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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 433 records · Page 24

GMLC Southeast Regional Consortium: Technology Driven Improvements to Power Grid Resiliency

Recognizing that electric grid challenges can differ by geographical regions across the US, the Department of Energy (DOE) created a pioneer regional partnership to provide technical assistance to stakeholders facing grid modernization challenges. The southeast regional teams will transfer technologies developed under DOE auspices to stakeholders for testing, evaluation, and market validation. Regional members will help define critical challenges and pave the way for transition of technologies to the commercial sector. Using the depth and expertise at Oak Ridge National Laboratory, Savannah River National Laboratory, University of Tennessee’s CURENT, CAPER and the Clemson 20 MVA Electrical Grid Laboratory—along with critical industry partners, such as Duke Energy, TVA, Southern Company, EPB, and Santee Cooper—the Southeast Regional Consortium team will conduct collaborative research to advance the state of the grid in the Southeast region and improve power system resiliency to enhance responsiveness, enable faster restoration of power, and increase distributed energy resource (DER) concentrations. This report provides details of the technical research and demonstration projects accomplished by Oak Ridge National Laboratory (ORNL) as part of the Southeast Regional Consortium. Specifically, ORNL analyzed the application of optical current and voltage measurements impedance relays which would enable step distance protection to be deployed on distribution systems. This would improve the precision of determining the geographic location of faults, increase network topology flexibility, and allow bi-directional power flow. Next, ORNL deployed time sensitive networking technology on the EPB fiberoptic data network to study the impact of increased sensor traffic on existing supervisory control and data acquisition data. The deterministic latency and high bandwidth were demonstrated by remotely inspecting a substation using a drone with full HD streaming video operated at the EPB Control Center. Finally, a new application-based communication and control system developed at ORNL call CSEISMIC was tested for future deployment on the EPB Control Center microgrid using a hardware-in-the-loop testbed that was also developed at ORNL. The controller was able to successfully optimize ancillary service when the microgrid is connected to the distribution network. The seamless islanding, resynchronization, and reconnection of the microgrid was also demonstrated through the testing.

24 POWER TRANSMISSION AND DISTRIBUTION↗

An Environmental Approach for Construction, Operation, and Maintenance of Floating Solar Array Renewable Energy Projects on Army Installations

The U.S. Army Office of Energy Initiatives (OEI) has primary responsibility over renewable projects to help achieve the Army’s renewable energy goals. The OEI serves as the central management office for partnering with U.S. Army installations to implement cost-effective, renewable energy projects, leveraging private sector financing. Siting, construction, and operation of solar power systems on U.S. Army installations help to achieve renewable energy goals. This report provides a general framework for environmental analysis for the siting, construction, and operation of floating solar renewable energy projects on U.S. Army installations, to include joint bases managed by the Department of the Army. This report includes specific information by resource area regarding the potential environmental impacts and probable best management practices or minimization approaches that afford environmental protection. This report provides analyses and suggestions that could support a programmatic analysis or site-specific action.

14 SOLAR ENERGY↗

Artificial Intelligence/Machine Learning Technology in Power System Applications

The primary purpose of this report is to provide an overview of the advancement in artificial intelligence and machine learning (AI/ML) technologies and their applications in power systems. It offers a foundation for understanding the transformative role of AI/ML in power systems and aims to stimulate further research and development in this area. This report begins with a historical perspective of AI/ML technologies, then explores their advancement to today’s prominence. The document highlights key contributors to the success of AI/ML technologies, including increased computational power, greater data availability, innovative algorithms, and advanced tools. It further introduces various AI/ML techniques, including supervised, unsupervised and reinforcement learning, graph neural networks, and generative AI. It also emphasizes the critical importance of ensuring the safety, security, and trustworthiness of these AI/ML techniques within this sector. The report reviews the recent representative advancements in various power system applications enhanced by AI/ML techniques, underscoring key developments and their transformative impact as evidenced by numerous studies. It also explores both the opportunities and challenges associated with the application of AI/ML technologies to improve power system applications. While the report extensively covers AI/ML applications in power systems, focusing primarily on the technical and operational aspects, it may not thoroughly explore the sociopolitical, economic, and broader regulatory implications of AI/ML integration in power systems. AI/ML techniques hold significant potential for enhancing power system applications; however, they are not omnipotent. It is crucial to acknowledge their limitations and understand that they may not be able to address all challenges in the power system domain. Various factors must be considered that influence the implementation, adoption, and effectiveness of AI/ML solutions, including but not limited to safety, security, transparency, and trustworthiness. Additionally, the incorporation of advanced human–machine interfaces is essential, as it enables humans to validate the effectiveness of AI/ML solutions while remaining actively engaged, fostering trust in AI/ML deployment. Finally, the report summarizes AI/ML research activities supported by the Department of Energy (DOE) Office of Electricity (OE) through the Advanced Grid Modeling (AGM) program. The work aligns with the interests and mission of DOE-OE AGM, with the report serving as a resource for identifying existing progress and for pinpointing future applications within AI/ML that need further exploration and support.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Key Grid-Interactive Efficient Building Technologies for Federal and Commercial Facilities

This report serves as a resource for building owners and managers interested in deploying GEB technologies in federal and commercial facilities. This document also provides an overview of smart buildings and the prioritization and categorization of GEB technologies that have a high potential to provide grid services.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Significant techniques in the processing and interpretation of ERTS-1 data

The discipline oriented investigations underway at the Johnson Space Center (JSC) using ERTS-1 data provide an appropriate framework for the systematic evaluation of the various elements comprising a prototype multispectral data processing and analysis system. In particular such a system may be thought of as the integration of: (1) a preprocessing subsystem; (2) a spectral clustering subsystem, (3) a correlation and classification subsystem; (4) mensuration subsystem; and (5) an information management subsystem. Specific elements of this system are already operational at JSC. It is in the context of this system that technique development and application is being pursued at JSC. Aircraft, ERTS and EREP data will be utilized to refine the subsystem elements for each of the data acquisition systems or system combinations that are optimally suited for a specific Earth Resources application. The techniques reported are those that have been developed to date during the utilization of ERTS-1 data in this processing and analysis system.

Cousin, S. B.↗

Application of ERTS-1 Results to US Department of Interior Programs

The activities of the U.S. Department of Interior which have benefited from ERTS-1 data are described. It is stated that the primary interest is in the area of land use. Legislative actions regarding land use are reported. Programs involving renewable resources are stressed.

John M DeNoyer↗

An algorithm for the space shuttle scheduling problem

The problem of determining launch times for a set of missions is considered. Launch times must satisfy early start time and resource constraints. The investigation reported is concerned with the minimization of the number of missions which are launched after specified late start times. An algorithm is presented which, under certain restrictive assumptions, provides an optimal solution. If the restrictive assumptions are not satisfied, the algorithm may be used to obtain a lower bound on the number of missions flown late.

Fisher, M. L.↗

Guidelines for Line-Oriented Flight Training, Volume 1

Line-Oriented Flight Training (LOFT) is a developing training technology which synthesizes high-fidelity aircraft simulation and high-fidelity line-operations simulation to provide realistic, dynamic pilot training in a simulated line environment. LOFT is an augmentation of existing pilot training which concentrates upon command, leadership, and resource management skills. This report, based on an NASA/Industry workshop held in January, 1981, is designed to serve as a handbook for LOFT users. In addition to providing background information, guidelines are presented for designing LOFT scenarios, conducting real-time LOFT operations, pilot debriefing, and instructor qualification and training. The final chapter addressed other uses of LOFT and line-operations (or full-mission) simulation.

Lauber, J. K.↗

Preliminary results from the evaluation of Cockpit Resource Management training - Performance ratings of flightcrews

The first data from the NASA/University of Texas Crew Performance project on the behavior of flightcrews with and without formal training in Cockpit Resource Management (CRM) is reported. Expert observers made detailed ratings of 15 components of crew behavior in both line operations and in full mission simulations. The results indicate that such training in crew coordination concepts increases the percentage of crews rated as above average in performance and decreases the percentage rated as below average. The data also show high and unexpected degrees of variations in rated performance among crews flying different aircraft within the same organization. It was also found that the specific behaviors that triggered observer ratings of above or below average performance differed markedly between organizations. Characteristics of experts' ratings and future research needs are also discussed.

Helmreich, Robert L.↗

Coordinated scheduling for dynamic real-time systems

In this project, we addressed issues in coordinated scheduling for dynamic real-time systems. In particular, we concentrated on design and implementation of a new distributed real-time system called R-Shell. The design objective of R-Shell is to provide computing support for space programs that have large, complex, fault-tolerant distributed real-time applications. In R-shell, the approach is based on the concept of scheduling agents, which reside in the application run-time environment, and are customized to provide just those resource management functions which are needed by the specific application. With this approach, we avoid the need for a sophisticated OS which provides a variety of generalized functionality, while still not burdening application programmers with heavy responsibility for resource management. In this report, we discuss the R-Shell approach, summarize the achievement of the project, and describe a preliminary prototype of R-Shell system.

Natarajan, Swaminathan↗

A Comparison of a Brain-Based Adaptive System and a Manual Adaptable System for Invoking Automation

Two experiments are presented that examine alternative methods for invoking automation. In each experiment, participants were asked to perform simultaneously a monitoring task and a resource management task as well as a tracking task that changed between automatic and manual modes. The monitoring task required participants to detect failures of an automated system to correct aberrant conditions under either high or low system reliability. Performance on each task was assessed as well as situation awareness and subjective workload. In the first experiment, half of the participants worked with a brain-based system that used their EEG signals to switch the tracking task between automatic and manual modes. The remaining participants were yoked to participants from the adaptive condition and received the same schedule of mode switches, but their EEG had no effect on the automation. Within each group, half of the participants were assigned to either the low or high reliability monitoring task. In addition, within each combination of automation invocation and system reliability, participants were separated into high and low complacency potential groups. The results revealed no significant effects of automation invocation on the performance measures; however, the high complacency individuals demonstrated better situation awareness when working with the adaptive automation system. The second experiment was the same as the first with one important exception. Automation was invoked manually. Thus, half of the participants pressed a button to invoke automation for 10 s. The remaining participants were yoked to participants from the adaptable condition and received the same schedule of mode switches, but they had no control over the automation. The results showed that participants who could invoke automation performed more poorly on the resource management task and reported higher levels of subjective workload. Further, those who invoked automation more frequently performed more poorly on the tracking task and reported higher levels of subjective workload. and the adaptable condition in the second experiment revealed only one significant difference: the subjective workload was higher in the adaptable condition. Overall, the results show that a brain-based, adaptive automation system may facilitate situation awareness for those individuals who are more complacent toward automation. By contrast, requiring operators to invoke automation manually may have some detrimental impact on performance but does appear to increases subjective workload relative to an adaptive system.

Bailey, Nathan R.↗

The lipidomics reporting checklist a framework for transparency of lipidomic experiments and repurposing resource data

The rapid increase in lipidomic studies has led to a collaborative effort within the community to establish standards and criteria for producing, documenting, and disseminating data. Creating a dynamic checklist that condenses key information about lipidomic experiments into common terminology will enhance the field's consistency, comparability, and repeatability. Here, we describe the structure and rationale of the established Lipidomics Minimal Reporting Checklist to increase transparency in lipidomics research.

59 BASIC BIOLOGICAL SCIENCES↗

Scalable Coordination and Control for Multiple Microgrids: Ten Month Progress Report

The incorporation of distributed energy resources into existing distribution systems provides make voltage and frequency regulation challenging for distribution system operators and in sufficient concentrations can destabilize the power grid. Re-configuring our distribution systems as a system of connected microgrids is one method for mitigating these instabilities. However, there is little economic reason for distribution system operators to undertake this complex upgrade of their systems. By looking beyond voltage, frequency, and power regulation for microgrids, new methods for controlling and operating microgrids can provide new functionality such as load flattening that will benefit distribution systems operators. This report details the initial research into new scalable coordination and control techniques that could be used to add this new functionality.

24 POWER TRANSMISSION AND DISTRIBUTION↗

2022 Power Global Community (Gloco) Summit Summary Report

The Prediction Of Worldwide Energy Resources (POWER) Project 25th year of providing global solar and meteorology data products to the world. The goals of this event were to inform users of new, enhanced features, gather feedback on services, identify new requests and requirements, and capture more thorough user stories while identifying new user communities and partnership opportunities. The event was “virtual” and had over 580 registrants. Over the two-day event, the Summit was attended by 162 unique attendees representing 24 countries.

NASA↗