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At least 919 records · Page 51
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Prediction of the SYM-H Index Using a Bayesian Deep Learning Method With Uncertainty Quantification

We propose a novel deep learning framework, named SYMHnet, which employs a graph neural network and a bidirectional long short-term memory network to cooperatively learn patterns from solar wind and interplanetary magnetic field parameters for short-term forecasts of the SYM-H index based on 1- and 5-min resolution data. SYMHnet takes, as input, the time series of the parameters' values provided by NASA's Space Science Data Coordinated Archive and predicts, as output, the SYM-H index value at time point t + w hours for a given time point t where w is 1 or 2. By incorporating Bayesian inference into the learning framework, SYMHnet can quantify both aleatoric (data) uncertainty and epistemic (model) uncertainty when predicting future SYM-H indices. Experimental results show that SYMHnet works well at quiet time and storm time, for both 1- and 5-min resolution data. The results also show that SYMHnet generally performs better than related machine learning methods. For example, SYMHnet achieves a forecast skill score (FSS) of 0.343 compared to the FSS of 0.074 of a recent gradient boosting machine (GBM) method when predicting SYM-H indices (1 hr in advance) in a large storm (SYM-H = -393 nT) using 5-min resolution data. When predicting the SYM-H indices (2 hr in advance) in the large storm, SYMHnet achieves an FSS of 0.553 compared to the FSS of 0.087 of the GBM method. In addition, SYMHnet can provide results for both data and model uncertainty quantification, whereas the related methods cannot.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

A2E2G (Atmosphere to Electrons to the Grid platform) [SWR-23-22]

A2E2G is a platform that integrates 1) forecasting tools to account for weather uncertainty, with 2) aerodynamic wind plant models to account for wake dynamics and wind plant operation, and 3) economic models to advise on operation for a wind power plant that offers grid services in addition to energy. The A2E2G platform can be used as a high-level controller for a wind plant for market participation and real-time wind plant control. The A2E2g platform is a holistic Python tool with modules that can be run to 1) advise on market participation and 2) control and operate a wind power plant in real time. The A2E2g framework assumes two stages: the first stage is in day-ahead and the second stage is in real-time. Managing uncertainty is key in the first stage and managing variability is key in the second stage. The different components have models written and developed in the Python programming language. The code is assembled into a Python package and can be easily downloaded and installed from the A2E2g repository (https://github.com/NREL/a2e2g).

Sinner, Michael↗
DOE OSTI2011

Meteorological Observations for Renewable Energy Applications at Site 300

In early October 2010, two Laser and Detection Ranging (LIDAR) units (LIDAR-96 and LIDAR-97), a 3 m tall flux tower, and a 3 m tall meteorological tower were installed in the northern section of Site 300 (Figure 1) as a first step in development of a renewable energy testbed facility. This section of the SMS project is aimed at supporting that effort with continuous maintenance of atmospheric monitoring instruments capable of measuring vertical profiles of wind speed and wind direction at heights encountered by future wind power turbines. In addition, fluxes of energy are monitored to estimate atmospheric mixing and its effects on wind flow properties at turbine rotor disk heights. Together, these measurements are critical for providing an accurate wind resource characterization and for validating LLNL atmospheric prediction codes for future renewable energy projects at Site 300. Accurate, high-resolution meteorological measurements of wind flow in the planetary boundary layer (PBL) and surface-atmosphere energy exchange are required for understanding the properties and quality of available wind power at Site 300. Wind speeds at heights found in a typical wind turbine rotor disk (~ 40-140 m) are driven by the synergistic impacts of atmospheric stability, orography, and land-surface characteristics on the mean wind flow in the PBL and related turbulence structures. This section of the report details the maintenance and labor required in FY11 to optimize the meteorological instruments and ensure high accuracy of their measurements. A detailed look at the observations from FY11 is also presented. This portion of the project met the following milestones: Milestone 1: successful maintenance and data collection of LIDAR and flux tower instruments; Milestone 2: successful installation of solar power for the LIDAR units; and Milestone 3: successful implementation of remote data transmission for the LIDAR units.

17 WIND ENERGY↗
DOE OSTI2024

WTK-LED: The WIND Toolkit Long-Term Ensemble Dataset

To satisfy a wide group of stakeholders across various wind energy disciplines, including but not limited to stakeholders in the distributed and utility scale wind industry, the new emerging airborne wind energy field, grid integration, power systems modeling, environmental modeling, and researchers in academia, and to close some of the gaps that current public datasets have, we aimed at developing an updated version of the meteorological WIND Toolkit, named WIND Toolkit Long-term Ensemble Dataset (WTK-LED), which is a meteorological dataset providing time series every 5 min and 2 km, including model uncertainty of wind speed at every modeling grid point so that users are provided with a range of possible wind speeds every 2 km. The data were produced using the Weather Research and Forecasting Model (WRF). The vertical grid used in WTK-LED includes many vertical layers in the atmospheric boundary layer to provide information of atmospheric quantities across the rotor layer of utility scale and distributed wind turbines. The WTK-LED includes: 1) Numerical simulations covering the continental United States, Alaska, and Hawaii, with high-resolution data being available for 3 years (2018-2020). 2) Climate simulations from Argonne National Laboratories covering the North American continent, including Alaska, Canada, and most of Mexico and the Caribbean Islands. These simulations complement the new WTK-LED to offer a 4-km dataset covering 20 years, from 2001-2020. 3) Specific long-term,high-resolution offshore simulations have been conducted separately for the US coasts, Hawaii, and the Great Lakes, leading to the 2023 National Offshore Wind data set. This report focuses on a description of the land-based WTK-LED for CONUS, Hawaii, and Alaska, for the 3-year 2-km/5-min dataset and the 20-year 4-km/hourly dataset, as well as the uncertainty quantification method. We also provide limited validation results. Based on our results to date, we suggest use cases and applications for each dataset of the WTK-LED.

17 WIND ENERGY↗
DOE OSTI2016

Forecasting the northern African dust outbreak towards Europe in April 2011: A model intercomparison

In the framework of the World Meteorological Organisation's Sand and Dust Storm Warning Advisory and Assessment System, we evaluated the predictions of five state-of-the-art dust forecast models during an intense Saharan dust outbreak affecting western and northern Europe in April 2011. We assessed the capacity of the models to predict the evolution of the dust cloud with lead times of up to 72 h using observations of aerosol optical depth (AOD) from the AErosol RObotic NETwork (AERONET) and the Moderate Resolution Imaging Spectroradiometer (MODIS) and dust surface concentrations from a ground-based measurement network. In addition, the predicted vertical dust distribution was evaluated with vertical extinction profiles from the Cloud and Aerosol Lidar with Orthogonal Polarization (CALIOP). To assess the diversity in forecast capability among the models, the analysis was extended to wind field (both surface and profile), synoptic conditions, emissions and deposition fluxes. Models predict the onset and evolution of the AOD for all analysed lead times. On average, differences among the models are larger than differences among lead times for each individual model. In spite of large differences in emission and deposition, the models present comparable skill for AOD. In general, models are better in predicting AOD than near-surface dust concentration over the Iberian Peninsula. Models tend to underestimate the long-range transport towards northern Europe. In this paper, our analysis suggests that this is partly due to difficulties in simulating the vertical distribution dust and horizontal wind. Differences in the size distribution and wet scavenging efficiency may also account for model diversity in long-range transport.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1978

IPS activity observed as a precursor of solar induced terrestrial activity

A radio telescope designed to exploit the interplanetary scintillation (IPS) technique and locate, map, and track solar wind disturbances which result in geomagnetic disturbances, thereby providing a forecast capability, is described. Preliminary results from operation of the telescope include: (1) evidence for a precursor signal in the IPS activity with a 1-2 day lead time with respect to density enhancements which frequently give rise to geomagnetic activity; (2) detection of a spectral broadening signature which also serves as a precursor of geomagnetic activity; (3) out-of-the-ecliptic plasma density enhancements which were not detected by near-Earth, ecliptic plane spacecraft; (4) detection of 12 corotating density enhancements;(5) detection of over 80 sources which give detectable scintillation of which 45 have been used for detailed synoptic analysis and 9 for spectral analysis; and (6) measurement of 0-lag coefficient of 0.56 between density and IPS activity enhancements.

Cronyn, W. M.↗
NASA NTRS1985

Analysis/forecast experiments with a multivariate statistical analysis scheme using FGGE data

A three-dimensional, multivariate, statistical analysis method, optimal interpolation (OI) is described for modeling meteorological data from widely dispersed sites. The model was developed to analyze FGGE data at the NASA-Goddard Laboratory of Atmospherics. The model features a multivariate surface analysis over the oceans, including maintenance of the Ekman balance and a geographically dependent correlation function. Preliminary comparisons are made between the OI model and similar schemes employed at the European Center for Medium Range Weather Forecasts and the National Meteorological Center. The OI scheme is used to provide input to a GCM, and model error correlations are calculated for forecasts of 500 mb vertical water mixing ratios and the wind profiles. Comparisons are made between the predictions and measured data. The model is shown to be as accurate as a successive corrections model out to 4.5 days.

Baker, W. E.↗
DOE OSTI2018

Transient Stability Analysis for Offshore Wind Power Plant Integration Planning Studies - Part I: Short Term Faults

Power system planning is the process of forecasting load demand and ensuring sufficient generation and reserve capacities over some planning horizon. This process includes investigation of steady-state and dynamic operation of power system of interest. This paper addresses the transient stability (also known as large-signal stability) analysis of power systems for offshore wind power plant integration planning studies. In particular, this study develops a comprehensive practical methodology to assess transient stability of power systems, including rotor angle stability, voltage stability and frequency response for all fault types for large scale power systems. This methodology considers variability of the offshore wind power plants as well as the type of any faulted components present and is applicable to the study of both short term and long term faults, though only short term faults are considered here (long term faults are treated sequentially in a companion paper). Furthermore, this paper considers the integration of offshore wind power plants into existing power systems and demonstrates the utility of this methodology through the examination of the specific case of integrating 1,000MW of offshore wind power into the FirstEnergy/PJM service territory using a realistic model of 63k-bus test system that represents the U.S. Eastern Interconnection.

17 WIND ENERGY↗
DOE OSTI2026

Wind and Temperature Consensus at Horn Point, HU-Beltsville, Piney Run (Maryland) in support of CoURAGE

The Maryland Department of the Environment (MDE) operates a ground-based atmospheric profiling network consisting of collocated radar wind profilers (RWP) and radio acoustic sounding systems (RASS) as part of its Ambient Air Monitoring Program. This network provides continuous observations of wind and temperature structure in the lower troposphere to support air quality forecasting, regulatory analysis, and atmospheric research. The network currently includes three fixed sites across Maryland: Horn Point (HP, lower eastern shore) [38.587525°,-76.141006°], Howard University-Beltsville (HUB, central Maryland) [39.055277°, -76.878632°], and Piney Run (PR, western Maryland) [39.705950°, -79.012000°] The network is designed to capture regional variability in atmospheric transport and boundary-layer processes. These systems measure vertical profiles of horizontal wind speed and direction using Doppler radar techniques, with observations typically spanning from ~100 m above ground level up to approximately 2.5–4 km. Measurements are derived from the Doppler shift of backscattered electromagnetic signals, enabling retrieval of wind vectors at multiple altitudes with high temporal resolution (e.g., 30-minute averages reported every 6 minutes). Each radar wind profiler is paired with a Radio Acoustic Sounding System (RASS) to provide profiles of virtual temperature in the lower atmosphere (~100–200 m AGL) by measuring the propagation speed of acoustic waves. Together, the RWP/RASS system yields a coupled data set of thermodynamic and kinematic atmospheric structure, including additional parameters such as vertical velocity, radial velocity, signal-to-noise ratio, and spectral width for advanced analysis. There are two types of files for each station: wind data (files with a "w" prefix) and virtual temperature RASS data (files with a "t" prefix). The wind data files are in the format wYYDDD.cns, where YY is the 2-digit year and DDD is the day of the year. The RASS virtual temperature data files are in the format tYYDDD.cns. Each record has the following header structure: Line 1 : Station Name RASS files Line 2 : RASS rev DeTect_2.0, WINDS files Line 2 : WINDS rev ATI 5.1 Line 3 : N latitude, W longitude, and site elevation (m) Line 4 : Date and begin time of consensus: yy mm dd hh mn ss plus # minutes to add to get UTC Line 5 : Consensus averaging time (minutes); number of beams; number of range gates Line 6 : Number of records required to make consensus (num) total number of records (tot) and the consensus window size (m/s) in the format: num:tot (window) RASS files Line 7 : no. of coded cells, no. of spec, pulse width (ns), and inter-pulse period (µs), WINDS files Line 7 : No. of coded cells, no. of spectra, pulse width (ns), and inter-pulse period (µs), each with a pair of values: first value is for oblique beams, second for vertical RASS files Line 8 : Full scale Doppler value (m/s) Delay to first gate (ns) Number of gates Spacing of gates (ns), WINDS files Line 8 : Full scale Doppler velocity (m/s), oblique and vertical Vertical correction applied to oblique beams? (0 = no, 1 = yes) Delay to first gate (ns), oblique and vertical Number of gates, oblique and vertical Spacing of gates (ns), oblique and vertical Line 9 : Azimuth and elevation (9s indicate vertical beam not used) RASS files Line 10, values : HT = Height above ground (km), T = Uncorrected virtual temperature consensus (deg C), Tc = Corrected virtual temperature consensus (deg C), W = Vertical wind consensus (9s indicate vertical beam not used, w-component, positive upward, m/s), CNT = Number of records that made consensus (for the 3 values in same order), SNR = Average signal to noise ratio (dB) of records in consensus (same order) WINDS files Line 10, values : HT = Height above ground (km), SPD = Wind speed (m/s), DIR = Wind direction (deg E of N from N), RAD = Radial velocities for each beam (m/s) in order given in azimuth and elevation line (positive toward radar; 9s indicate vertical beam not used, CNT = Number of records that made consensus, SNR = Average signal to noise ratio (dB) of records in consensus

{"wind speed and direction",temperature}↗
NASA NTRS1988

Meteorological aspects of cloud-to-ground lightning in the Kennedy Space Center region

This paper examines the meteorological environment in which cloud-to-ground lightning occurs at the Kennedy Space Center (KSC) region during summer. Using the lightning patterns of central Florida, flashes from individual thunderstorms were analyzed for five low-level wind regimes during three summers. The results showed large differences between the number, timing, and location of flashes for varying flow regimes, with southwest flow being the most prolific producer of flashes in the KSC area. In the second part of the study, short-term forecasts of lightning were investigated using the divergence measured by the KSC surface wind network. An interval of about 1 hour was found from the beginning of a convergence event to first lightning. Monitoring 5-min surface convergence, in combination with understanding the climatology of lightning related to the daily flow regime, made it possible to isolate the lightning. Results were used successfully in operations at KSC.

Holle, Ronald L.↗
DOE OSTI2017

Entrainment rate diurnal cycle in marine stratiform clouds estimated from geostationary satellite retrievals and a meteorological forecast model: Entrainment Rate in Stratiform Clouds

The mean diurnal cycle of cloud entrainment rate (w e ) over the northeast Pacific region is for the first time computed by combining, in a mixed-layer model framework, the hourly composited GOES-15 satellite-based cloud top height (H T ) tendency, advection, and large-scale vertical velocity (w) during May to September 2013, with horizontal winds and w taken from the European Centre for Medium-Range Weather Forecasts (ECMWF) model. The tendency term dominates the magnitude and phase of the w e diurnal cycle, with a secondary role of w, and a modest advective contribution. The peak and minimum in w e occur between 20:00–22:00 LT and 9:00–11:00 LT, respectively, in close agreement with the diurnal cycle of turbulence driven by cloud top longwave cooling. Uncertainties in H T and ECMWF fields are assessed with in situ observations and three meteorological reanalysis data sets. This study provides the basis for constructing nearly global climatologies of w e by combining a suite of well-calibrated geostationary satellites.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2011

Western Wind and Solar Integration Study

The Western Wind and Solar Integration Study (WWSIS) is one of the largest regional wind and solar integration studies to date. It was initiated in 2007 to examine the operational impact of up to 35% energy penetration of wind, photovoltaics (PV), and concentrating solar power (CSP) on the power system operated by the WestConnect group of utilities in Arizona, Colorado, Nevada, New Mexico, and Wyoming (see study area map). WestConnect also includes utilities in California, but these were not included because California had already completed a renewable energy integration study for the state. This study was set up to answer questions that utilities, public utilities commissions, developers, and regional planning organizations had about renewable energy use in the west: (1) Does geographic diversity of renewable energy resource help mitigate variability; (2) How do local resources compare to out-of-state resources; (3) Can balancing area cooperation help mitigate variability; (4) What is the role and value of energy storage; (5) Should reserve requirements be modified; (6) What is the benefit of forecasting; and (7) How can hydropower help with integration of renewables? The Western Wind and Solar Integration Study is sponsored by the U.S. Department of Energy (DOE) and run by NREL with WestConnect as a partner organization. The study follows DOE's 20% Wind Energy by 2030 report, which did not find any technical barriers to reaching 20% wind energy in the continental United States by 2030. This study and its partner study, the Eastern Wind Integration and Transmission Study, performed a more in-depth operating impact analysis to see if 20% wind energy was feasible from an operational level. In DOE/NREL's analysis, the 20% wind energy target required 25% wind energy in the western interconnection; therefore, this study considered 20% and 30% wind energy to bracket the DOE analysis. Additionally, since solar is rapidly growing in the west, 5% solar was also considered in this study. The goal of the Western Wind and Solar Integration Study is to understand the costs and operating impacts due to the variability and uncertainty of wind, PV, and CSP on the grid. This is mainly an operations study, (rather than a transmission study), although different scenarios model different transmission build-outs to deliver power. Using a detailed power system production simulation model, the study identifies operational impacts and challenges of wind energy penetration up to 30% of annual electricity consumption.

14 SOLAR ENERGY↗
DOE OSTI2011

Atlas of global wave energy from 10 years of reanalysis and hindcast data

Development of ocean wave energy requires general knowledge of the wave climate as well as reliable estimates of the available power. A WAVEWATCH III hindcast study with surface winds from the Final Global Tropospheric Analysis (FNL) provides 10 years of spectral wave data for a thorough examination of the wave resource. The fully assimilated FNL data provides accurate wind input for more reliable predictions of the wave conditions than the operational forecasts. The computed wave parameters show good correlation with Jason-1 altimetry and buoy measurements. Here, the monthly median plots describe the seasonal variation of the global wave climate and the percentile plots indicate the persistence and severity of the wave conditions. Separate estimates of the power from the wind waves and primary swell provide a precise description of the resource in support of design and planning of wave energy converters.

16 TIDAL AND WAVE POWER↗
NASA NTRS1992

Upper tropospheric equatorial waves in ECMWF analyses

An observational study is presented of travelling waves in the near-equatorial upper tropospheric wind field as revealed in operational analyses produced by the European Center for Medium-range Weather Forecasts (ECMWF) over the years 1980-1987. Space-time spectra are presented that reveal the seasonal and interannual variability of traveling waves in the tropical wind fields. The zonal wind spectra exhibit a majority of power in the lowest resolved frequencies, and there is a lack of notable spectral peaks. The upper tropospheric meridional wind spectra show maxima for westward-propagating zonal waves 4-7 with 6- to 10-day periods. The events are also longitudinally localized, with a preference for westward-propagating waves occurring over the eastern Pacific Ocean during August-September. The waves exhibit maximum amplitudes in the upper troposphere and weak coherence with the near-surface layers of the atmosphere.

Randel, William J.↗
DOE OSTI2014

DOE SBIR Phase II Final Technical Report - Assessing Climate Change Effects on Wind Energy

Specialized Vertum Partners software tools were prototyped, tested and commercialized to allow wind energy stakeholders to assess the uncertainties of climate change on wind power production and distribution. This project resulted in three commercially proven products and a marketing tool. The first was a Weather Research and Forecasting Model (WRF) based resource evaluation system. The second was a web-based service providing global 10m wind data from multiple sources to wind industry subscription customers. The third product addressed the needs of our utility clients looking at climate change effects on electricity distribution. For this we collaborated on the Santa Ana Wildfire Threat Index (SAWTi), which was released publicly last quarter. Finally to promote these products and educate potential users we released “Gust or Bust”, a graphic-novel styled marketing publication.

17 WIND ENERGY↗
NASA NTRS1994

The value of NDBC observations during March 1993's 'Storm of the Century'

National Data Buoy Center (NDBC) observations from the western Gulf of Mexico Provided several early indications of more rapid cyclogenesis on 12 March 1993 than was forecast by numerical weather prediction (NWP) models. Observations demostrated a closed circulation with gale-force winds shortly after the storm entered the Gulf of Mexico. Pressure measurements at two buoys off the Texas coast were 4-6 hPa lower than the 12-h NWP forecasts, a significant forecast error. Observations from NDBC's moored buoys and Coastal-Marine Automated Network stations revealed that the developing storm was significantly deeper than was indicated on the National Meteorological Center's automated surface analyses. Ocean wave observations reveal some of the steepest waves NDBC has ever measured, indicating phenomenonal wave growth and a high potential for damage to vessels and structures. A warm eddy caused sea surface temperatures (SST) to be several degrees above normal under the track of the storm, creating a strong SST gradient to the north. This provided ample energy and strengthened the baroclinity. NDBC observations showed the eddy to be somewhat larger and warmer than indicated by the most recent National Hurricane Center analysis. This event demonstrates the tremendous value of NDBC marine observations for accurately detecting the occurrence and strength of coastal cyclogenesis events.

Gilhousen, David B.↗
NASA NTRS2011

Geoeffectiveness (D (sub st) and K (sub p)) of Interplanetary Coronal Mass Ejections During 1995-2009 and Implications for Storm Forecasting

We summarize the geoeffectiveness (based on the Dst and Kp indices) of the more than 300 interplanetary coronal mass ejections (ICMEs) that passed the Earth during 1996-2009, encompassing solar cycle 23. We subsequently estimate the probability that an ICME will generate geomagnetic activity that exceeds certain thresholds of Dst or Kp, including the NOAA "G" storm scale, based on maximum values of the southward magnetic field component (Bs), the solar wind speed (V), and the y component (Ey) of the solar wind convective electric field E = -V x B, in the ICME or sheath ahead of the ICME. Consistent with previous studies, the geoeffectiveness of an ICME is correlated with Bs or Ey approx.= VBs in the ICME or sheath, indicating that observations from a solar wind monitor upstream of the Earth are likely to provide the most reliable forecasts of the activity associated with an approaching ICME. There is also a general increase in geoeffectiveness with ICME speed, though the overall event-to-event correlation is weaker than for Bs and Ey. Nevertheless, using these results, we suggest that the speed of an ICME approaching the Earth inferred, for example, from routine remote sensing by coronagraphs on spacecraft well separated from the Earth or by all-sky imagers, could be used to estimate the likely geoeffectiveness of the ICME (our "comprehensive" ICME database provides a proxy for ICMEs identified in this way) with a longer lead time than may be possible using an upstream monitor

Richardson, I. G.↗