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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 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Scalable filesystem enumeration and metadata operations

Systems, apparatus, and methods are disclosed for performing scalable operations in a file system, including POSIX-like file systems. Metadata entries in a namespace or directory tree are sharded across multiple file metadata servers. An enumeration operation, such as listing a directory, is parallelized across the multiple file metadata servers, while retaining standard functionality transparently to clients. Other enumeration operations include no-output operations such as changing file attributes or deleting a file, and cumulative operations such as counting total disk space usage. The parallelization is compatible with tree-level parallelization and storage-level parallelization. Disclosed technologies can be applied to other fields requiring scalable enumeration, such as database and network applications.

Grider, Gary A.↗
NASA NTRS2003

Micro - helm - a mission operation visualization system

Micro-Helm is a PC based mission visualization system that can be employed for comprehensive monitoring of mission system states during operation. Micro-Helm was designed as a cost-effective system solution that can be adapted to multiple missions in various mission lifecycle phases. It has been successfully applied to DS1 mission during its entire operation phases and Mars Odyssey mission during its launch and orbit-insertion phase, providing scenario design and validation.

Micro-Helm↗
NASA NTRS1988

Development of a Space Station Operations Management System

To enhance the productivity of operations aboard the Space Station, a means must be provided to augment, and frequently to supplant, human effort in support of mission operations and management, both on the ground and onboard. The Operations Management System (OMS), under development at the Johnson Space Center, is one such means. OMS comprises the tools and procedures to facilitate automation of station monitoring, control, and mission planning tasks. OMS mechanizes, and hence rationalizes, execution of tasks traditionally performed by mission planners, the mission control center team, onboard System Management software, and the flight crew.

Brandli, A. E.↗
NASA NTRS1988

MODIS information, data and control system (MIDACS) operations concepts

The MODIS Information, Data, and Control System (MIDACS) Operations Concepts Document provides a basis for the mutual understanding between the users and the designers of the MIDACS, including the requirements, operating environment, external interfaces, and development plan. In defining the concepts and scope of the system, how the MIDACS will operate as an element of the Earth Observing System (EOS) within the EosDIS environment is described. This version follows an earlier release of a preliminary draft version. The individual operations concepts for planning and scheduling, control and monitoring, data acquisition and processing, calibration and validation, data archive and distribution, and user access do not yet fully represent the requirements of the data system needed to achieve the scientific objectives of the MODIS instruments and science teams. The teams are not yet formed; however, it is possible to develop the operations concepts based on the present concept of EosDIS, the level 1 and level 2 Functional Requirements Documents, and through interviews and meetings with key members of the scientific community. The operations concepts were exercised through the application of representative scenarios.

Han, D.↗
NASA NTRS2019

Ground Risk Assessment Service Provider (GRASP) Development Effort as a Supplemental Data Service Provider (SDSP) for Urban Unmanned Aircraft System (UAS) Operations

NASA’s Unmanned Aircraft System (UAS) Traffic Management (UTM) project aims to enable the integration of new aviation paradigms such as Unmanned Aircraft Systems (UAS) while providing the necessary infrastructure for future concepts such as On-Demand Mobility (ODM) and Urban Air Mobility (UAM) operations in the National Airspace System (NAS). In order to do so, the UTM project has developed an architecture to allow communication among UAS operators, UAS Service Suppliers (USS), Air Navigation Service Providers (ANSP), and the public. As part of this framework, the Supplemental Data Service Providers (SDSP) are envisioned as model and/or data based services that disseminate essential or enhanced information to ensure safe operations within low-altitude airspace. These services include terrain and obstacle data, specialized weather data, surveillance, constraint information, risk monitoring, etc. This paper highlights the development efforts of a non-participant casualty risk assessment SDSP called Ground Risk Assessment Service Provider (GRASP) which assists operators with preflight planning. GRASP is based on the previously introduced UTM Risk Assessment Framework (URAF) and allows UAS operators to simulate and visualize potential non-participant casualty risks associated with their proposed flight. The risk assessment capability also allows operators to revise their flight plans if the casualty risks are determined to be above acceptable thresholds. GRASP is configured to account for future improvements including servicing airborne aircraft as part of NASA’s System-Wide Safety (SWS) project.

Ancel, Ersin↗
DOE OSTI2024

Solar, Wind, and Load Forecasting Dataset for MISO, NYISO, and SPP Balancing Areas

The Performance-based Energy Resource Feedback, Optimization, and Risk Management (PERFORM) program is an initiative intended to foster "a fundamental shift in grid management rooted in an understanding of asset risk and system risk" (ARPA-E 2020). Launched by the Advanced Research Projects Agency-Energy (ARPA-E), the program supports efforts to incorporate uncertainty in electric power decision making. In support of PERFORM, the National Renewable Energy Laboratory (NREL) has produced a set of time-coincident forecasts of solar, wind, and load profiles. As part of Phase I of the PERFORM effort, NREL created a dataset that consists of one year of time-coincident load, wind, and solar actuals and probabilistic forecasts based on data from the Electric Reliability Council of Texas (ERCOT) (Bryce et al. 2023). In Phase II, NREL developed similar datasets for three other U.S. Independent System Operators (ISO): the Midcontinent Independent System Operator (MISO), the New York Independent System Operator (NYISO), and the Southwest Power Pool (SPP).

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2015

Enhancing the Traffic Management Advisor's Schedule by Time Advance

A time advance algorithm associated with the scheduling functionalities of the Traffic Management Advisor (TMA) for arrival flights is presented and evaluated. The algorithm enhances TMA's meter fix schedule by advancing the flights' Scheduled Time of Arrival (STA) by an amount that minimizes their systemic operating cost. The systemic operating cost leverages the inherent trade-off of time and fuel efficiency resident in the cost index of modern flight management systems. The resulting STAs are achievable by speeding up the leading flights from their desired nominal speed profiles. A key advantage of this approach is that it reduces systemic delay to tight groupings of arriving aircraft as well as increases sustained throughput of the operation. A fast-time, Monte Carlo simulation that emulates TMA's scheduling functionalities is performed for arrival flights to the Phoenix Airport to quantify the benefit of the time advance algorithm. Results show consistent time saving benefits, ranging from 3 to 50 minutes for 112 flights with varying levels of traffic congestion.

arrival traffic management↗
DOE OSTI2022

DSO+T: Valuation Methodology and Economic Metrics (DSO+T Study: Volume 4)

This report summarizes a rigorous valuation analysis methodology used by the Distribution System Operator with Transactive (DSO+T) study to estimate the financial benefits and costs of adopting Transactive Energy coordination of distributed energy resources for key stakeholders (for example distribution system operators and customers). This was achieved by modeling the value exchanges between stakeholders and determining the annualized costs and revenues experienced by stakeholders, enabling the evaluation of overall impact on stakeholder’s annualized cash flow. Extensive work was conducted developing methods to estimate the operating costs of distribution system operators at a level of granularity that would allow the financial impact of implementing a transactive energy approach to be estimated. This work included developing parametric models for labor and software costs, distribution system capital and maintenance costs, growth rates, and factors to determine annualized costs of capital investments. Simulation results were used to calculate wholesale energy costs and revenues from retail sales. Valuation analysis methods were also developed for other stakeholders including customers, the transmission system operator, independent system operator, and generators. The resulting capability allows a complete mapping of the flow of financial value between stakeholders that can be directly integrated with the results of demand flexibility simulations. Example results are provided for a business-as-usual case and compared to a transactive energy case as well as to actual cost data.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Operational Probabilistic Tools for Solar Uncertainty (OPTSUN) (Final Project Report for DOE Solar Forecasting II Project)

Increasing levels of solar PV can challenge system operations and may require novel methods to operate the power system reliably and efficiently. Power system operating plans generally use deterministic forecasts, in which the variable energy resources are represented by the expected value for each interval of the decision horizon. Probabilistic forecasts are relatively new but have the potential to address the shortfalls of deterministic forecasts. However, understanding how best to use such forecasts is still a key gap in industry and was the focus of this project. The project had three workstreams. In a forecasting workstream, improvements were made to baseline probabilistic forecasts using a number of new approaches such as machine learning methods and improved input data. In a design workstream, advanced simulation tools used these forecasts to investigate newly proposed reserve determination methods. Lastly, in a demonstration workstream a scheduling management platform (SMP) was developed to leverage probabilistic forecasts in a modular and customizable manner. In order to study the benefits that could be accrued, the project team collaborated with three utility partners (Duke Energy, Southern Company and Hawaiian Electric) to deliver improved probabilistic forecasts for each region and to model each region in case studies using advanced production cost modeling tools. Different methods to determine operating reserve requirements from probabilistic forecasts were developed, simulated, and tested across each region. The benefits of using these newly proposed methods varied by utility, but, in general, using probabilistic forecasts as well as historical data to set the reserve requirements seems to improve reliability related results, with less risk of reserve or supply shortfalls. The cost implications were not always straightforward; in some cases the new methods could show a reduction in expected operating costs, but often the increase in reserves associated with better risk mitigation using probabilistic forecasts could result in an increase in operating costs in the simulations. The SMP tool was developed to process probabilistic forecasts from their initial receipt through to scheduling decisions. This open-source tool consists of several modules for scenario development, reserve requirements calculation, and visualization. The SMP tool was demonstrated to a wide range of operators and stakeholders at all three utilities and further improved based on their feedback. The tool will be available on www.epri.com/optsun. The proposed probabilistic information-based reserve determination approaches have the potential to be implemented by different regions to ensure an economic and reliable power system operation on power systems integrating increasing levels of variable renewable resources. The innovative yet practical methods developed in this project demonstrated tangible benefits from using probabilistic forecasts beyond just study-based assessments to include three unique balancing areas. The demonstrated benefits across the multiple utility environments, are expected to provide system operators in all regions the confidence required and a platform to adopt the new forecasting and operating methods.

14 SOLAR ENERGY↗
DOE OSTI2024

Preventive Power Outage Estimation Based on a Novel Scenario Clustering Strategy

The increasing occurrence of extreme weather events is challenging power grid operation. For extreme weather events, the system operator is responsible for estimating the power outages and scheduling the restoration resources. This paper proposes an outage evaluation framework to identify the possible unserved load profiles, vulnerable areas, and mobile energy adequacy. The outputs of an outage prediction model tool are used to generate numerous faulted line scenarios. Next, each scenario's nodal unserved load profile is obtained by solving a three-phase restoration model that considers repair crews and mobile energy resources (MERs). Then, a novel scenario clustering strategy is developed to cluster the unserved load profiles into multiple representative profiles which the system operator can focus on. Finally, case studies on a distribution system evaluate the damage caused by an extreme weather event and verify the effectiveness of the proposed scenario clustering strategy.

MATHEMATICS AND COMPUTING,POWER TRANSMISSION AND D↗
DOE OSTI2021

Method and apparatus for controlling a vehicle including an adaptive cruise control system

Operating a subject vehicle equipped with an adaptive cruise control system includes setting initial states for control parameters, including setting a desired vehicle speed and determining a desired following gap range, wherein the desired following gap range is associated with a lead vehicle. Operation is controlled via the adaptive cruise control system based upon the initial states for the control parameters. Operation also includes monitoring for presence of the lead vehicle. Upon detecting presence of the lead vehicle, an actual following gap is determined between the subject vehicle and the lead vehicle, and the initial states of the control parameters associated with the adaptive cruise control system are adjusted based upon the actual following gap between the subject vehicle and the lead vehicle, and the desired following gap range. Operation is controlled via the adaptive cruise control system based upon the adjusted initial states of the control parameters.

Zhao, Junfeng↗
NASA NTRS1985

Designing a configuration control mechanism for a flight software validation facility

Embedded computer systems and supporting operating systems have recently enabled the automation of many time-critical flight functions. This automation requires the integration of computer hardware and software, aircraft hardware, and the flight application. To properly integrate and control these critical functions requires a real-time environment that is provided by the onboard flight computer, a real-time operating system, and a real-time flight application that supplies the input commands to the aircraft and responds to the resulting actions. The increased complexity of developing and testing such real-time applications can best be supported by a separate test facility that provides the processing visibility and control which is virtually impossible in the actual real-time operating environment. Such a flight software validation facility has been developed at the NASA Langley Research Center to support applications using the Shuttle real-time language HAL/S. The development and control of this facility are described. Some of the management techniques used were project schedules, status monitoring, code walk-throughs, configuration control, phased releases, validation suites, and modern programming techniques.

Smith-Taylor, R.↗
DOE OSTI2025

Deep Factorization Machine Learning for Disaggregation of Transmission Load Profiles with High Penetration of Behind-The-Meter Solar

The ever-growing integration of distributed energy resources (DERs), especially behind-the-meter (BTM) solar generations, poses imperative operational challenges to system operators such as regional transmission organizations (RTOs). It is important for RTOs to effectively and accurately extract actual load profiles at the transmission level for a single node with significant BTM solar injection. This paper first illustrates the necessity of disaggregating the daily actual load profile of a single node. Furthermore, by segmenting nodes with selected timeseries features, nodes with significant BTM solar generation are identified. Lastly, a bi-level framework is proposed, comprising reference node disaggregation and DeepFM nodal disaggregation, aimed at disaggregating the nodal load profiles from which system operators require more information. By adopting a hybrid Deep Factorization Machine (DeepFM) model, the model achieve accurate results by extracting both linear and nonlinear relations between nodes in the same region and the zonal load and nodal load profile. To overcome the lack of ground truth, this paper segments the load profile into daytime, nighttime, and zero-crossing points and utilizes the latter two for evaluation purposes. The proposed disaggregation procedure is validated using real world, minute-level, normalized, and anonymized nodal data in the PJM service territory.

42 ENGINEERING↗
DOE OSTI2026

Generator Interconnection Costs to the Transmission System in non-ISO Balancing Authorities [Slides]

Electric transmission system operators—including Independent System Operators (ISOs), Regional Transmission Organizations (RTOs), and utilities—require proposed power plants to undergo a series of interconnection studies before connecting to the grid. These studies assess what transmission upgrades or new infrastructure may be necessary and assign the associated costs to the project. Lawrence Berkeley National Laboratory has compiled, aggregated, and cleaned interconnection cost data, originally for ISOs/RTOs, and now for five non-ISO Balancing Authorities: PacifiCorp, Bonneville Power Authority, Duke Energy Progress, Duke Energy Carolinas and Duke Energy Florida. Insufficient transparency in interconnection cost data may contribute to rapidly expanding interconnection queues, with active queue capacities tripling between 2020 and 2024 in the studied BAs. Most projects withdraw after receiving high interconnection cost estimates. Interconnection costs have increased since the early 2000s, with average costs for "complete" projects reaching $194/kW between 2018 and 2024. Active queue projects and withdrawn projects incur substantially higher costs, primarily due to rising network upgrade costs. Recent interconnection costs in non-ISO balancing authorities are higher than in ISO regions, potentially due to a greater willingness to pay among developers. Utility-scale solar, wind, and storage projects have interconnection costs that exceed those for natural gas. However, when focusing on projects that do not withdraw from the queue, the interconnection costs for these technologies are more similar to natural gas projects. Other key findings include: (1) Larger generation projects benefit from lower proportional interconnection costs, (2) capacity transmission service (NRIS) often requires additional network investments, and (3) projects with high network upgrade costs are often clustered geographically. The dataset includes results from 2,104 interconnection studies conducted between 2000 and 2024, covering projects that are operational, withdrawn, or still progressing through the study process. The Excel file contains (a) the complete project-level interconnection cost dataset, and (b) seven additional tabs summarizing cost metrics across dimensions such as time, market structure, cost category (point of interconnection vs. broader network upgrades), fuel type, service type (ERIS vs. NRIS), generator size, and geography.

24 POWER TRANSMISSION AND DISTRIBUTION↗