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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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At least 37 records · Page 2

Grid-Forming Inverters: Project Demonstrations and Pilots

Power system operators around the world are pushing the limits of integrating inverter-based resources (IBRs) to very high levels, approaching 100% instantaneous penetration under certain operating conditions. This often applies to smaller power systems with very little or no ac interconnections to other neighboring regions or sometimes to fringes of large balancing areas, such as Denmark or Portugal, within the mainland European power system. These jurisdictions have identified the potential of grid-forming (GFM) technology as a key enabler to support the energy transition with very few or no synchronous generators online. Until recently, practical applications of GFM inverters were limited to microgrids and isolated grids and in smaller grid applications on the order of a few tens of megawatts (MW).

Australia↗

Biomass yield in a genetically diverse Miscanthus sacchariflorus germplasm panel phenotyped at five locations in Asia, North America, and Europe

Abstract Miscanthus is a high‐yielding bioenergy crop that is broadly adapted to temperate and tropical environments. Commercial cultivation of Miscanthus is predominantly limited to a single sterile triploid clone of Miscanthus × giganteus , a hybrid between Miscanthus sacchariflorus and M. sinensis. To expand the genetic base of M. × giganteus , the substantial diversity within its progenitor species should be used for cultivar improvement and diversification. Here, we phenotyped a diversity panel of 605 M. sacchariflorus from six previously described genetic groups and 27 M. × giganteus genotypes for dry biomass yield and 16 yield‐component traits, in field trials grown over 3 years at one subtropical location (Zhuji, China) and four temperate locations (Foulum, Denmark; Sapporo, Japan; Urbana, Illinois; and Chuncheon, South Korea). There was considerable diversity in yield and yield‐component traits among and within genetic groups of M. sacchariflorus , and across the five locations. Biomass yield of M. sacchariflorus ranged from 0.003 to 34.0 Mg ha −1 in year 3. Variation among the genetic groups was typically greater than within, so selection of genetic group should be an important first step for breeding with M. sacchariflorus . The Yangtze 2x genetic group (=ssp. lutarioriparius ) of M. sacchariflorus had the tallest and thickest culms at all locations tested. Notably, the Yangtze 2x genetic group's exceptional culm length and yield potential were driven primarily by a large number of nodes (>29 nodes culm −1 average over all locations), which was consistent with the especially late flowering of this group. The S Japan 4x, the N China/Korea/Russia 4x, and the N China 2x genetic groups were also promising genetic resources for biomass yield, culm length, and culm thickness, especially for temperate environments. Culm length was the best indicator of yield potential in M. sacchariflorus . These results will inform breeders' selection of M. sacchariflorus genotypes for population improvement and adaptation to target production environments.

59 BASIC BIOLOGICAL SCIENCES↗

Definition of the IEA Wind 22-Megawatt Offshore Reference Wind Turbine

This technical report describes the design of a new 22 Megawatt reference wind turbine (RWT). The turbine model was designed collaboratively by two teams at the Denmark Technical University and at the National Renewable Energy Laboratory within the International Energy Agency (IEA) Wind Technology Commercialization Programme (TCP) Task 55 on Reference Wind Turbines and Farms. RWTs serve an important purpose in the wind energy community, since they provide openly available data for models representative of current wind turbine technology, which can be used by practitioners for a variety of modeling purposes, ranging from aerodynamic, structural, and aeroelastic turbine modeling to wind farm flow modeling, across a range of fidelities. The IEA 22 RWT aims to model machines with projected installation in the 2025-2030 time frame. The turbine has a rotor diameter of 284 meters and a hub height of 170 meters. It is a class 1-B machine with a rotor specific power nearing 350 W m -2 and it is mounted on either a fixed-bottom offshore foundation or a semi-submersible floating platform.

17 WIND ENERGY↗

Ground-based_transient_electromagnetic_data_and_resistivity_models_for_SubTER_BelleCreek_2017-2018

Ground-based transient electromagnetic (TEM) data were acquired in selected locations around Belle Creek, Montana to define the resistivity structure of the near surface. Data were acquired using the ABEM WalkTEM system (Guideline Geo Ab, Sundbyberg, Sweden). TEM data were processed and numerically inverted to derive one-dimensional resistivity structure using SPIA (Aarhus Geosoftware, Aarhus, Denmark). This release includes raw and processed TEM data and resistivity models for each data location using the following structure: Ground-based_transient_electromagnetic_data_and_resistivity_models_for_SubTER_BelleCreek_2017-2018.xml SBC_TEM_2019_SoundingLocationsModels.gdb.zip - file geodatabase with all models and plots attached. This is a mirror of the contents of the model directory. Ground-based_transient_electromagnetic_data_and_resistivity_models_for_SubTER_BelleCreek_2017-2018.zip Data SBC_USF - raw data USF_format_description.pdf - manual describing the USF file format SBC_SoundingID-USF_lookup.csv - table describing the USF file naming convention and channel mapping *.usf files - raw, unprocessed data files SBC_TEM - processed data AarhusInv_manual.pdf - manual describing the TEM file format *.tem files - processed data files Models SBC_Model_Plots - plots of the data and the models for each sounding location TEM_model_data_dictionary.csv - data dictionary describing tabulated models SBC_TEM_models.csv - tabulated models

geophysical surveying↗

Angle of Incidence Characterization of Six Laminated Solar Cells for 2020 DTU Fotonik Inter-Laboratory Comparison Study

Photovoltaic energy prediction models include functions or modifiers to account for sun angle reflection losses. These functions may be known interchangeably as Angle of Incidence (AOI) or Incident Angle Modifier (IAM). While standards exist, there is no universally accepted single best practice for developing these functions. They can be generated through characterization of representative modules or single cells, in natural sunlight or indoors using simulated light sources. Repeatability of measurements and the viability of cross-laboratory comparisons are critical to confidence in validation of both methods. To investigate the differences between methods and labs, The Technical University of Denmark (DTU) initiated an international round-robin test comparison between several key test labs with AOI measurement capability. A total of six minimodules were provided in three different cell/interconnect/backsheet combinations. Sandia characterized these minimodules using methods developed over two decades specifically for the outdoor characterization of full-size photovoltaic modules. This report documents the characterization results, summarizes key observations and tabulates the processed data for comparison to results provided by other characterization labs.

14 SOLAR ENERGY↗

IEA Wind TCP Task 37: Definition of the IEA 15-Megawatt Offshore Reference Wind Turbine

This report describes a 15-megawatt offshore wind turbine with a fixed-bottom monopile support structure. This reference wind turbine is a Class IB direct-drive machine, with a rotor diameter of 240 meters and a hub height of 150 meters. An overview of the design is presented in Figure ES-1 and Table ES-1. The design reflects a joint effort between the National Renewable Energy Laboratory, sponsored by the U.S. Department of Energy, and the Technical University of Denmark, sponsored by the European Union's H2020 Program, through the second work package of International Energy Agency Wind Task 37 on Wind Energy Systems Engineering: Integrated RD&D. A forthcoming report will detail a semisubmersible floating support structure developed by the University of Maine.

15 MW↗

NREL CITIES Support (CRADA CRD-14-00558 Final Report)

The Technical University of Denmark has received a Grant from the Danish Council for Strategic Research for the project "CITIES - Centre for IT-Intelligent Energy Systems in Cities", a strategic research centre, which involves industrial partners and universities. The Alliance for Sustainable Energy, LLC will participate with DTU as an industrial partner in "CITIES" under this Cooperative Research and Development Agreement (CRADA). The Centre for IT based Intelligent Energy Systems in Cities (CITIES) Project is a Danish national research center focused on work in building short-term operational integrated energy system models that feed longer term plam1ing models, considering the spatio-temporal variations, interactions, dynamics and stochastics in the energy system, from production to consumption. CITIES will harness the extensive expertise and experience of its industrial and academic partners to conduct meaningful research with tangible outputs, including a roadmap to a fossil free future. Decision support tools will be developed to inform stakeholders of the impact of investment, control and policy measures and to identify further opportunities for energy system efficiency. Dissemination and transferring knowledge is a key value to this CRADA, and the use of results by Danish policymakers, industry and society is vital. All participants in the Centre for IT based Intelligent Energy Systems in Cities (CITIES) Project are therefore encouraged to use all means to communicate their findings to society. Wherever possible, and compatible with applicable intellectual property regulations, publications should be produced and disseminated under Open Science, Data, Source and Access principles.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Outcomes of the DOE Workshop on Atmospheric Challenges for the Wind Energy Industry

The U.S. Department of Energy-funded Mesoscale-to-Microscale Coupling (MMC) project team planned and conducted a virtual Workshop on Atmospheric Challenges for the Wind Energy Industry on October 19 and 20, 2020. The goal of the workshop was to forge a dialog with the community, including industry representatives, on how modeling tools are currently being used, the present active atmospheric modeling research in support of wind energy, and required advancements in capabilities and technology to continue to advance wind energy deployment. The workshop was planned in collaboration with an industry advisory panel that included representatives from wind power plant developers, turbine manufacturers, and companies that provide resource assessment and forecasting services. The format of the workshop included panels from government research sponsors, visionaries from industry, and mixed panels of researchers discussing research status and needs. A shared keynote presentation from the Technical University of Denmark experts anchored the second day of the workshop. An emphasis was placed on understanding the research needs in the offshore environment. In addition, breakout opportunities were provided each day. On the first day, the breakout discussions addressed predesigned questions configured to elicit participants’ thoughts on needed research directions. The second-day breakouts treated three important technical topics through a combination of presentations and group conversations. Each workshop participant chose their breakout preference from among downscaling details, modeling for turbines, and using artificial intelligence for atmospheric modeling. The discussions were robust and productive. The outcomes of the workshop include archiving a series of recommendations from industry and the research community on research directions required to further advance wind energy deployment. Discussions confirmed the need for high-fidelity modeling but that there are specific areas of applicability and other areas where the time and cost of computation is prohibitive. In those cases, the high-fidelity models can inform low-order models that are more practical for real-time or widely deployed applications. Industry must consider the financial cost of performing more expensive modeling approaches, but industry engineers and researchers are using these approaches where there appears to be a return on investment. An emerging type of low-order model is based on machine learning (ML). Participants confirmed that there are many atmospheric phenomena that need to be modeled better, including low-level jets, cold air outbreaks, land-sea induced circulations, diurnal variability, thin stable boundary layers, dynamic changes such as from frontal passage, interaction of wakes and blockage, and more. For the offshore environment, there is wide agreement that some level of ocean-wave-atmospheric coupling is necessary to capture variations in rotor-level winds needed to plan and operate offshore wind plants. Another recurring recommendation is that more observations are needed, particularly for the offshore environment. Those observations should consider the needs for model improvement, both for physically based models and for ML models. Observations must capture atmospheric profiles of variables that are important to understanding and modeling atmospheric and oceanic phenomena that impact boundary layer winds. Models must be validated with data and the uncertainty quantified, particularly those that are sensitive to initial and boundary conditions. Finally, a repeated request was to consider the holistic needs of hybrid plants of wind, solar, and storage resources because those types of plants are likely to be the wave of the future. In addition, industry wishes to understand impacts of the resource under a changing climate for long-term planning.

17 WIND ENERGY↗

Bifacial Photovoltaic Modules and Systems: Experience and Results from International Research and Pilot Applications

Within the framework of IEA PVPS, Task 13 aims to provide support to market actors working to improve the operation, the reliability and the quality of PV components and systems. Operational data from PV systems in different climate zones compiled within the project will help provide the basis for estimates of the current situation regarding PV reliability and performance. The general setting of Task 13 provides a common platform to summarize and report on technical aspects affecting the quality, performance, reliability and lifetime of PV systems in a wide variety of environments and applications. By working together across national boundaries we can all take advantage of research and experience from each member country and combine and integrate this knowledge into valuable summaries of best practices and methods for ensuring PV systems perform at their optimum and continue to provide competitive return on investment. Task 13 has so far managed to create the right framework for the calculations of various parameters that can give an indication of the quality of PV components and systems. The framework is now there and can be used by the industry who has expressed appreciation towards the results included in the high-quality reports. The IEA PVPS countries participating in Task 13 are Australia, Austria, Belgium, Canada, Chile, China, Denmark, Finland, France, Germany, Israel, Italy, Japan, the Netherlands, Norway, Spain, Sweden, Switzerland, Thailand, and the United States of America.

14 SOLAR ENERGY↗

Designing New Materials for Photovoltaics: Opportunities for Lowering Cost and Increasing Performance through Advanced Material Innovations

Within the framework of IEA PVPS, Task 13 aims to provide support to market actors working to improve the operation, the reliability and the quality of PV components and systems. Operational data from PV systems in different climate zones compiled within the project will help provide the basis for estimates of the current situation regarding PV reliability and performance. The general setting of Task 13 provides a common platform to summarize and report on technical aspects affecting the quality, performance, reliability and lifetime of PV systems in a wide variety of environments and applications. By working together across national boundaries we can all take advantage of research and experience from each member country and combine and integrate this knowledge into valuable summaries of best practices and methods for ensuring PV systems perform at their optimum and continue to provide competitive return on investment. Task 13 has so far managed to create the right framework for the calculations of various parameters that can give an indication of the quality of PV components and systems. The framework is now there and can be used by the industry who has expressed appreciation towards the results included in the high-quality reports. The IEA PVPS countries participating in Task 13 are Australia, Austria, Belgium, Canada, Chile, China, Denmark, Finland, France, Germany, Israel, Italy, Japan, the Netherlands, Norway, Spain, Sweden, Switzerland, Thailand, and the United States of America.

14 SOLAR ENERGY↗

A Father’s Day Tribute Father-son Nobel Prize-winning physicists worked together at the Lab

Partners in physics during the World War II years, father and son Niels and Aage Bohr worked side by side on the Lab’s top-secret effort to create the first atomic bombs. Arriving in Los Alamos in late 1943, Aage was just 21 years old. He had been studying physics to follow in the footsteps of his father, who had won a Nobel Prize in 1922. Aage’s higher education, however, had been interrupted by the rapid spread of Nazism in Europe. The Bohrs, who had Jewish heritage, fled their native Denmark to escape persecution, eventually arriving in Los Alamos to aid in the creation of weapons that would help end the war. Their story is part of the collections at the National Security Research Center, which is the Lab’s classified library and also houses unclassified historic materials. While at Los Alamos, Niels and Aage were accorded VIP status because of the family’s scientific renown and given new names to protect their identities: Aage was James Baker, while his father was Nicholas Baker, but the scientific community called him Uncle Nick. Whether called Niels and Aage or Nick and Jim, father and son were inseparable.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Deliverable D12 – Distributed Wind Data Catalog Development Guide and Instruction Manual

Pacific Northwest National Laboratory and Technical University of Denmark completed this deliverable as part of Work Package 2: Data Information Catalog for Distributed Wind Research (WP2) for the International Energy Agency Wind Technology Collaboration Programme Task 41: Enabling Wind to Contribute to a Distributed Energy Future (IEA Wind Task 41). As the final deliverable for WP2, Deliverable D12 includes a data instruction guide for the IEA Wind Task 41 distributed wind data catalog. As such, this document includes: a step-by-step explanation of how the IEA Wind Task 41 data catalog was created, how it was populated, and how to use it; future options for the IEA Wind Task 41 data catalog, and a summary with recommendations for future work.

17 WIND ENERGY↗

Deliverable D11 – Data Sharing, Storage, Security Protocols, and a Specification of a Potential Data Sharing Portal

Pacific Northwest National Laboratory (PNNL) and Technical University of Denmark (DTU) completed this deliverable as part of Work Package 2: Data Information Catalog for Distributed Wind Research for the International Energy Agency (IEA) Wind Technology Collaboration Programme Task 41: Enabling Wind to Contribute to a Distributed Energy Future. As part of the work plan, Deliverable D11 requires the development of data sharing, storage, and security protocols for metadata to be stored on the platform, if needed. The specification of a potential data sharing portal that expands on the catalog is also required.

17 WIND ENERGY↗

Geothermal Energy and Resilience in Arctic Countries

The eight Arctic countries - Iceland, Canada, Denmark (Greenland and the Faroe Islands) Norway, Sweden, Finland, Russia, and the United States (Alaska) - have diverse energy systems, but can be split into two distinct groups based on energy characteristics. The first group includes systems in Europe (Finland, Norway, Sweden, and Iceland), which are heavily grid-connected. The second group includes the United States (Alaska), Canada, Russia, and Greenland, which have grid-connected energy systems in their more densely populated southern regions, but are also defined by the prevalence of remote microgrids. Energy sources for heat and power vary across grid-connected communities in the Arctic nations. The primary energy source for remote communities, on the other hand, is almost exclusively diesel. This is true for both heat and power. Despite these and other key distinctions, Arctic countries share many commonalities with regard to their energy systems. One is a fundamental need for heat. Heat and electric energy are linked in most communities - remote, rural, and urban - and those linked systems are increasingly vulnerable to disruptions. Several of the Arctic countries use baseload renewable energy resources for heat and power. Iceland uses geothermal and hydroelectric; Canada, the United States, Sweden, Norway, and Finland use hydroelectric. Utilization of baseload renewable energy resources on-site for combined heat and power appears to enhance the resilience of communities in Arctic countries with high penetration of those resources. On the other hand, reliance on diesel by remote communities in other Arctic countries may be amplifying vulnerabilities. Although geothermal energy is currently used in all eight Arctic countries, resources are poorly mapped, and details can be difficult to come by. Despite this, geothermal energy provides heat and sometimes electricity at both utility scales and at the microgrid scale. Geothermal electricity is produced in Iceland, Russia, and the United States (Alaska). Direct use of geothermal heat is used in Iceland, Russia, United States, Canada, and Norway. Geo-exchange is used in Sweden, Finland, Norway, Canada, and the United States. In this paper, we reframe geothermal heat and power systems as integrated energy systems, asking the question: are integrated geothermal energy systems - where available and economic - resilient solutions for communities in Arctic countries? We identify resilience attributes of integrated geothermal energy systems, with a focus on microgrids and small-scale applications. Based on the high-level, qualitative analysis presented in this paper, the answer appears to be yes. Further work should prioritize refining our understanding of geothermal resources in Arctic countries, because development of the most economic geothermal resources in Arctic countries has the potential to enhance the energy resilience of its residents, whether in a grid-connected or remote off-grid context.

15 GEOTHERMAL ENERGY↗

International Energy Agency 22 MW Offshore Reference Wind Turbine

The presentation will be used in a public webinar to introduce the newly developed 22 megawatt offshore reference wind turbine designed within the International Energy Agency Wind Technology Commercialization Programme Task 55 Reference Wind Turbines and Plants. The turbine was designed collaboratively by two teams at the Denmark Technical University and at the National Renewable Energy Laboratory. Reference turbines serve an important purpose in the wind energy community, since they provide openly available data for models representative of current wind turbine technology, which can be used by practitioners for a variety of modeling purposes, ranging from aerodynamic, structural, and aeroelastic turbine modeling to wind farm flow modeling, across a range of fidelities. The IEA 22 RWT aims to model machines with projected installation in the 2025-2030 time frame. The turbine has a rotor diameter of 284 meters and a hub height of 170 meters. It is a class 1-B machine with a rotor specific power nearing 350 W m-2 and it is mounted on either a fixed-bottom offshore foundation or a semi-submersible floating platform.

17 WIND ENERGY↗

U-gas +Cool GTL™ - A New Integrated Process for Direct Biomass Conversion to Liquid Fuels

The U-Gas gasification technology, marketed by Sungas, is a proven fluid bed gasification technology for biomass conversion. U-Gas has been tested on a wide variety of biomass feeds including wood and waste streams. The U-Gas Technology has successfully converted wood for more than 20 years in a gasification plant in Skive Denmark at the 150t/d size. GTI has also recently developed the Cool GTL process for converting biogas to high quality gasoline, jet, and diesel fuels. The technoeconomics and LCA for the combination of the two technologies results an integrated optimized process, which will be discussed. The Cool GTL process is still in development and the development should be complete by 2023. Cool GTL converts high CO2 content feeds to synthesis gas with a 2-2.4/1 H2/CO ratio suitable for fuels synthesis. The process is based on a novel, highly stabile CO2/steam reforming catalyst. The 2.0-2.4/1 H2/CO synthesis gas ratio is always achieved, independently of feed CO2 content, by adjusting the amount of water added according to the amount of CO2 in the feed. The reformer catalyst has been tested for 500 hours and shows no measurable deactivation. The product from the reformer then goes directly to a low temperature slurry bed Fischer Tropsch reactor with an integrated finishing hydroisomerization reactor which makes hydrocarbon liquids from the synthesis gas. With this configuration no wax is produced. The technoeconomics and carbon intensity for the integration of UGas and the Cool GTL processes will be compared to other biomass conversion approaches. The use of electrolysis to boost H2 in the feed and increase liquid production will also be analyzed as a potential process improvement with sensitivities to the cost of electricity and the use of renewable electricity.

09 BIOMASS FUELS↗

Wind Turbine - SWiFT southeast - WTGa1 - Reviewed Data

Scaled Wind Farm Technology (SWiFT) Facility meteorological tower (MET), turbine, and Technical University of Denmark (DTU) SpinnerLidar data acquired on 20161216 UTC during a neutral atmospheric boundary layer inflow at a single focus distance of 2.5 D (D=27 m).

17 WIND ENERGY↗