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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Control Parameter Sensitivity Study for Inverter-Based-Resource Dominated Grids: A Small Signal Stability Approach and Framework

The growing adoption of renewable energy is driving the prevalence of inverter-based resources (IBRs) within power grids. Future power grids will integrate both grid-following IBRs (GFM-IBRs) and grid-forming IBRs (GFL-IBRs) alongside synchronous generators. Therefore, it is crucial to perform stability studies that account for all components and especially control interactions related to IBRs. Extensive research has performed to study the IBR-related stability, however, the sensitivity study of IBRs' control parameters on system stability has not been adequately studied yet, especially from a systematic way. Therefore, this paper conducts a small signal stability analysis for a generic grid with multiple types of resources and develops an analytical framework for assessing the sensitivity of control parameters affecting stability margins. To achieve that, the non-autonomous reduced-order non-linear dynamic model is developed for a generic power system with multiple synchronous generator-based resources (SGBRs), GFM-IBRs, and GFL-IBRs. Based on the analytic model, a systematic framework for parametric sensitivity on systems' asymptotic stability is developed. A parameter sensitivity analysis based on eigenvalue methods is proposed. The impact of the droop controllers of GFM-IBRs, PQ-dispatch and the PLL controller of GFL-IBR on the system asymptotic stability is discussed. This sensitivity study is aiming to provide deep insights on control parameters' impact on system stability, and gives direction for parameter tuning in case of instability.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Congestion Management Solutions for Enhanced Distribution System Operations with Aggregated Distribution Grid Resources Providing Grid Services and Market Participation

Microgrids and other aggregations of distribution grid resources (DGRs) are poised to actively participate in electricity markets and provide essential grid services in the coming years. In fact, DGRs already play such a role through behind-the-meter (BTM) demand response programs and small-scale BTM dispatchable generation initiatives. At the same time, the rapid growth of artificial intelligence (AI) and cryptocurrency datacenters imposes significant, often unpredictable, demands on the power distribution system. Aggregated DGRs can serve as flexible resources that help mitigate these pressures by using available transmission and distribution capacity more efficiently, supporting resource adequacy and other reliability services, and providing bridge strategies while long-term transmission infrastructure is being developed. The impacts this activity will have on distribution networks are not fully understood and could present significant challenges for distribution utilities due to capacity constraints and the need for congestion management. Technical issues include reverse power flow, variability and possible degradation of equipment integrity, voltage violations, and customer power quality concerns. These issues will likely intensify as electricity market operators across the United States implement Federal Energy Regulatory Commission Order 2222 over the next few years.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Effectively Considering the Distribution System in Integrated Resource Plans

While electricity planning practices vary by state and utility based on utility type and market structure, integrated resource planning (IRP) remains a prominent vehicle — even in states with centrally-organized wholesale electricity markets. IRP focuses on meeting forecasted long-term electricity needs. Typically, utilities have not considered impacts of design and operation of the low-voltage distribution network in IRP. With advanced capabilities of grid-edge technologies to generate and store electricity and provide load flexibility, and large utility investments in distribution systems, it's increasingly important to consider at least some distribution planning elements in IRP. This report considers the value proposition for doing so, such as reducing utility costs through resource co-optimization and strategic siting of grid-edge resources, and idenfities the most important touchpoints between planning for bulk power and distribution systems and provide a range of tactics for integrating these two processes.

Relf, Grace [Lawrence Berkeley National Laboratory↗
DOE OSTI2026

C-HER Metadata Overview: Approach, Standards, and Rigor for the Centralized Health and Exposomic Resource

The Centralized Health and Exposomic Resource (C-HER) unifies environmental, demographic, geographic, and health-related data for exposomic research. The source data differ in format, geographic coverage, time period, resolution, terminology, and documentation. We use a common metadata framework to describe those differences and to record how each data resource has been processed, documented, and ingested. This document relates only to the C-HER metadata framework. It explains the information that is recorded for each resource, the standards used to organize that information, the conditions for metadata completeness, and the relationship between metadata and quality review. It is intended for those who need to understand what C-HER metadata communicates and how it supports appropriate use of the data. It is not an implementation specification or procedure. It does not document the database schema, source code, deployment configuration, transformation algorithms, or dataset-specific QA/QC thresholds. Those materials are maintained separately.

MacFarland, Midgie [ORNL] (ORCID:0009000807354078)↗
DOE OSTI2025

Evaluating the potential of short-term instrument deployment to improve distributed wind resource assessment

Distributed wind projects, which are connected at the distribution level of an electricity system or in off-grid applications to serve specific or local energy needs, often rely solely on wind resource models to establish wind speed and energy generation expectations. Historically, anemometer loan programs have provided an affordable avenue for more accurate onsite wind resource assessment, and the lowering cost of lidar systems has shown similar advantages for more recent assessments. While a full 12 months of onsite wind measurement is the standard for correcting model-based long-term wind speed estimates for utility-scale wind farms, the time and capital investment involved in gathering onsite measurements must be reconciled with the energy needs and funding opportunities that drive expedient deployment of distributed wind projects. Much literature exists to quantify the performance of correcting long-term wind speed estimates with 1 or more years of observational data, but few studies explore the impacts of correcting with months-long observational periods. This study aims to answer the question of how short you can go in terms of the observational time period needed to make impactful improvements to model-based long-term wind speed estimates. Three algorithms, multivariable linear regression, adaptive regression splines, and regression trees, are evaluated for their skill at correcting long-term wind resource estimates from the European Centre for Medium-Range Weather Forecasts Reanalysis version 5 (ERA5) using months-long periods of observational data from 66 locations across the US. On average, correction with even 1 month of observations provides significant improvement over the baseline ERA5 wind speed estimates and produces median bias magnitudes and relative errors within 0.22 m s −1 and 4 percentage points of the median bias magnitudes and relative errors achieved using the standard 12 months of data for correction. However, in cases when the shortest observational periods (1 to 2 months) used for correction are not well correlated with the overlapping ERA5 reference, the resultant long-term wind speed errors are worse than those produced using ERA5 without correction. Summer months, which are characterized by weaker relative wind speeds and standard deviations for most of the evaluation sites, tend to produce the worst results for long-term correction using months-long observations. The three tested algorithms perform similarly for long-term wind speed bias; however, regression trees perform notably worse than multivariable linear regression and adaptive regression splines in terms of correlation when using 6 months or less of observational data for correction. Translating the analysis to wind energy, median relative errors in the capacity factor are on average within 10 % using 1 month of training. If the observation period used for correction is not well correlated with the reference data, however, misrepresentation of the observed capacity factor can be substantial. The risk associated with poor correlation between the observed and reference datasets decreases with increasing training period length. In the worst-correlation scenarios, the median capacity factor relative errors from using 1, 3, and 6 months are within 47 %, 26 %, and 16 %, respectively.

17 WIND ENERGY↗
DOE OSTI2026

Assessing Photovoltaic Capacity Factor Variability Using Long-Term Satellite Derived Solar Resource Data Under Brazilian Climate

Accurate estimation of photovoltaic (PV) energy yield and its variability is essential for reducing financial risk and supporting reliable system planning for rapidly expanding PV markets. In Brazil, high solar adoption and increasing levels of distributed energy resources are beginning to introduce operational challenges such as curtailment and evolving grid requirements. Understanding how natural variability in solar resource propagates into PV system performance is therefore increasingly important for both project design and grid integration. Modern PV yield assessments commonly rely on multi-year meteorological datasets and probabilistic exceedance metrics (e.g., P50/P90) to quantify energy yield uncertainty for project financing. However, the implications of long-term solar resource variability for PV system design choices and high-adoption grid conditions remain less well characterized for rapidly expanding markets such as Brazil. In particular, understanding how weather-driven variability propagates into PV production distributions and capacity factor expectations is important for evaluating curtailment exposure, deployment strategies, and storage requirements in regions experiencing rapid growth of distributed and utility-scale PV. Seasonal and interannual variability in atmospheric conditions can produce substantial fluctuations in monthly PV energy production, which propagate into uncertainty in annual energy yield and capacity factor expectations. Characterizing this variability using long-term meteorological datasets allows probabilistic estimation of PV system performance and provides improved insight into the range of expected PV energy outcomes. This study explores the use of long-term satellite-derived meteorological data from the National Solar Radiation Database (NSRDB) to evaluate the variability of photovoltaic system performance across multiple locations in Brazil. Using a 27-year dataset (1998-2024), PV system simulations are performed to characterize the distribution of annual and seasonal capacity factors and energy yield outcomes, while propagating key sources of meteorological variability and model uncertainty through the PV modeling chain. The analysis also investigates the sensitivity of PV performance outcomes to key system design assumptions within the PV modeling chain, including tracking configuration and system sizing parameters. The resulting probabilistic performance characterization provides insight into how weather-driven variability influences PV production expectations and capacity factor distributions. These results provide a foundation for evaluating how weather-driven variability interacts with high PV adoption and potential storage or curtailment mitigation strategies.

14 SOLAR ENERGY↗
DOE OSTI2026

Solar Resource Measurements in Eugene, OR: Cooperative Research and Development Final Report, CRADA Number CRD-07-00252

Site-specific, long-term, continuous, and high-resolution measurements of solar irradiance are important for developing renewable resource data. These data are used for several research and development activities consistent with the NLR mission: establish a national 3-year climatological database of measured solar irradiances; provide high quality ground-truth data for satellite remote sensing validation; support development of radiative transfer models for estimating solar irradiance from available meteorological observations; provide solar resource information needed for technology deployment and operations. Data acquired under this agreement will be available to the public through NLR's Measurement & Instrumentation Data Center – MIDC (http://www.nlr.gov/midc) Or the Renewable Resource Data Center - RReDC (http://rredc.nlr.gov). The MIDC offers a variety of standard data display, access, and analysis tools designed to address the needs of a wide user audience (e.g., industry, academia, and government interests).

14 SOLAR ENERGY↗
NASA NTRS1971

NASA to Survey Earth's Resources

A wide variety of the natural resources of earth and man's management of them will be studied by an initial group of foreign and domestic scientists tentatively chosen by the National Aeronautics and Space Administration to analyze data to be gathered by two earth-orbiting spacecraft. The spacecraft are the first Earth Resources Technology Satellite (ERTS-A) and the manned Skylab which will carry an Earth Resources Experiment Package (EREP). In the United States, the initial experiments will study the feasibility of remote sensing from a satellite in gathering information on ecological problems. The objective of both ERTS and EREP aboard Skylab is to obtain multispectral images of the surface of the earth with high resolution remote sensors and to process and distribute the images to scientific users in a wide variety of disciplines. The ERTS-A, EREP, and Skylab systems are described and their operation is discussed.

Mittauer, R. T.↗
NASA NTRS1971

Inventory and analysis of natural vegetation and related resources from space and high altitude photography

A high altitude photomosaic resource map of Site 29 was produced which provided an opportunity to test photo interpretation accuracy of natural vegetation resource features when mapped at a small (1:133,400) scale. Helicopter reconnaissance over 144 previously selected test points revealed a highly adequate level of photo interpretation accuracy. In general, the reasons for errors could be accounted for. The same photomosaic resource map enabled construction of interpretive land use overlays. Based on features of the landscape, including natural vegetation types, judgements for land use suitability were made and have been presented for two types of potential land use. These two, agriculture and urbanization, represent potential land use conflicts.

Poulton, C. E.↗
NASA NTRS1972

Application of remote sensing to water resources problems

The following conclusions were reached concerning the applications of remote sensing to water resources problems: (1) Remote sensing methods provide the most practical method of obtaining data for many water resources problems; (2) the multi-disciplinary approach is essential to the effective application of remote sensing to water resource problems; (3) there is a correlation between the amount of suspended solids in an effluent discharged into a water body and reflected energy; (4) remote sensing provides for more effective and accurate monitoring, discovery and characterization of the mixing zone of effluent discharged into a receiving water body; and (5) it is possible to differentiate between blue and blue-green algae.

Clapp, J. L.↗
NASA NTRS1972

Resource analysis and land use planning with space and high altitude photography

Photographic scales providing resource data for decision making processes of land use and a legend system for barren lands, water resources, natural vegetation, agricultural, urban, and industrial lands in hierarchical framework are applied to various remote sensing techniques. Two natural vegetation resource and land use maps for a major portion of Maricopa County, Arizona are also produced.

Schrumpf, B. J.↗
NASA NTRS1972

Orbital surveys and state resource management

The resource management implications of satellite earth resource surveys for the state of Ohio are discussed. Discussions cover environmental problems, planning future developments, and short- and long-range benefits of such resource management.

Wukelic, G. E.↗
NASA NTRS1972

An integrated study of earth resources in the state of California based on ERTS-1 and supporting aircraft data

There are no author-identified significant results in this report. Results of an integrated study of earth resources in the state of California using ERTS-1 and supporting aircraft data are presented. Areas of investigation cover (1) regional agricultural surveys; (2) solving water resource management problems; (3) resource management in Northern California using ERTS-1 data; (4) analysis of river meanders; (5) assessment and monitoring change in west side of the San Joaquin Valley and central coastal zone of state; (6) assessment and monitoring of changes in Southern California environment; (7) digital handling and processing of ERTS-1 data; (8) use of ERTS-1 data in educational and applied research programs of the Agricultural Extension Service; and (9) identification, classification, and mapping of salt affected soils.

Colwell, R. N.↗
NASA NTRS1971

Measurement of Hydrologic Resource Parameters Through Remote Sensing in the Feather River Headwaters Area

The four problem are as being investigated are: (1) determination of the feasibility of providing the resource manager with operationally useful information through the use of remote sensing techniques; (2) definition of the spectral characteristics of earth resources and the optimum procedures for calibrating tone and color characteristics of multispectral imagery (3) determination of the extent to which humans can extract useful earth resource information through remote sensing imagery; (4) determination of the extent to which automatic classification and data processing can extract useful information from remote sensing data.

Thorley, G. A.↗
NASA NTRS1973

A feasibility study of using remotely sensed data for water resource models

Remotely sensed data were collected to demonstrate the feasibility of applying the results to water resource problems. Photographs of the Wolf Creek watershed in southwestern Colorado were collected over a one year period. Cloud top temperatures were measured using a radiometer. Thermal imagery of the Wolf Creek Pass area was obtained during one pre-dawn flight. Remote sensing studies of water resource problems for user agencies were also conducted. The results indicated that: (1) remote sensing techniques could be used to assist in the solution of water resource problems; (2) photogrammetric determination of snow depths is feasible; (3) changes in turbidity or suspended material concentration can be observed; and (4) surface turbulence can be related to bed scour; and (5) thermal effluents into rivers can be monitored.

Ruff, J. F.↗
NASA NTRS1973

Application of ERTS-1 Data to Aid in Solving Water Resources Management Problems in the State of California

Investigations within the State of California have emphasized the direct utilization of the supplemental data source afforded by the Earth Resources Technology Satellite-1 (ERTS-1) imagery. A user-oriented study has been underway for several years to identify and develop application methodology for remotely sensed information available from several platform levels, including low and high flights by NASA's U2 aircraft, and other manned and unmanned devices. The University of California has pursued both basic and applied research in remote sensing, through ongoing studies supported by NASA, and in cooperation with state agencies responsible for water resources and related fields. This report reviews the applications of ERTS-1 and supplementary imagery sources applicable to water resources planning, operations, and management.

Burgy, R. H.↗
NASA NTRS1973

The first Earth Resources Technology Satellite (ERTS-1)

The first Earth Resources Technology Satellite (ERTS-1) makes images of the earth's surface in four portions of the electromagnetic spectrum with sufficient spatial resolution and with a minimum of geometric distortions, so that these images may be applied experimentally to the study of geophysical processes relating to earth resources, to the exploration and conservation of these resources, and to the assessments of environmental stresses. During the first six months of operation, ERTS-1 has imaged 6.5 million square kilometers of the earth's surface every day, covering most major land masses and coastal zones as well as both polar regions of this planet. These images as well as the results of their analyses are available to all people throughout the world. Scientific investigators of all countries have been invited to participate in the utilization of ERTS-1 observations. Many of them have already demonstrated the great efficiency, economy, and reliability of making earth surveys from space.

Nordberg, W.↗
NASA NTRS1973

Skylab experiments. Volume 2: Remote sensing of earth resources

This volume covers the broad area of earth resources in which Skylab experiments will be performed. A brief description of the Skylab program, its objectives, and vehicles is included. Section 1 introduces the concept and historical significance of remote sensing, and discusses the major scientific considerations involved in remotely sensing the earth's resources. Sections 2 through 6 provide a description of the individual earth resource sensors and experiments to be performed. Each description includes a discussion of the experiment background and scientific objectives, the equipment involved, and a discussion of significant experiment performance areas.

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