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At least 163 records · Page 9

An overview of wind-energy-production prediction bias, losses, and uncertainties

Abstract. The financing of a wind farm directly relates to the preconstruction energy yield assessments which estimate the annual energy production for the farm. The accuracy and the precision of the preconstruction energy estimates can dictate the profitability of the wind project. Historically, the wind industry tended to overpredict the annual energy production of wind farms. Experts have been dedicated to eliminating such prediction errors in the past decade, and recently the reported average energy prediction bias is declining. Herein, we present a literature review of the energy yield assessment errors across the global wind energy industry. We identify a long-term trend of reduction in the overprediction bias, whereas the uncertainty associated with the prediction error is prominent. We also summarize the recent advancements of the wind resource assessment process that justify the bias reduction, including improvements in modeling and measurement techniques. Additionally, because the energy losses and uncertainties substantially influence the prediction error, we document and examine the estimated and observed loss and uncertainty values from the literature, according to the proposed framework in the International Electrotechnical Commission 61400-15 wind resource assessment standard. From our findings, we highlight opportunities for the industry to move forward, such as the validation and reduction of prediction uncertainty and the prevention of energy losses caused by wake effect and environmental events. Overall, this study provides a summary of how the wind energy industry has been quantifying and reducing prediction errors, energy losses, and production uncertainties. Finally, for this work to be as reproducible as possible, we include all of the data used in the analysis in appendices to the article.

17 WIND ENERGY↗

Case study of a bore wind-ramp event from lidar measurements and HRRR simulations over ARM Southern Great Plains

The rapid change of wind speed and direction on 21 August 2017 is studied using Doppler lidar measurements at five sites of the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) facility in north-central Oklahoma. The Doppler lidar data were investigated along with meteorological variables such as temperature, humidity, and turbulence available from the large suite of instrumentation deployed at the SGP Central Facility (C1) during the Land-Atmosphere Feedback Experiment in August 2017. Lidar measurements at five sites, separated by 55-70 km, allowed us to document the development and evolution of the wind flow over the SGP area, examine synoptic conditions to understand the mechanism that leads to the ramp event, and estimate the ability of the High-Resolution Rapid Refresh model to reproduce this event. The flow feature in question is an atmospheric bore, a small-scale phenomenon that is challenging to represent in models, that was generated by a thunderstorm outflow northwest of the ARM SGP area. The small-scale nature of bores, its impact on power generation, and the modeling challenges associated with representing bores are discussed in this paper. In conclusion, the results also provide information about model errors between sites of different surface and vegetation types.

54 ENVIRONMENTAL SCIENCES↗

Study of Z boson plus jets events using variables sensitive to double-parton scattering in pp collisions at 13 TeV

Double-parton scattering is investigated using events with a Z boson and jets. The Z boson is reconstructed using only the dimuon channel. The measurements are performed with proton-proton collision data recorded by the CMS experiment at the LHC at s√ = 13 TeV, corresponding to an integrated luminosity of 35.9 fb -1 collected in the year 2016. Differential cross sections of Z+ ≥1 jet and Z+ ≥2 jets are measured with transverse momentum of the jets above 20 GeV and pseudorapidity |η| < 2.4. Several distributions with sensitivity to double-parton scattering effects are measured as functions of the angle and the transverse momentum imbalance between the Z boson and the jets. The measured distributions are compared with predictions from several event generators with different hadronization models and different parameter settings for multiparton interactions. The measured distributions show a dependence on the hadronization and multiparton interaction simulation parameters, and are important input for future improvements of the simulations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Features Events and Processes Relevant to DPC Disposal Criticality Analysis

The Department of Energy is evaluating the technical feasibility of disposal of spent nuclear fuel in dual-purpose canisters in various geologies. As part of ongoing research and development, the effect of potential post-closure criticality events on repository performance is being studied. Many different features, events, and processes (FEPs) could affect the potential for criticality or the extent of a criticality event. Additionally, a criticality event could affect other FEPs. This report uses existing lists of FEPs as a starting point to evaluate the FEPs that could affect or be affected by an in- package criticality event. The evaluation indicates that most of the FEPs associated with the waste form, the waste, or the EBS have some effect on post-closure criticality and/or are affected by the consequences of post-closure criticality. In addition, FEPs not previously considered are identified for further development.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Applying Waveform Correlation and Waveform Template Metadata to Mining Blasts to Reduce Analyst Workload

Organizations that monitor for underground nuclear explosive tests are interested in techniques that automatically characterize mining blasts to reduce the human analyst effort required to produce high - quality event bulletins. Waveform correlation is effective in finding similar waveforms from repeating seismic events, including mining blasts. In this study we use waveform template event metadata to seek corroborating detections from multiple stations in the International Monitoring System of the Preparatory Commission for the Comprehensive Nuclear-Test-Ban Treaty Organization. We build upon events detected in a prior waveform correlation study of mining blasts in two geographic regions, Wyoming and Scandinavia. Using a set of expert analyst-reviewed waveform correlation events that were declared to be true positive detections, we explore criteria for choosing the waveform correlation detections that are most likely to lead to bulletin-worthy events and reduction of analyst effort.

47 OTHER INSTRUMENTATION↗

The geometry of signal space: a case study of direct mapping between seismic signals and event distribution

SUMMARY Under favourable circumstances, seismic waveforms corresponding to an ensemble of events related by a common, spatially distributed process collectively exhibit a regular, signal-space geometry. When events in the ensemble have a common, or nearly common, source mechanism, this geometry is a distorted image of the distribution of events in the source region. The signal-space image can be visualized using a relatively simple waveform alignment and projection operation. Ensemble waveform correlation measurements can be inverted to estimate the distribution of the events in the source region, up to an arbitrary rotation, reflection and scaling, with residual distortion. We demonstrate these concepts with synthetic waveforms and with observations of long-wall mining induced seismicity for which substantial ground truth information is available. Our experience with these data has implications for location, correlation detection and machine learning and possible application to studies of repeating events in induced, volcanic and glacial seismicity. Our results place limits on the widely held assumption that waveform correlation is a useful measure of event separation. We suggest that the constraints on event separation need to be evaluated in the context of a population of related events, whose waveforms sample the signal space image of the source region. A better indicator of event separation is the length of the shortest path in signal space along the image.

58 GEOSCIENCES↗

A mini-TGA protein modulates gene expression through heterogeneous association with transcription factors

Abstract TGA (TGACG-binding) transcription factors, which bind their target DNA through a conserved basic region leucine zipper (bZIP) domain, are vital regulators of gene expression in salicylic acid (SA)-mediated plant immunity. Here, we investigated the role of StTGA2.1, a potato (Solanum tuberosum) TGA lacking the full bZIP, which we named a mini-TGA. Such truncated proteins have been widely assigned as loss-of-function mutants. We, however, confirmed that StTGA2.1 overexpression compensates for SA-deficiency, indicating a distinct mechanism of action compared with model plant species. To understand the underlying mechanisms, we showed that StTGA2.1 can physically interact with StTGA2.2 and StTGA2.3, while its interaction with DNA was not detected. We investigated the changes in transcriptional regulation due to StTGA2.1 overexpression, identifying direct and indirect target genes. Using in planta transactivation assays, we confirmed that StTGA2.1 interacts with StTGA2.3 to activate StPRX07, a member of class III peroxidases (StPRX), which are known to play role in immune response. Finally, via structural modeling and molecular dynamics simulations, we hypothesized that the compact molecular architecture of StTGA2.1 distorts DNA conformation upon heterodimer binding to enable transcriptional activation. This study demonstrates how protein truncation can lead to distinct functions and that such events should be studied carefully in other protein families.

59 BASIC BIOLOGICAL SCIENCES↗

Pyrocumulonimbus Events Over British Columbia in 2017: An Ensemble Model Study of Parameter Sensitivities and Climate Impacts of Wildfire Smoke in the Stratosphere

Abstract The Pyrocumulonimbus (pyroCb) events over British Columbia in 2017 were observed in the lower stratosphere for about 8–10 months after the smoke injections. Several previous studies used global climate models to investigate the physical parameters for the 2017 pyroCb events, but the conclusions show strong model dependency. In this study, we use the Energy Exascale Earth System Model (E3SM) and complete an ensemble of runs exploring three injection parameters: smoke aerosol mass, the percentage of black carbon within the smoke aerosols, and plume injection height. Additionally, we consider the heterogeneous reaction of ozone and primary organic matter. According to the satellite daily observed aerosol optical depth (AOD), we find that the best ensemble member is the simulation with 0.4 Tg of smoke, 3% of which is black carbon, a 13.5 km smoke injection height, and a 10 −5 probability factor of the heterogeneous reaction. Besides AOD, we examine the ensemble score based on the metrics used in previous studies: the metrics of the extinction coefficient at 18 km altitude and the maximum plume height. The conclusion of the best estimate of the injection parameters for 2017 pyroCb events shows strong not only model but also evaluation metric dependency. We use the Random Forest machine learning technique to quantify the relative importance of each parameter in accurately simulating the 2017 pyroCb events and find that the injection height is the most critical feature, no matter which metric is used to score the ensemble members.

54 ENVIRONMENTAL SCIENCES↗

Adversarial Attacks on Deep Neural Network-based Power System Event Classification Models

Online event classification is essential to strengthening the reliability of the power transmission system. Recently, deep learning based methods have achieved great success in numerous domains such as computer vision and natural language processing. Researchers began to adopt deep learning based methods to solve the power system event identification problem and achieved effective results. However, these previous works do not consider that deep learning models are vulnerable to adversarial attacks, potentially influencing real-world applications' reliability. In this paper, we adopt several adversarial attack mechanisms by adding tailored noise signal to the input Phasor Measurement Units (PMU) time series and make the deep learning model misclassify the power system event. This numerical study discloses that current state-of-the-art deep learning based power system event classifiers are extremely vulnerable to adversarial attacks, which may jeopardize the reliability of the power transmission system.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Search for NC Delta Radiative Decay Single Photon Events In MicroBooNE

MicroBooNE, a liquid argon time projection chamber at Fermilab, is investigating the MiniBooNE anomaly, which consists of an excess of low-energy electromagnetic showers in a neutrino beam. Recent results from MicroBooNE have ruled out a 3+1 sterile neutrino explanation of the anomaly, leaving the single photon-like explanation as the most likely possibility. In this poster, we describe results of a new expanded search for the neutral current Delta radiative decay topology, a rare type of event which is by far the largest expected source of neutrino-induced single photons. Using two different reconstruction paradigms simultaneously, we study in detail events both with and without visible hadronic activity; either category of event could explain the MiniBooNE anomaly, but the two could have very different implications for underlying physics. We find that events with visible protons are excluded as an explanation of the MiniBooNE anomaly, but events without visible protons remain a possible explanation requiring further study.

Hagaman, Lee [Nevis Labs, Columbia U.] (ORCID:0000↗

Grid resolution requirement for resolving rare and high intensity wall-shear stress events in direct numerical simulations

Turbulent signals are intermittent with large instantaneous fluctuations. Such large fluctuations lead to small Kolmogorov scales that are hard to resolve in numerical simulations [P. K. Yeung, K. R. Sreenivasan, and S. B. Pope, Effects of finite spatial and temporal resolution in direct numerical simulations of incompressible isotropic turbulence, Phys. Rev. Fluids 3, 064603 (2018)]. Here, the present paper follows the above basic logic, but instead of dissipation events in isotropic turbulence, we study wall-shear stress events in plane channel flow. Wall-shear stress fluctuations are increasingly more intermittent as the Reynolds number increases. Hence, one has to employ higher grid resolutions as the Reynolds number increases in order to resolve a given percentage of wall-shear stress events. The objective of this paper is to quantify effects of the grid resolutions on the rare and high intensity wall-shear stress events. We find that the standard grid resolution resolves about 99% of the wall-shear stress events at Re τ = 180. A slightly higher grid resolution has to be employed in order to resolve 99% of the wall-shear stress events at higher Reynolds numbers, and if the standard grid resolution is used for, e.g., a Re τ = 10000 channel flow, one resolves about 90%–95% wall-shear stress events.

42 ENGINEERING↗

Provider - University of Washington - Raw Data

GOES satellite, WSR-88D radar, sounding balloon, surface weather observation and mesoscale model data from the area within, up, and downstream of the study area for use in event logging procedures and case study investigations.

17 WIND ENERGY↗

Provider - University of Washington - Reviewed Data

GOES satellite, WSR-88D radar, sounding balloon, surface weather observation and mesoscale model data from the area within, up, and downstream of the study area for use in event logging procedures and case study investigations.

17 WIND ENERGY↗

A Novel Spatio-Temporal Regime Tracking Method for Impact Simulations

In this proposal, we present a novel method of tracking the rheological regimes activated during impact cratering events that will allow researchers to gain new insights into cratering mechanics. Rheology describes the stress-strain response of rocks to different conditions. Planetary impact cratering events often occur on too large of a scale to be feasibly captured in controlled experiments. Instead, these dynamic events are primarily studied using multi-physics codes equipped with complex material models that enable calculations of the impact event at scale. However, determining which physical processes are required for the problem of interest is challenging. Because the dominant rheological regimes change with space and time during crater formation, it is difficult to link numerical simulations with observable features of craters at the end of the event. The basis of this work is the implementation of numerical flags that track the activation of each rheological regime throughout impact simulations. We demonstrate this with the ‘Rock Model’ implemented in the CTH shock-physics code. We will use this rheology tracking method to ’zoom in’ on a specific region within an event and track the conditions the rock experiences over time. This work will develop community benchmarks to validate and distribute our implemented rheological models. We will focus on improving the melt models used by the planetary impact modeling community by developing an EOS-aware rheological transition from solid to melt. Through analysis of cell and tracer-particle based tracking data, we will study the effects of different rheologies on modeled outcomes, particularly on the volume and distributions of impacts melts. We will also use this method to link observable features with the rheological mechanisms responsible for them. The deliverables (peer-reviewed papers) from the proposed work are (i) tests of the implemented rheologic processes and demonstrations of the tracking flags; (ii) the first calculations of the spatio-temporal evolution of the dominant rheologies during impact cratering events; and (iii) application to delivery of impactor iron during basin-scale impacts.

58 GEOSCIENCES↗

NRC Reactor Operating Experience Analysis and Trend Summary: 2020 Update

This report presents a summary of the reliability and frequency trends identified in the 2020 update reports for component performance study, loss of offsite power analysis, initiating events analysis, and system study provided on the Nuclear Regulatory Commission (NRC) Reactor Operating Experience Results and Databases web site (https://nrcoe.inl.gov/).

99 GENERAL AND MISCELLANEOUS↗

NRC Reactor Operating Experience Analysis and Trend Summary: 2022 Update

This report presents a summary of the Nuclear Regulatory Commission (NRC) reactor operating experience analyses with data through 2022 as well as the reliability and frequency trends identified in the 2022 update reports for component performance study, loss of offsite power analysis, initiating events analysis, and system study provided on the NRC Reactor Operating Experience Results and Databases website (https://nrcoe.inl.gov/).

99 GENERAL AND MISCELLANEOUS↗

Super-Resolution for Renewable Energy Resource Data with Climate Change Impacts (Sup3rCC)

The Super-Resolution for Renewable Energy Resource Data with Climate Change Impacts (Sup3rCC) data is a collection of 4km hourly wind, solar, temperature, humidity, and pressure fields for the contiguous United States under various climate change scenarios. Sup3rCC is downscaled Global Climate Model (GCM) data. The downscaling process was performed using a generative machine learning approach called sup3r: Super-Resolution for Renewable Energy Resource Data (linked below as "Sup3r GitHub Repo"). The data includes both historical and future weather years, although the historical years represent the historical climate, not the actual historical weather that we experienced. You cannot use Sup3rCC data to study historical weather events, although other sup3r datasets may be intended for this. The Sup3rCC data is intended to help researchers study the impact of climate change on energy systems with high levels of wind and solar capacity. Please note that all climate change data is only a representation of the possible future climate and contains significant uncertainty. Analysis of multiple climate change scenarios and multiple climate models can help quantify this uncertainty.

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