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This presentation for the Fourth Wind Energy Systems Engineering Workshop covers some of the uncertainties that still impact turbulent wind operation and how these affect design and structural reliability; identifies key sources and prioritization for R and D; and summarizes an analysis of current procedures, industry best practice, standards, and expert opinions.
This presentation describes the Energy Department's wind energy Regional Resource Centers (RRCs) initiative and provides examples of RRC accomplishments.
Computational designs were performed for three different low aspect ratio wing planforms fitted with nonplanar winglets; one of the three configurations was selected to be constructed as a wind tunnel model for testing in the NASA LaRC 8-foot transonic pressure tunnel. A design point of M = 0.8, C(sub L) is approximate or = to 0.3 was selected, for wings of aspect ratio equal to 2.2, and leading edge sweep angles of 45 deg and 50 deg. Winglet length is 15 percent of the wing semispan, with a cant angle of 15 deg, and a leading edge sweep of 50 deg. Winglet total area equals 2.25 percent of the wing reference area. The design process and the predicted transonic performance are summarized for each configuration. In addition, a companion low-speed design study was conducted, using one of the transonic design wing-winglet planforms but with different camber and thickness distributions. A low-speed wind tunnel model was constructed to match this low-speed design geometry, and force coefficient data were obtained for the model at speeds of 100 to 150 ft/sec. Measured drag coefficient reductions were of the same order of magnitude as those predicted by numerical subsonic performance predictions.
Monte Carlo models of the distribution of atomic hydrogen in the exosphere of Venus were computed which simulate the effects of thermospheric winds and the production of a 'hot' hydrogen component by charge exchange of H(+) and H and Q in the exosphere, as well as classic exospheric processes. A thermosphere wind system that is approximated by a retrograde rotating component with equatorial speed of 100 m/sec superimposed on a diurnal solar tide with cross-terminator day-to-night winds of 200 m/sec is shown to be compatible with the thermospheric hydrogen distribution deduced from Pioneer Venus orbiter measurements.
Modern wind plants are increasingly tasked with multiple performance objectives. In addition to designing plants that maximize power output and minimize the levelized cost of energy (LCOE), the design and operation of wind plants is increasingly influenced by challenges regarding grid integration of variable generation renewables. This places a growing emphasis on making wind plants more controllable and predictable. WindSE is a Reynolds-averaged Navier-Stokes (RANS) model designed around analytical gradient and adjoint methods, with the ability to capture terrain-induced effects, as shown in Figure 1. The recent addition of an unsteady solver with an actuator line method (ALM) and ongoing work to enable massively parallel optimizations gives it a unique niche to explore coupled plant-level controls and design problems. This code is an open source python package built on the FEniCS framework that utilizes fast, parallel PETSc solvers to model fluid flow throughout wind-farm scale domains. Two recent studies performed using WindSE demonstrate the capability to optimize under a wide variety of flow conditions and objective functions. In the first, we present an optimization focused on modifying the layout of a wind farm with a fixed number of turbines for maximum total power output [1]. This study highlights the ability to quickly perform simulations using the steady Navier-Stokes solver combined with rotors represented as actuator disks while also stressing the importance of capturing terrain-induced effects. Gradient-based optimization using the RANS equations is viable due to the inclusion of efficiently computed adjoint derivatives. We interpret the physical results of the optimal layout and also discuss the computational cost of scaling to larger problems. In the second study, we present the capabilities of the unsteady Navier-Stokes solver, where rotor-blade profiles represented by actuator lines are optimized to enhance wake steering effects and overall power production [2]. We quantify the wind plant performance gains obtained from this type of simultaneous control co-design optimization as compared to optimizing the blade design and yaw independently. Figure 2 shows the differences between a baseline two-turbine system and an optimized system where we fine-tune the blade chord profile. Results and challenges from each study are quickly summarized and used to motivate the current development efforts within WindSE. Current and future work is focused on enabling higher-resolution studies with more degrees of freedom through parallelization of both the simulation and optimization algorithms. We present benchmarking results to show that WindSE performs well in both weak- and strong-scaling tests and further demonstrate that the optimizer obtains the same convergence rates in both shared- and distributed-memory environments. Using larger wind farms, we can study deep-array effects within an optimization context, allowing the use of objective functions that have been previously unstudied. As an example, we present ongoing work on a blockage metric which characterizes the loss of available kinetic energy due to wake effects from multiple upstream turbines.
There are many differences and also remarkable similarities between the ion chemistry and physics of planetary ionospheres and the ion chemistry and physics of astronomical environments beyond the solar system. In the early Universe, an expanded cooling gas of hydrogen and helium was embedded in the cosmic background radiation field and ionized by it. As the Universe cooled by adiabatic expansion, recombination occurred and molecular formation was driven by catalytic reactions involving the relict electrons and protons. Similar chemical processes are effective in the ionized zones of gaseous and planetary nebulae and in stellar winds where the ionization is due to radiation from the central stars, in the envelopes of supernovae where the ionization is initiated by the deposition of gamma-rays, in dissociative shocks where the ionization arises from electron impacts in a hot gas and in quasar broad-line region clouds where the quasar is responsible for the ionization. At high altitudes in the atmospheres of the Jovian planets, the main constituents are hydrogen and helium and the ion chemistry and physics is determined by the same processes, the source of the ionization being solar ultraviolet radiation and cosmic rays. After the collapse of the first distinct astronomical entities to emerge from the uniform flow, heavy elements were created by nuclear burning in the cores of the collapsed objects and distributed throughout the Universe by winds and explosions. The chemistry and physics became more complicated. Over 90 distinct molecular species have been identified in interstellar clouds where they are ionized globally by cosmic ray impacts and locally by radiation and shocks associated with star formation and evolution. Complex molecules have also been found in circumstellar shells of evolved stars. At intermediate and low altitudes in the Jovian atmospheres, the ion chemistry is complicated by the increasing abundance of heavy elements such as carbon, and an extensive array of complex molecules has been predicted. Reactions involving heavy elements dominate the structure of the ionspheres of the terrestrial planets and the satellites Titan and Triton.
The effects of planetary waves on atmospheric nitric oxide (NO) concentration were investigated using a time-dependent numerical model. The model is used to calculate planetary wave and zonal mean winds, which in turn are used to calculate mean and perturbation NO distribution. The time-dependent model is used to determine equilibrium NO distributions resulting from time-dependent lower boundary planetary wave forcings. The factors which contribute to the zonal mean NO concentration are examined. NO chemistry is modelled using a simplified source sink approach. Changes in the initial NO distribution which result from the addition of planetary-wave winds are described. Planetary waves are found to induce a wavelike structure in the NO distribution which resembles that derived from observational data. These waves affect the NO concentration through wave-induced changes in the mean meridional circulation and through the NO perturbation induuced by the wave winds themselves.
A study of the Antarctic ozone hole was made with a 3-D chemical transport model using linearized photochemistry for ozone based on observed distribution. The tracer model uses the winds and convection from the GISS general circulation model (8 deg x 10 deg x 23 layers). A 3-year control run of the ozone distribution is compared with the observed climatology. In two experiments, a hypothetical Antarctic ozone hole is induced on October 1 and on November 1; the tracer model is integrated for 1 year with the standard linearized chemistry. The initial depletion, 90 percent of the O sub 3 poleward of 70 S between 25 and 180 mbar, amounts to about 5 percent of the total O sub 3 in the Southerm Hemisphere. As the vortex breaks down and the hole is dispersed, significant depletions to column ozone, of order 10 D.U., occur as far north as 36 S during Austral summer. One year later, about 25 percent of the original depletion remains, mostly below 100 mbar and poleward of 30 S. Details of the calculations are shown, along with a budget analysis showing the fraction of the hole filled in by photochemistry versus that transported into the troposhere.
Abstract A near‐global aquaplanet cloud‐resolving model (NGAqua) with fixed meridionally varying sea‐surface temperature (SST) is used to investigate cloud feedbacks due to three climate perturbations: a uniform 4 K SST increase, a quadrupled‐CO 2 concentration, and both combined. NGAqua has a horizontal resolution of 4 km with no cumulus parameterization. Its domain is a zonally periodic 20,480 km‐long tropical channel, spanning 46°S–N. It produces plausible mean distributions of clouds, rainfall, and winds. After spin‐up, 80 days are analyzed for the control and increased‐SST simulations, and 40 days for those with quadrupled CO 2 . The Intertropical Convergence Zone width and tropical cloud cover are not strongly affected by SST warming or CO 2 increase, except for the expected upward shift in high clouds with warming, but both perturbations weaken the Hadley circulation. Increased SST induces a statistically significant increase in subtropical low cloud fraction and in‐cloud liquid water content but decreases midlatitude cloud, yielding slightly positive domain‐mean shortwave cloud feedbacks. CO 2 quadrupling causes a slight shallowing and a statistically insignificant reduction of subtropical low cloud fraction. Warming‐induced low cloud changes are strongly correlated with changes in estimated inversion strength, which increases modestly in the subtropics but decreases in the midlatitudes. Enhanced clear‐sky boundary layer radiative cooling in the warmer climate accompanies the robust subtropical low cloud increase. The probability distribution of column relative humidity across the tropics and subtropics is compared between the control and increased‐SST simulations. It shows no evidence of bimodality or increased convective aggregation in a warmer climate.
Sea wave behavior calculations require the precalculation of wave elements as well as consideration of the spectral functions of ocean wave formation. The spectrum of the random wave process is largely determined by the distribution of energy in the actual wind waves observed on the surface of the sea as expressed in statistical and spectral characteristics of the sea swell.
Wind turbine extreme load estimation is especially difficult because turbulent inflow drives nonlinear turbine physics and control strategies; thus there can be huge differences in turbine response to essentially equivalent environmental conditions. The two main current approaches, extrapolation and Monte Carlo sampling, are both unsatisfying: extrapolation-based methods are dangerous because by definition they make predictions outside the range of available data, but Monte Carlo methods converge too slowly to routinely reach the desired 50-year return period estimates. Thus a search for a better method is warranted. We introduce an adaptive stratified importance sampling approach that allows for treating the choice of environmental conditions at which to run simulations as a stochastic optimization problem that minimizes the variance of unbiased estimates of extreme loads. Furthermore, the framework, built on the traditional bin-based approach used in extrapolation methods, provides a close connection between sampling and extrapolation, and thus allows the solution of the stochastic optimization (i.e., the optimal distribution of simulations in different wind speed bins) to guide and recalibrate the extrapolation. Results show that indeed this is a promising approach, as the variance of both the Monte Carlo and extrapolation estimates are reduced quickly by the adaptive procedure. We conclude, however, that due to the extreme response variability in turbine loads to the same environmental conditions, our method and any similar method quickly reaches its fundamental limits, and that therefore our efforts going forward are best spent elucidating the underlying causes of the response variability.
The lunar exosphere is generated by several processes each of which generates neutral distributions with different spatial and temporal variability. Solar wind sputtering of the lunar surface is a major process for many regolith-derived species and typically generates neutral distributions with a cosine dependence on solar zenith angle. Complicating this picture are remanent crustal magnetic anomalies on the lunar surface, which decelerate and partially reflect the solar wind before it strikes the surface. We use Kaguya maps of solar wind reflection efficiencies, Lunar Prospector maps of crustal field strengths, and published neutral sputtering yields to calculate anisotropic solar wind sputtering maps. We feed these maps to a Monte Carlo neutral exospheric model to explore three-dimensional exospheric anisotropies and find that significant anisotropies should be present in the neutral exosphere depending on selenographic location and solar wind conditions. Better understanding of solar wind/crustal anomaly interactions could potentially improve our results.
This paper describes an estimation algorithm for velocity and power output signals in a wind farm under changing wind direction. A graph-theoretic definition describes the wind farm as a collection of nodes (turbines) and time-varying weighted edges (inter-turbine wake propagation) that change as a function of incoming wind direction. The velocity at each turbine is determined through a discrete input-output model. Changes in wind direction serve as the input and the output is defined in terms of a time-varying weighted adjacency matrix that depends on the time-delay of information propagation between turbines. These delays, which are defined in terms of the advection speed of the wind and the distance between the turbines, capture the delayed effect of wind direction changes on the inter-connectivity of the graph as the wind conditions at the farm inlet propagate through the turbine array. An event-based update framework is employed to capture time-dependent topology changes due to shifts in wind direction. Simulation results for dynamically changing wind inlet directions to a circular wind farm are compared to predictions from both the static and dynamic versions of the FLOw Redirection and Induction in Steady State (FLORIS) model. The approach is shown to enable real-time tracking of dynamic changes to wind farm power output within a framework that can be easily integrated into real-time, horizon-based, control strategies that typically do not account for wind direction changes.
Residential and commercial buildings have huge potential to contribute value to improve grid resilience by participating grid services. To reveal the significant value, it is critical to estimate the grid service capability from these buildings. Unlike the large-scale distributed energy resources such as wind and solar farms, those buildings need to participate grid services in aggregation, not by individual. Therefore, it is important to appropriately group buildings for aggregation. The load profiles in the same group will have similar characteristics at the same time step, so grid operators can send the grid service signal to the customer group with a higher chance to respond at that time step. In this paper, we develop a load profile clustering method to classify the building-level load profiles for grid service capability estimation and the results have proved the effectiveness of this method.
In the present consideration of the probability of interstellar wind H and He atoms' survival of ionization by solar wind electrons, a dual temperature electron distribution is for the first time used to model the effects of 'core' (10 eV) and 'halo' (60 eV) solar electrons on survival probabilities. The interstellar wind has a higher probability of surviving halo rather than core electron ionization only at heliocentric distances smaller than 0.5 AU. For larger distances, halo and core survival probabilities are similar, and similarly insensitive to changes in (1) interstellar wind velocity at infinity, (2) the solar ratio of radiation to gravitational force, and (3) solar electron temperatures. At distances smaller than 0.5 AU, however, sensitivity significantly increases.
This work combined coronagraphic visible light (VL) and UV data to provide with an unprecedented view of the inner corona where the nascent solar wind is accelerated. The UV (H i Lyα) and VL (polarized brightness) images (reconstructed with SOHO/UVCS, LASCO, and Mauna Loa data) have been analyzed with the Doppler dimming technique to provide for the first time daily 2D images of the radial wind speed between 1 and 6 R {sub ⊙} over 1 month of observations. Results show that both polar and equatorial regions are characterized at the base of the corona by plasma outflows at speeds >100 km s{sup −1}. The plasma is then decelerated within ∼1.5 R {sub ⊙} at the poles and ∼2.0 R {sub ⊙} at the equator, where local minima of the expansion speeds are reached, and gently reaccelerated higher up, reaching speeds typical of fast and slow wind components. The mass flux is highly variable with latitude and time at the equator and more uniform and stable over the poles. The polar flow is asymmetric, with speeds above the south pole lower than those above the north pole. A correlation (anticorrelation) between the wind speed and its density is found below (above) ∼1.8 R {sub ⊙}. The 2D distribution of forces responsible for deceleration and reacceleration of solar wind is provided and interpreted in terms of Alfvén waves. These results provide a possible connection between small-scale outflows reported with other instruments at the base of the corona and bulk wind flows measured higher up.
A generalized actuator line (GAL) wind turbine parameterization is implemented within the Weather Research and Forecasting model to enable high-fidelity large-eddy simulations of wind turbine interactions with boundary layer flows under realistic atmospheric forcing conditions. Numerical simulations using the GAL parameterization are evaluated against both an already implemented generalized actuator disk (GAD) wind turbine parameterization and two field campaigns that measured the inflow and near-wake regions of a single turbine. The representation of wake wind speed, variance, and vorticity distributions is examined by comparing fine-resolution GAL and GAD simulations and GAD simulations at both fine and coarse-resolutions. The higher-resolution simulations show slightly larger and more persistent velocity deficits in the wake and substantially increased variance and vorticity when compared to the coarse-resolution GAD. The GAL generates distinct tip and root vortices that maintain coherence as helical tubes for approximately one rotor diameter downstream. Coarse-resolution simulations using the GAD produce similar aggregated wake characteristics to both fine-scale GAD and GAL simulations at a fraction of the computational cost. Furthermore, the GAL parameterization provides the capability to resolve near wake physics, including vorticity shedding and wake expansion.
Residential and commercial buildings have huge potential to contribute value to improve grid resilience by participating grid services. To reveal the significant value, it is critical to estimate the grid service capability from these buildings. Unlike the large-scale distributed energy resources such as wind and solar farms, those buildings need to participate grid services in aggregation, not by individual. Therefore, it is important to appropriately group buildings for aggregation. In this paper, we develop a load profile clustering method to classify the building-level load profiles for grid service capability estimation. In our two-step clustering approach, we first calculate the total load consumption for each building, clustering the load profiles based on energy consumption level. Then, we further cluster the load profiles in each energy cluster based on the load shape. The parameter selection for each clustering step is discussed. The proposed method is applied on actual building-level load profiles, and the results have proved the effectiveness of this method.