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At least 739 records · Page 41

Evaluating commercial feasibility of a new tall wind tower design concept using a stochastic levelized cost of energy model

Wind power generation has seen a dramatic increase in the 21st century and the Department of Energy (DOE) envisions that wind energy will become a much larger part of overall power generation in the U.S. by 2050. Wind turbines have continued to grow in size during the last few decades with towers commonly built at a height of 80 m for typical utility-scale turbines in the Unites States, and this is accompanied by certain transportation and logistics challenges. The newly proposed tall tower technology has been designed to be cost-effective in assembling towers as high as 140 m from precast concrete module components that are capable of transport on the U.S. road system. This paper presents an alternative wind tower design with potential for reducing the overall levelized cost of energy (LCOE); it evaluates a hexagonal precast concrete wind tower solution that facilitates use of a taller wind turbine generator for harvesting stronger, steadier, and more frequent wind resources to increase wind energy production and lower the overall LCOE. An integrated team of industry experts was consulted to support development of a stochastic life cycle cost model using a parametric estimate of the cost and fabrication and assembly schedules of this new wind tower design concept as well as forecasting the projected revenue to be created by the new technology. The study concludes that this new design concept is a commercially viable solution, with an estimated LCOE savings ranging from 2% to 4% compared with the typical 80 m turbine deployed in the United States, and it also provides wind power potential to previously untapped regions in the country. This article helps to inform energy developers, manufacturers, and policy makers, both regionally and nationally, of a possible economically feasible wind tower design solution.

17 WIND ENERGY↗

Optimal Initial Perturbations for Ensemble Prediction of the Madden-Julian Oscillation during Boreal Winter

An initialization strategy, tailored to the prediction of the Madden-Julian oscillation (MJO), is evaluated using the Goddard Earth Observing System Model, version 5 (GEOS-5), coupled general circulation model (CGCM). The approach is based on the empirical singular vectors (ESVs) of a reduced-space statistically determined linear approximation of the full nonlinear CGCM. The initial ESV, extracted using 10 years (1990-99) of boreal winter hindcast data, has zonal wind anomalies over the western Indian Ocean, while the final ESV (at a forecast lead time of 10 days) reflects a propagation of the zonal wind anomalies to the east over the Maritime Continent an evolution that is characteristic of the MJO. A new set of ensemble hindcasts are produced for the boreal winter season from 1990 to 1999 in which the leading ESV provides the initial perturbations. The results are compared with those from a set of control hindcasts generated using random perturbations. It is shown that the ESV-based predictions have a systematically higher bivariate correlation skill in predicting the MJO compared to those using the random perturbations. Furthermore, the improvement in the skill depends on the phase of the MJO. The ESV is particularly effective in increasing the forecast skill during those phases of the MJO in which the control has low skill (with correlations increasing by as much as 0.2 at 20 25-day lead times), as well as during those times in which the MJO is weak.

Ham, Yoo-Geun↗

Potential advantages of the spaced antenna method for operational wind profiling, part 3.1B

The problem of very short-range forecasting is twofold. It is necessary to understand the processes that are being forecasted, and data appropriate to the scale of interest has to be generated. Coherent VHF and UHF radars are being used for operational wind profiling and are providing part of the solution to the data-acquisition problem. The Profiler system operated by the Wave Propagation Laboratory at NOAA has already shown great promise. As a result, plans are being considred for expanding the network of radars to cover a larger area of the country. The Profiler uses what is commonly referred to as the Doppler method for measuring winds. Two beams are pointed off-vertical, and the Doppler shift of the echo determines the line-of-sight velocity. The velocity components along the beams are then translated to horizontal wind components. A number of possible advantages of the spaced antennas (SA) method for operational wind profiling are discussed.

Rottger, J.↗

Evaluation of Vertically Resolved Water Winds from AIRS using Hurricane Katrina

The knowledge of wind velocity as a function of altitude is key to weather forecast improvements. The ability of hyperspectral sounders in principle to measure vertically resolved water winds, which has long been recognized, has been tested with Atmospheric Infrared Sounder (AIRS) data. AIRS retrievals of total column water above 300 mb have been correlated with the radiosonde upper-tropospheric wind velocity and moisture data. The excellent correlation is illustrated with results obtained from hurricane Katrina and from the western United States. AIRS is a hyperspectral infrared sounder in low Earth orbit. It was launched in May 2002. We illustrate the use of AIRS data for the measurement of upper tropospheric water by using the 2387/cm CO2 R-branch channel and the 1551/cm water vapor channel. The 2387/cm channel measures the temperature at 300 mb totally independent of water vapor. The weighting function of the 1551/cm channel peaks at 300 mb only under moist conditions; the peak shifts downward (higher temperature) for less water and upward (lower temperature) for more water. The difference between the brightness temperatures bt2387 and bt1551 cancels the local several degree weather related variability of the temperature and measures the component due to the water vapor at 300 mb.

Atmospheric Infrared Sounder (AIRS)↗

Understanding Diurnal Patterns in Wind Power Generation Data

Integrating wind energy on the power grid is a challenging task given the intermittent nature of these resources. When the percentage of wind energy was small, control room operators did not have a major problem in scheduling wind resources. However, as this percentage has increased, it is clear that the operators will need more accurate forecasts, as well as any additional information they can exploit, to make better-informed scheduling decisions. In this paper, we investigate diurnal patterns observed in wind-power time series data. Using actual wind generation data from two sites, we try to identify these patterns, understand them better, and determine if it is possible to use weather conditions in the vicinity of the wind farms to predict the pattern for a day. Such analysis could provide insights useful in scheduling wind resources on days with inaccurate forecasts.

17 WIND ENERGY↗

Impact Assessment of All-Sky TROPICS Microwave Observations on the NASA GEOS Analyses and Forecasts and Progress to Use the Data in the JEDI-GEOS Analysis System

The NASA Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats (TROPICS) mission is a constellation of small satellites carrying state-of-art microwave temperature and humidity sounders with 12 channels between 91 GHz and 205 GHz frequency. Including TROPICS-pathfinder, launched on 30 June 2021, five TROPICS CubeSats operate and provide temperature and humidity data to NWP and atmospheric retrieval communities. This study is dedicated to evaluating the impact of the TROPICS satellite constellation microwave observations in numerical weather prediction (NWP) using the NASA Goddard Earth Observing System (GEOS). The TROPICS-01 (TROPICS-Pathfinder), TROPICS-03, TROPICS-05, and TROPICS-06 data in all-sky conditions over the ocean during the period of 25 July 2023 and 6 September 2023 are used for assessing forecast impacts on global NWP analysis and five-day forecasts. A series of experiments are carried out to measure the benefits of assimilating observations from only temperature sounders, water vapor sounders, and both sounders. Statistical analysis of the Observing System Experiments (OSEs) results has shown incremental improvements in global model forecast skills for critical geophysical parameters, including temperature, winds, and geopotential heights. The results demonstrate the potential of the TROPICS-like data to positively impact NWP by adding new information to the current observation and forecast system. In another set of experiments, the TROPICS-03, TROPICS-05, and TROPICS-06 data sets are added to the TROPICS-01 one by one to evaluate the impacts of increasing the revisit rate of TROPICS satellite measurements on NWP analysis for a tropical cyclone’s dynamical and microphysical structures. This study offers important insights into the capabilities of a new generation of small satellite microwave radiometers based on emerging technologies, including their unique measurements at 118 GHz and 205 GHz that are not available in traditional operational microwave sounders. Finally, the efforts to implement these new developments for TROPICS in the JEDI-GEOS atmospheric data assimilation system are in progress, and preliminary results from cycled JEDI-GEOS data assimilation experiments are presented.

Min-Jeong Kim↗

A hybrid data-driven and model-based approach for computationally efficient stochastic unit commitment and economic dispatch under wind and solar uncertainty

Stochastic unit commitment (UC) and economic dispatch (ED) are imperative in dealing with uncertainty in renewable forecast for power system operation and planning such that the overall expected production cost is minimized over the planning horizon. However, accurate calculation of the expected production cost requires assessment of a very large number of different scenarios of uncertain renewable resources, such as solar and wind, which is practically infeasible to simulate in real time. This article proposes a hybrid datadriven and physics-based model-predictive paradigm to efficiently solve for stochastic unit commitment and economic dispatch considering uncertainty in wind and solar power forecasts. Here, the novelty of the approach lies in decoupling the production cost estimation from the unit commitment and economic dispatch optimization problems under uncertainty without compromising on the fidelity of the solutions. A data-driven machine learning model is first developed to predict the mean optimal production cost. A physics-based inverse problem is then solved to get the stochastic UC and ED profiles from the expected cost. The presented approach considers, for the first time, solar uncertainty in UC/ED determination and enables efficient and accurate propagation of wind and solar uncertainty to estimate the statistics of the production cost. The effectiveness of the developed approach is demonstrated systematically on a stylized RTS-GMLC single-node system. The overall framework predicts the expected cost 62.5% more accurately than the existing state-of-the-art, on unforeseen days during the entire year, and yields, for the first time, the associated physically consistent UC and ED profiles. The solutions are also shown to be flexible in providing adequate daily reserves to address any statistical deviations from probabilistic power forecasts. The computational time associated with the presented method is only about 10 s compared to over 24 h needed for a conventional stochastic UC/ED determination under uncertainty on an Intel Core i9 processor with 32 GB of RAM.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Impact of Satellite Microwave Radiance Data Assimilation on GEOS Atmospheric Analysis and Forecasts in Tropics

The NASA Global Modeling and Assimilation Office (GMAO) has developed a system to assimilate all-sky microwave radiance data in the Goddard Earth Observing System (GEOS). The system provides additional constraints on the analysis process near the storm regions and adjusts the geophysical parameters such as precipitation, cloud, moisture, surface pressure, and wind by combining information from microwave radiance measurements and model forecasts in an optimal manner. The system proved that assimilating the all-sky microwave radiance data improve the GEOS atmospheric analyses and forecasts. This all-sky data framework has been included in the GEOS Forward Processing (FP) system and currently assimilating all-sky GMI data in real-time for GEOS global analysis and forecast production at the GMAO. This presentation describes the methodologies to assimilate cloud- and precipitation-affected microwave radiances in GEOS data assimilation system based on hybrid four-dimensional ensemble-variational (4D-EnVar) configuration. In the current operational GEOS-FP system, the addition of all-sky GMI radiances has the largest impact in the Tropics. Specific humidity is significantly improved in the short term (0-72 hours) forecasts. Similar improvements are seen in the Tropical and lower tropospheric temperature and winds. More detailed results on all-sky microwave radiance data impact on GEOS analysis and forecasts are discussed in this presentation.

Kim, Min-Jeong↗

An Analysis of Peak Wind Speed Data from Collocated Mechanical and Ultrasonic Anemometers

This study focuses on a comparison of peak wind speeds reported by mechanical and ultrasonic anemometers at Cape Canaveral Air Force Station and Kennedy Space Center (CCAFS/KSC) on the east central coast of Florida and Vandenberg Air Force Base (VAFB) on the central coast of California. The legacy mechanical wind instruments on CCAFS/KSC and VAFB weather towers are being changed from propeller-and-vane (CCAFS/KSC) and cup-and-vane (VAFB) sensors to ultrasonic sensors under the Range Standardization and Automation (RSA) program. The wind tower networks on KSC/CCAFS and VAFB have 41 and 27 towers, respectively. Launch Weather Officers, forecasters, and Range Safety analysts at both locations need to understand the performance of the new wind sensors for a myriad of reasons that include weather warnings, watches, advisories, special ground processing operations, launch pad exposure forecasts, user Launch Commit Criteria (LCC) forecasts and evaluations, and toxic dispersion support. The Legacy sensors measure wind speed and direction mechanically. The ultrasonic RSA sensors have no moving parts. Ultrasonic sensors were originally developed to measure very light winds (Lewis and Dover 2004). The technology has evolved and now ultrasonic sensors provide reliable wind data over a broad range of wind speeds. However, because ultrasonic sensors respond more quickly than mechanical sensors to rapid fluctuations in speed, characteristic of gusty wind conditions, comparisons of data from the two sensor types have shown differences in the statistics of peak wind speeds (Lewis and Dover 2004). The 45th Weather Squadron (45 WS) and the 30 WS requested the Applied Meteorology Unit (AMU) to compare data from RSA and Legacy sensors to determine if there are significant differences in peak wind speed information from the two systems.

Short, David A.↗

Analysis of ocean surface wind fields using SEASAT-A scatterometer data

In addition to the SEASAT forecast impact studies previously conducted with the GLA model, a study was also made of the global analyses of surface wind stress, wind stress curl, and surface sensible and latent heat fluxes, which are generated as a by-product of the assimilation process. Both instantaneous analyses of these quantities and 15-day averages of each of these fields were found to be in good qualitative agreement with published fields.

Kalnay, E.↗

Performance of a Local Mesoscale Model with Data Denial

Forecasters at the 45th Weather Squadron (45 WS) use observations from the Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) wind tower network and daily rawinsonde observations (RAOB) to issue and verify wind advisories, watches, and warnings for operations. They are also used by the Spaceflight Meteorology Group and Melbourne, Florida National Weather Service to initialize locally run mesoscale models. Due to impending budget cuts, some or all of the mainland wind towers and RAOBs may be eliminated, The loss of these data may significantly impact the forecast capability of the 45 WS and SMG. The Applied Meteorology Unit (AMU) was tasked to conduct an objective independent modeling study to determine how important these observations are to the accuracy of the model output used by the forecasters as input to their forecasts. To accomplish this, the AMU performed a sensitivity study using the Weather Research and Forecasting (WRF) model run with and without KSC/CCAFS wind tower and CCAFS RAOB observations and assessed the accuracy of model forecasts by comparing them to the observations.

Watson, Leela↗

Roles of Wind Shear at Different Vertical Levels, Part I: Cloud System Organization and Properties

Understanding of critical processes that contribute to the organization of mesoscale convective systems is important for accurate weather forecast and climate prediction. In this study, we investigate the effects of wind shear at different vertical levels on the organization and properties of cloud systems using the Weather Research & Forecasting (WRF) model with a spectral-bin microphysical scheme. The sensitivity experiments are performed by increasing wind shear at the lower (0-5 km), middle (5-10 km), upper (> 10 km) and the entire troposphere, respectively, based on a control run for a mesoscale convective system (MCS) with weak wind shear. We find that increasing wind shear at the both lower and middle vertical levels reduces the domain-accumulated precipitation and the occurrence of heavy rain, while increasing wind shear at the upper levels changes little on precipitation. Although increasing wind shear at the lower-levels is favorable for a more organized quasi-line system which leads to enlarged updraft core area, and enhanced updraft velocities and vertical mass fluxes, the precipitation is still reduced by 18.6% compared with the control run due to stronger rain evaporation induced by the low-level wind shear. Strong wind shear in the middle levels only produces a strong super-cell over a narrow area, leading to 67.3% reduction of precipitation over the domain. By increasing wind shear at the upper levels only, the organization of the convection is not changed much, but the increased cloudiness at the upper-levels leads to stronger surface cooling and then stabilizes the atmosphere and weakens the convection. When strong wind shear exists over the entire vertical profile, a deep dry layer (2-9 km) is produced and convection is severely suppressed. There are fewer very-high (cloud top height (CTH) > 15 km) and very-deep (cloud thickness > 15 km) clouds, and the precipitation is only about 11.8% of the control run. The changes in cloud microphysical properties further explain the reduction of surface rain by strong wind shear especially at the lower- and middle-levels. The insights obtained from this study help us better understand the cloud system organization and provide foundation for better parameterizing organized MCS.

cloud system organization↗

Effects of land-based wind turbine upsizing on community sound levels and power and energy density

Multiple technological, social, and market factors of wind power are evolving rapidly. Most notably, significant wind turbine scaling is occurring and is forecasted to continue. While the larger turbines expected to be deployed in the future are more powerful and efficient, they are also expected to operate at higher sound levels and require larger setbacks than those installed in the last decade. These sometimes-competing deployment trends and impacts cannot be understood via simple extrapolations of past trends. This study analyzes the effect of these future larger turbines on wind turbine micro-siting, project-level power and energy density, and community noise impacts. Due to their taller heights, larger rotors, and higher sound power levels, future wind turbines will require larger setbacks from homes and greater inter-turbine spacing, resulting in fewer turbines deployed for a given land area. This research finds these changes more than offset the effect of the higher turbine sound emissions, significantly decreasing the average sound levels that wind plant hosting communities experience. Yet, simultaneously, plant layouts using future turbine designs also result in projects with higher installed capacities and annual energy output for a given land area. These increases will likely lead to increased tax benefits and local income in the community. The deployment of fewer turbines on a smaller number of parcels could have implications on siting flexibility and landowner payments.

17 WIND ENERGY↗

Can mesoscale models capture the effect from cluster wakes offshore?

Long wakes from offshore wind turbine clusters can extend tens of kilometers downstream, affecting the wind resource of a large area. Given the ability of mesoscale numerical weather prediction models to capture important atmospheric phenomena and mechanisms relevant to wake evolution, they are often used to simulate wakes behind large wind turbine clusters and their impact over a wider region. Yet, uncertainty persists regarding the accuracy of representing cluster wakes via mesoscale models and their wind turbine parameterizations. Here, we evaluate the accuracy of the Fitch wind farm parameterization in the Weather Research and Forecasting model in capturing cluster-wake effects using two different options to represent turbulent mixing in the planetary boundary layer. To this end, we compare operational data from an offshore wind farm in the North Sea that is fully or partially waked by an upstream array against high-resolution mesoscale simulations. In general, we find that mesoscale models accurately represent the effect of cluster wakes on front-row turbines of a downstream wind farm. However, the same models may not accurately capture cluster-wake effects on an entire downstream wind farm, due to misrepresenting internal-wake effects.

17 WIND ENERGY↗

An OSSE on Mesoscale Model Assimilation of Simulated HIRAD-Observed Hurricane Surface Winds

The hazards of landfalling hurricanes are well known, but progress on improving the intensity forecasts of these deadly storms at landfall has been slow. Many cite a lack of high-resolution data sets taken inside the core of a hurricane, and the lack of reliable measurements in extreme conditions near the surface of hurricanes, as possible reasons why even the most state-of-the-art forecasting models cannot seem to forecast intensity changes better. The Hurricane Imaging Radiometer (HIRAD) is a new airborne microwave remote sensor for observing hurricanes, and is operated and researched by NASA Marshall Space Flight Center in partnership with the NOAA Atlantic Oceanographic and Meteorological Laboratory/Hurricane Research Division, the University of Central Florida, the University of Michigan, and the University of Alabama in Huntsville. This instrument?s purpose is to study the wind field of a hurricane, specifically observing surface wind speeds and rain rates, in what has traditionally been the most difficult areas for other instruments to study; the high wind and heavy rain regions. Dr. T. N. Krishnamurti has studied various data assimilation techniques for hurricane and monsoon rain rates, and this study builds off of results obtained from utilizing his style of physical initializations of rainfall observations, but obtaining reliable observations in heavy rain regions has always presented trouble to our research of high-resolution rainfall forecasting. Reliable data from these regions at such a high resolution and wide swath as HIRAD provides is potentially very valuable to mesoscale forecasting of hurricane intensity. This study shows how the data assimilation technique of Ensemble Kalman Filtering (EnKF) in the Weather Research and Forecasting (WRF) model can be used to incorporate wind, and later rain rate, data into a mesoscale model forecast of hurricane intensity. The study makes use of an Observing System Simulation Experiment (OSSE) with a simulated HIRAD dataset sampled during a hurricane and uses EnKF to forecast the track and intensity prediction of the hurricane. Comparisons to truth and error metrics are used to assess the model?s forecast performance.

Albers, Cerese↗

A Large-Eddy Simulation Study in WRF on Wind over Broadband Waves of Different Directions and Spreading Widths

We use the Weather Research and Forecasting (WRF) Model coupled with moving waves to conduct large-eddy simulations (LESs) of wind over broadband waves with different propagating directions and spreading widths. Our results show that wind-opposing waves can double the form drag, and the wave propagating direction affects the mean wind velocity, velocity variances, and pressure stress. On the other hand, waves with wider spread tend to reduce the form drag in the streamwise direction. Results further indicate that the wave direction can impact the bulk drag coefficient by as much as 25%, while the wave directional spreading width can change it by 5%. Based on our wave-phase-resolved simulations, we demonstrate that the parameterization of sea surface roughness is significantly influenced by the direction of wave propagation relative to the wind, a factor that the commonly used Charnock relation does not account for.

54 ENVIRONMENTAL SCIENCES↗

Identifying Stratospheric Air Intrusions and Associated Hurricane-Force Wind Events over the North Pacific Ocean

Motivation: Ocean data is sparse: reliance on satellite imagery for marine forecasting; Ocean Prediction Center (OPC) –“mariner’s weather lifeline”. Responsible for: Pacific, Atlantic, Pacific Alaska surface analyses –24, 48, 96 hrs.; Wind & wave analyses –24, 48, 96 hrs.; Issue warnings, make decisions, Geostationary Operational Environmental Satellite –R Series (now GOES-16), Compared to the old GOES: 3 times spectral resolution, 4 times spatial resolution, 5 times faster coverage; Comparable to Japanese Meteorological Agency’s Himawari-8, used a lot throughout this research. Research Question: How can integrating satellite data imagery and derived products help forecasters improve prognosis of rapid cyclogenesis and hurricane-force wind events? Phase I –Identifying stratospheric air intrusions: Water Vapor –6.2, 6.9, 7.3 micron channels; Airmass RGB Product; AIRS, IASI, NUCAPS total column ozone and ozone anomaly; ASCAT (A/B) and AMSR-2 wind data.

Ozone↗