Surface Meteorological Station - PNNL Short Tower, Grass Valley - Reviewed Data
In support of the Wind Forecasting Improvement Project, Pacific Northwest National Laboratory (PNNL) deployed surface meteorological stations in Oregon.
17 WIND ENERGY↗
SEARCH · Engineering Papers
Results for “energy forecasting”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Surface Meteorological Station - PNNL Short Tower, Hood River - Reviewed Data
In support of the Wind Forecasting Improvement Project, Pacific Northwest National Laboratory (PNNL) deployed surface meteorological stations in Oregon.
17 WIND ENERGY↗
Surface Meteorological Station - PNNL Short Tower, Rufus - Reviewed Data
In support of the Wind Forecasting Improvement Project, Pacific Northwest National Laboratory (PNNL) deployed surface meteorological stations in Oregon.
17 WIND ENERGY↗
Surface Meteorological Station - PNNL Short Tower, Umatilla - Reviewed Data
In support of the Wind Forecasting Improvement Project, Pacific Northwest National Laboratory (PNNL) deployed surface meteorological stations in Oregon.
17 WIND ENERGY↗
Surface Meteorological Station - PNNL 3m Tower, Physics site-7 - Reviewed Data
In support of the Wind Forecasting Improvement Project, Pacific Northwest National Laboratory (PNNL) deployed surface meteorological stations in Oregon.
17 WIND ENERGY↗
Surface Meteorological Station - PNNL 3m Tower, Physics site-8 - Reviewed Data
In support of the Wind Forecasting Improvement Project, Pacific Northwest National Laboratory (PNNL) deployed surface meteorological stations in Oregon.
17 WIND ENERGY↗
A Gate-to-Gate Life Cycle Assessment for the CO 2 -EOR Operations at Farnsworth Unit (FWU)
Greenhouse gas (GHG) emissions related to the Farnsworth Unit’s (FWU) carbon dioxide enhanced oil recovery (CO 2 -EOR) operations were accounted for through a gate-to-gate life cycle assessment (LCA) for a period of about 10 years, since start of injection to 2020, and predictions of 18 additional years of the CO 2 -EOR operation were made. The CO 2 source for the FWU project has been 100% anthropogenically derived from the exhaust of an ethanol plant and a fertilizer plant. A cumulative amount of 5.25 × 106 tonnes of oil has been recovered through the injection of 1.64 × 106 tonnes of purchased CO 2 , of which 92% was stored during the 10-year period. An LCA analysis conducted on the various unit emissions of the FWU process yielded a net negative (positive storage) of 1.31 × 106 tonnes of CO 2 equivalent, representing 79% of purchased CO 2 . An optimized 18-year forecasted analysis estimated 86% storage of the forecasted 3.21 × 106 tonnes of purchased CO 2 with an equivalent 2.90 × 106 tonnes of crude oil produced by 2038. Major contributors to emissions were flaring/venting and energy usage for equipment. Improvements on the energy efficiency of equipment would reduce emissions further but this could be challenging. Improvement of injection capacity and elimination of venting/flaring or fugitive gas are methods more likely to be utilized for reducing net emissions and are the cases used for the optimized scenario in this work. This LCA illustrated the potential for the CO 2 -EOR operations in the FWU to store more CO 2 with minimal emissions.
54 ENVIRONMENTAL SCIENCES↗
Transmission and Distribution Real-Time Analysis Software for Monitoring and Control: Design and Simulation Testing
The US electric grid is facing operational, stability, and security challenges. Transmission system operators need some measure of visibility into distribution system renewable generation. Distribution system generation needs to support transmission system voltage. The grid is experiencing an expansion in measurement systems. How to take full advantage of this expansion and defend against attacks, both cyber and physical, poses additional challenges. This paper introduces software designed to meet these challenges. At the center of the software is an Integrated System Model (ISM) that spans from transmission to secondary distribution. The ISM is employed in real-time abnormality detection, voltage stability forecasting, and multi-mode control. The software architecture along with selected analysis modules is presented. Testing results are presented for: 1—attacks on utility infrastructure; 2—energy savings from optimal control; 3—distribution system control response during a low voltage transmission system event; 4—cyber-attacks on PV inverters, where physical inverters are used in hardware-in-the-simulation-loop studies. Contributions of this work include real-time analysis that spans from three-phase transmission through secondary distribution; an approach for detecting abnormalities that employs measurements from three independent measurement systems; and a multi-mode distribution system control that responds to cyber-attacks, physical attacks, equipment failures, and transmission system needs.
14 SOLAR ENERGY↗
Ultimate limits to error probabilities for ionospheric models based on solar geophysical indices and how these compare with the state of the art
An ideal model based on a given set of geophysical indices is defined as a model that provides a least squares fit to the data set as a function of the indices considered. Satellite measurements of electron content for three stations at different magnetic latitudes were used to provide such data sets which were each fitted to the geophysical indices. The magnitude of the difference between the measured value and the derived equation for the data set was used to estimate the probability of making an error greater than a given magnitude for such an ideal model. Atmospheric Explorer C data is used to examine the causes of the fluctuations and suggestions are made about how real improvements can be made in ionospheric forecasting ability. Joule heating inputs in the auroral electrojets are related to the AL and AU magnetic indices. Magnetic indices based on the time integral of the energy deposited in the electrojets are proposed for modeling processes affected by auroral zone heating.
Nisbet, J. S.↗
Relationship of Global Precipitation Measurement (GPM) Mission to Global Change Research
In late 2001, the Global Precipitation Measurement (GPM) mission was approved as a new start by the National Aeronautics and Space Administration (NASA). This new mission is motivated by a number of scientific questions that are posed over a range of space and time scales that generally fall within the discipline of the global water and energy cycle (GWEC). Recognizing that satellite rainfall datasets are now a foremost tool for understanding global climate variability out to decadal scales and beyond, for improving weather forecasting, and for producing better predictions of hydrometeorological processes including short-term hazardous flooding and seasonal fresh water resources assessment, a comprehensive and internationally sanctioned global measuring strategy has led to the GPM mission. The GPM mission plans to expand the scope of rainfall measurement through use of a multi-member satellite constellation that will be contributed by a number of world nations. This talk overviews the GPM scientific research program that has been fostered within NASA, then focuses on scientific progress that is being made in various research areas in the course of the mission formulation phase that are of interest to the global change scientific community. This latter part of the talk addresses research issues that have become central to the GPM science implementation plan concerning: (1) the rate of global water cycling through the atmosphere and surface and the relationship of precipitation variability to the sustained rate of the water cycle; (2) the relationship between climate change and cloud macrophysical- microphysical processes; and (3) the general improvement in measuring precipitation at the fundamental microphysical level that will take place during the GPM era and an explanation of how these improvements are expected to come about.
Smith, Eric A.↗
Lightning Flash Behavior and Convective Characteristics in Hurricanes Florence (2018), Dorian (2019), and Laura (2020)
Lightning is a useful tool in forecasting and understanding the behavior of tropical cyclones (TCs). Flash extent density (FED) has been found to be indicative of strength and intensification in TCs, but optical energy is a newer parameter that has not been studied intensively. This presentation analyzes the relationship between convective characteristics, such as updraft speed and updraft size, and Geostationary Lightning Mapper (GLM) optical energy, flash area, and FED in Hurricanes Florence (2018) and Laura (2020). The maximum optical energy values were analyzed for each minute from the innermost 100 kilometers of the eye to determine if there was a relationship between optical energy, flash area, updraft behavior, and intensification. Microwave imagery and tail-doppler radar (TDR) were examined during rapid increases in flash energy to connect updraft size and strength to these spikes. Early results show an increase in size of a moderate updraft occurring just prior to an increase in lightning optical energy and TC intensity, while smaller updrafts coincide with a decrease in intensity or little to no change in intensity. Continuing work aims to investigate the role of moderate updraft size in lightning behavior and TC intensity.
Kiahna Mollette↗
A Comprehensive Approach to Measure the Efficiency of Freight Transport: Freight Mobility Energy Productivity (F-MEP) Metric
Freight travel accounts for a major share of the energy consumed in the transportation sector in any country, and the United States is no exception. Understanding and modeling freight movement is critical, particularly in the context of capturing the impact of emerging technologies on freight travel and its externalities. The domain of freight modeling and forecasting is gaining pace in the recent years, but advancement in comprehensive freight performance metrics is still lagging. Conventional freight performance metrics such as truck-miles, ton-miles, or value-miles are unidimensional and aggregated in nature, making them unsuitable to accurately capture the impact of emerging transportation trends on the performance of freight systems. Addressing this research need, this paper presents the 'Freight Mobility Energy Productivity' metric to quantify freight performance of current as well as future freight systems, accounting for various costs associated with freight transport. The proposed metric was implemented using data from the Freight Analysis Framework along with other published sources, which shows intuitive results in quantifying freight performance. Further, a scenario analysis exercise was conducted to test the capability of the metric in tracking improvements in system-level freight efficiency as a result of vehicle powertrain technology improvement. Results of the scenario analysis reinforce confidence that the proposed metric can be used as a decision support tool in assessing the efficiency of existing as well as future freight trends and technologies.
25 ENERGY STORAGE↗
Selection of high-redshift Lyman-Break Galaxies from broadband and wide photometric surveys
In this paper, we investigate the possibility of selecting high-redshift Lyman-Break Galaxies (LBG) using current and future broadband wide photometric surveys, such as the Ultraviolet Near Infrared Optical Northern Survey (UNIONS) or the Vera C. Rubin Legacy Survey of Space and Time (LSST), using a Random Forest algorithm. This work is conducted in the context of future large-scale structure spectroscopic surveys like DESI-II, the next phase of the Dark Energy Spectroscopic Instrument (DESI), which will start around 2029.We use deep imaging data from the Hyper Suprime Camera (HSC) and the Canada-France-Hawaii Telescope Large Area U-band Deep Survey (CLAUDS) on the COSMOS and XMM-LSS fields. To predict the selection performance of LBGs with image quality similar to UNIONS, we degrade the u,g,r,i and z bands to UNIONS depth.The Random Forest algorithm is trained with the u,g,r,i and z bands to classify LBGs in the 2.5 < z < 3.5 range.We find that fixing a target density budget of 1,100 deg$^{-2}$, the Random Forest approach gives a density of z > 2 targets of 873 deg$^{-2}$, and a density of 493 deg$^{-2}$ of confirmed LBGs after spectroscopic confirmation with DESI. This UNIONS-like selection was tested in a dedicated spectroscopic observation campaign of 1,000 targets with DESI on the COSMOS field, providing a safe spectroscopic sample with a mean redshift of 3. This sample is used to derive forecasts for DESI-II, assuming a sky coverage of 5,000 deg$^{2}$. We predict uncertainties on Alcock-Paczynski parameters α$_{⊥}$ and α$_{∥}$ to be 0.7% and 1% for 2.6 < z < 3.2, resulting in a potential 2% measurement of the dark energy fraction at high redshift. Additionally, we estimate the uncertainty in local non-Gaussianity and predict σ$_{fNL}$ ≈ 7, which would be comparable to the current best precision achieved by Planck. The latter forecast suggests that achieving the precision required to place stringent constraints on inflationary models (σ$_{fNL}$ ≈ 1) using spectroscopic galaxy surveys necessitates the development of a next-generation (Stage V) spectroscopic survey.
79 ASTRONOMY AND ASTROPHYSICS↗
Integration of New Technology Considering the Trade-Offs Between Operational Benefits and Risks: A Case Study of Dynamic Line Rating
Electric grid operators are adept at handling complexity and uncertainty. However, with increasing introduction of renewable generation, distributed energy resources, and more frequent severe weather events, operators will experience new workload and challenging decision scenarios. Here, this paper quantifies risks and benefits from an operator's perspective of introducing weather based forecast Dynamic Line Ratings (DLR) using variable wind conditions in addition to ambient temperature to relieve transmission congestion and facilitating more offshore wind (OSW). A concept of operations (CONOPS) applied to a forecast DLR implementation and its integration with OSW is defined. A method for evaluating tradeoffs of derating to make the rating more conservative but decreasing the benefit was developed and applied to a case study for two existing overhead transmission lines on Long Island, New York. The CONOPS uses historical day-ahead and hour-ahead High Resolution Rapid Refresh weather forecasts and weather station data to support planning and real-time operations. The analysis determines the risk of downgrades in real-time operational rating compared to the forecast and quantifies the frequency and severity of last-minute downgrades. The risk is compared against the benefits in increased capacity to provide insights on the additional amount of uncertainty DLR and OSW will add to the operator's workload.
17 WIND ENERGY↗
Selection of high-redshift Lyman-Break Galaxies from broadband and wide photometric surveys
Here, in this paper, we investigate the possibility of selecting high-redshift Lyman-Break Galaxies (LBG) using current and future broadband wide photometric surveys, such as the Ultraviolet Near Infrared Optical Northern Survey (UNIONS) or the Vera C. Rubin Legacy Survey of Space and Time (LSST), using a Random Forest algorithm. This work is conducted in the context of future large-scale structure spectroscopic surveys like DESI-II, the next phase of the Dark Energy Spectroscopic Instrument (DESI), which will start around 2029. We use deep imaging data from the Hyper Suprime Camera (HSC) and the Canada-France-Hawaii Telescope Large Area U-band Deep Survey (CLAUDS) on the COSMOS and XMM-LSS fields. To predict the selection performance of LBGs with image quality similar to UNIONS, we degrade the u,g,r,i and z bands to UNIONS depth. The Random Forest algorithm is trained with the u,g,r,i and z bands to classify LBGs in the 2.5 < z < 3.5 range. We find that fixing a target density budget of 1,100 deg -2 , the Random Forest approach gives a density of z > 2 targets of 873 deg -2 , and a density of 493 deg -2 of confirmed LBGs after spectroscopic confirmation with DESI. This UNIONS-like selection was tested in a dedicated spectroscopic observation campaign of 1,000 targets with DESI on the COSMOS field, providing a safe spectroscopic sample with a mean redshift of 3. This sample is used to derive forecasts for DESI-II, assuming a sky coverage of 5,000 deg 2 . We predict uncertainties on Alcock-Paczynski parameters α ⊥ and α ∥ to be 0.7% and 1% for 2.6 < z < 3.2, resulting in a potential 2% measurement of the dark energy fraction at high redshift. Additionally, we estimate the uncertainty in local non-Gaussianity and predict σ fNL ≈ 7, which would be comparable to the current best precision achieved by Planck. The latter forecast suggests that achieving the precision required to place stringent constraints on inflationary models (σ fNL ≈ 1) using spectroscopic galaxy surveys necessitates the development of a next-generation (Stage V) spectroscopic survey.
cosmological parameters from LSS↗
Membranes in Solar-Driven Evaporation: Design Principles and Applications
In this study, solar-driven evaporation process brings exciting opportunities to recover clean water and resources in a sustainable way from diverse sources like seawater and wastewater. Separation membranes, as a vital material in many environmental and energy applications, can contribute significantly to this process owing to their structural features. However, the unique roles of membranes in solar evaporator construction and process design are seldom recognized and not summarized yet from scientific principles and application demands, which forms the motivation of this review. Herein, the roles of membranes in different processes based on solar-driven evaporation are focused and the design principles of membrane materials and devices to meet the requirements of these applications are discussed. Fabrication strategies for photothermal membranes are introduced primarily, followed by a discussion on how to design membrane materials, devices, and processes to pursue optimal performance and realize advanced functions accompanied by evaporation. Furthermore, the future of this field is forecast with both challenges and opportunities.
14 SOLAR ENERGY↗
Comprehensive Approach to Measure the Mobility Energy Productivity of Freight Transport
Freight travel accounts for a major share of the energy consumed in the transportation sector in any country, and the United States is no exception. Understanding and modeling freight movement are critical, particularly in the context of capturing the impact of emerging technologies on freight travel and its externalities. The domain of freight modeling and forecasting has been gaining pace in recent years, but advancement in comprehensive freight performance metrics is still lagging. Conventional freight performance metrics such as truck-miles, ton-miles, or value-miles are unidimensional and aggregate in nature, making them unsuitable to accurately capture the impact of emerging transportation trends on the performance or productivity of freight systems. Addressing the research need, this paper presents the “Freight Mobility Energy Productivity” metric to quantify freight productivity of current as well as future freight systems, accounting for various costs associated with freight transport. The proposed metric was implemented using data from the Freight Analysis Framework along with other published sources, and shows intuitive results in quantifying freight productivity. Further, a scenario analysis exercise was conducted to test the capability of the metric in tracking improvements in system-level freight productivity as a result of vehicle electrification. The relative differences in Freight Mobility Energy Productivity scores help identify which zones benefit from the vehicle powertrain technology improvement. The results of the scenario analysis reinforce confidence that the proposed metric can be used as a decision support tool in assessing the productivity of existing as well as future freight trends and technologies.
47 OTHER INSTRUMENTATION↗
A Comprehensive Approach to Measure the Mobility Energy Productivity of Freight Transport: Preprint
Freight travel accounts for a major share of the energy consumed in the transportation sector in any country, and the United States is no exception. Understanding and modeling freight movement are critical, particularly in the context of capturing the impact of emerging technologies on freight travel and its externalities. The domain of freight modeling and forecasting is gaining pace in the recent years, but advancement in comprehensive freight performance metrics is still lagging. Conventional freight performance metrics such as truck-miles, ton-miles, or value-miles are unidimensional and aggregate in nature, making them unsuitable to accurately capture the impact of emerging transportation trends on the performance or productivity of freight systems. Addressing the research need, this paper presents the “Freight Mobility Energy Productivity” metric to quantify freight productivity of current as well as future freight systems, accounting for various costs associated with freight transport. The proposed metric was implemented using data from the Freight Analysis Framework along with other published sources, which shows intuitive results in quantifying freight productivity. Further, a scenario analysis exercise was conducted to test the capability of the metric in tracking improvements in system-level freight productivity as a result of vehicle electrification. The relative differences in Freight Mobility Energy Productivity scores help identify which zones benefit from the vehicle powertrain technology improvement. The results of the scenario analysis reinforce confidence that the proposed metric can be used as a decision support tool in assessing the productivity of existing as well as future freight trends and technologies.
47 OTHER INSTRUMENTATION↗