry, Armin Walter Publication Date: 2015-01-01 OSTI Identifier: 1244859 Report ...

  18. Synthetic Aperture Radar Persistent Scatterer Interferometry...

    Open Energy Info (EERE)

    NA, 2010 DOI Not Provided Check for DOI availability: http:crossref.org Online Internet link for Synthetic Aperture Radar Persistent Scatterer Interferometry (PSInSAR)...

  19. National Offshore Wind Energy Grid Interconnection Study

    SciTech Connect (OSTI)

    Daniel, John P.; Liu, Shu; Ibanez, Eduardo; Pennock, Ken; Reed, Greg; Hanes, Spencer

    2014-07-30

    The National Offshore Wind Energy Grid Interconnection Study (NOWEGIS) considers the availability and potential impacts of interconnecting large amounts of offshore wind energy into the transmission system of the lower 48 contiguous United States. A total of 54GW of offshore wind was assumed to be the target for the analyses conducted. A variety of issues are considered including: the anticipated staging of offshore wind; the offshore wind resource availability; offshore wind energy power production profiles; offshore wind variability; present and potential technologies for collection and delivery of offshore wind energy to the onshore grid; potential impacts to existing utility systems most likely to receive large amounts of offshore wind; and regulatory influences on offshore wind development. The technologies considered the reliability of various high-voltage ac (HVAC) and high-voltage dc (HVDC) technology options and configurations. The utility system impacts of GW-scale integration of offshore wind are considered from an operational steady-state perspective and from a regional and national production cost perspective.

  20. Radar network communication through sensing of frequency hopping

    DOE Patents [OSTI]

    Dowla, Farid; Nekoogar, Faranak

    2013-05-28

    In one embodiment, a radar communication system includes a plurality of radars having a communication range and being capable of operating at a sensing frequency and a reporting frequency, wherein the reporting frequency is different than the sensing frequency, each radar is adapted for operating at the sensing frequency until an event is detected, each radar in the plurality of radars has an identification/location frequency for reporting information different from the sensing frequency, a first radar of the radars which senses the event sends a reporting frequency corresponding to its identification/location frequency when the event is detected, and all other radars in the plurality of radars switch their reporting frequencies to match the reporting frequency of the first radar upon detecting the reporting frequency switch of a radar within the communication range. In another embodiment, a method is presented for communicating information in a radar system.

  1. Polarimetric radar and aircraft observations of saggy bright bands during MC3E

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Matthew R. Kumjian; Giangrande, Scott E.; Mishra, Subashree; Toto, Tami; Ryzhkov, Alexander V.; Bansemer, Aaron

    2016-03-19

    Polarimetric radar observations increasingly are used to understand cloud microphysical processes, which is critical for improving their representation in cloud and climate models. In particular, there has been recent focus on improving representations of ice collection processes (e.g., aggregation, riming), as these influence precipitation rate, heating profiles, and ultimately cloud life cycles. However, distinguishing these processes using conventional polarimetric radar observations is difficult, as they produce similar fingerprints. This necessitates improved analysis techniques and integration of complementary data sources. Furthermore, the Midlatitude Continental Convective Clouds Experiment (MC3E) provided such an opportunity.

  2. Wind Career Map: Resource List | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Career Map: Resource List Wind Career Map: Resource List The following resources were used in the development of the Wind Career Map, associated job profile information, or are potential resources for interested Wind Career Map viewers. Competencies for Careers in Renewable Energy Together with the Department of Labor, the Office of Energy Efficiency and Renewable Energy developed a comprehensive Renewable Energy Competency Model that includes wind energy job skills and knowledge as one of

  3. NREL: Wind Research - Site Wind Resource Characteristics

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Site Wind Resource Characteristics A graphic showing the location of National Wind Technology Center and its wind power class 2. Click on the image to view a larger version. ...

  4. NREL: Wind Research - Offshore Wind Turbine Research

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Offshore Wind Turbine Research Photo of a European offshore wind farm. Photo by Siemens For more than eight years, NREL has worked with the U.S. Department of Energy (DOE) to become an international leader in offshore wind energy research. NREL's offshore wind turbine research capabilities focus on critical areas that reflect the long-term needs of the industry and DOE. National Wind Technology Center (NWTC) researchers are perpetually exploring new wind and water power concepts, materials, and

  5. Wind | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Science & Innovation Energy Sources Renewable Energy Wind Wind Wind The United States is home to one of the largest and fastest growing wind markets in the world. To stay ...

  6. NREL: Wind Research - Wind Energy Videos

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Wind Energy Videos The National Wind Technology Center (NWTC) is pleased to offer video presentations of its world-class capabilities, facilities, research areas, and personnel. As ...

  7. NREL: Wind Research - Wind Resource Assessment

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Wind Resource Assessment A map of the United States is color-coded to indicate the high winds at 80 meters. This map shows the wind resource at 80 meters for both land-based and offshore wind resources in the United States. Correct estimation of the energy available in the wind can make or break the economics of wind plant development. Wind mapping and validation techniques developed at the National Wind Technology Center (NWTC) along with collaborations with U.S. companies have produced

  8. Wind Integration National Dataset (WIND) Toolkit

    Broader source: Energy.gov [DOE]

    For utility companies, grid operators and other stakeholders interested in wind energy integration, collecting large quantities of high quality data on wind energy resources is vitally important....

  9. ARM Climate Research Facility Radar Operations Plan (Program...

    Office of Scientific and Technical Information (OSTI)

    Climate Research Facility Radar Operations Plan Citation Details In-Document Search Title: ARM Climate Research Facility Radar Operations Plan Roles, responsibilities, and ...

  10. ARM: Ka ARM Zenith Radar (KAZR): filtered spectral data, moderate...

    Office of Scientific and Technical Information (OSTI)

    Title: ARM: Ka ARM Zenith Radar (KAZR): filtered spectral data, moderate sensitivity mode, cross-polarized mode Ka ARM Zenith Radar (KAZR): filtered spectral data, moderate ...