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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 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Thermal Resilience of Residential Building with Thermally Anisotropic Building Envelope Connected to Geothermal Sources

Heat waves and cold snaps have become more frequent and more intense because of climate change. A heat wave and a cold snap are a period of excessively hot and cold weather, respectively, that poses severe risks to building occupants’ health, especially for vulnerable people. They increase electrical energy consumption and put high stress on the grid which leads to potential power outages. Therefore, it is critical to assess and actively improve the thermal resilience of buildings to cope with heat waves, cold snaps, and power outages. The thermally anisotropic building envelope (TABE) is a novel active building envelope that can save energy while maintaining thermal comfort in buildings by redirecting heat and coolness from building envelopes to hydronic loops. When connecting to a ground thermal loop (GL), TABE can utilize the relatively stable temperature of the ground to protect the indoor environment during heat waves and cold snaps. This study assesses the thermal resilience of residential buildings that installed TABE and used ground thermal energy to supply the hydronic loops, abbreviated as ground thermal loop or TABE+GL. The simulation and analysis are conducted for the US Department of Energy prototype single-family detached residential building in the hot climate of Miami, Florida and Tucson, Arizona, and the cold climate of Denver, Colorado, and Rochester, Minnesota. Heat waves and cold snaps were obtained from the historical weather data of 1998-2020 for the studied regions. Three thermal resilience metrics, including the standard effective temperature (SET) degree-hours, the Heat Index, and the Hours of Safety (HOS) were used to quantify the effect of TABE+GL. The results showed that buildings installed TABE+GL could significantly reduce the average SET degree-hours above 30°C, increase HOS, and greatly improve thermal resilience.

Shen, Zhenglai↗
DOE OSTI2024

Generic and ML Workloads in an HPC Datacenter: Node Energy, Job Failures, and Node-Job Analysis

HPC datacenters offer a backbone to the modern digital society. Increasingly, they run Machine Learning (ML) jobs next to generic, compute-intensive workloads, supporting science, business, and other decision-making processes. However, understanding how ML jobs impact the operation of HPC datacenters, relative to generic jobs, remains desirable but understudied. In this work, we leverage long-term operational data, collected from a national-scale production HPC datacenter, and statistically compare how ML and generic jobs can impact the performance, failures, resource utilization, and energy consumption of HPC datacenters. Our study provides key insights, e.g., ML-related power usage causes GPU nodes to run into temperature limitations, median/mean runtime and failure rates are higher for ML jobs than for generic jobs, both ML and generic jobs exhibit highly variable arrival processes and resource demands, significant amounts of energy are spent on unsuccessfully terminating jobs, and concurrent jobs tend to terminate in the same state. We open-source our cleaned-up data traces on Zenodo (https://doi. org/10.5281/zenodo.13685426), and provide our analysis toolkit as software hosted on GitHub (https://github.com/atlarge-research/2024-icpads-hpc-workload-characterization). This study offers multiple benefits for data center administrators, who can improve operational efficiency, and for researchers, who can further improve system designs, scheduling techniques, etc.

crossanalysis↗
DOE OSTI2021

OPFLearnData: Dataset for Learning AC Optimal Power Flow

The datasets are resulting from OPFLearn.jl, a Julia package for creating AC OPF datasets. The package was developed to provide researchers with a standardized way to efficiently create AC OPF datasets that are representative of more of the AC OPF feasible load space compared to typical dataset creation methods. The OPFLearn dataset creation method uses a relaxed AC OPF formulation to reduce the volume of the unclassified input space throughout the dataset creation process. The dataset contains load profiles and their respective optimal primal and dual solutions. Load samples are processed using AC OPF formulations from PowerModels.jl. More information on the dataset creation method can be found in our publication, "OPF-Learn: An Open-Source Framework for Creating Representative AC Optimal Power Flow Datasets" and in the package website: https://github.com/NREL/OPFLearn.jl.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

U.S. Voluntary Green Power Market Data 2019

This data book provides certain data behind figures and tables found in the NREL presentation, Status and Trends in the U.S. Voluntary Green Power Market (2019 Data). These data reflect estimates based on the best available data.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Combining Generative Modeling and Advanced Control for Building Scenario Generation

Buildings make up a large portion of energy consumption in the U.S. today. Understanding their energy consumption patterns can improve their efficiency, but requires detailed models that rely on incomplete or unknown information. Previous work has shown that artificial intelligence (AI) can be used to predict missing information and even suggest upgrades to improve building efficiency. However, building upgrades may require undesirable upfront costs. Oppositely, advanced control could improve building efficiency with negligible upfront cost. To explore the tradeoffs between these two approaches, in this work we propose a workflow to compute optimal temperature setpoint schedules to minimize energy consumption and operational cost. Results show that modifying the temperature setpoints in a building using model predictive control (MPC) can effectively reduce its energy consumption and operational cost. This optimal operation cannot fully meet a desired goal. However, we show that by considering MPC in addition to component upgrades, a desired goal can be met with significantly less upfront costs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

2022 Combined Heat and Power/District Energy System Portfolio Meeting (Summary Report)

The U.S. Department of Energy’s (DOE’s) Advanced Manufacturing Office held the 2022 Combined Heat and Power & District Energy System Portfolio Meeting on June 7–9, 2022. The meeting brought together approximately 50 researchers from industry, national laboratories, and research institutes. The purpose of the meeting was for DOE to understand the performance of the projects being sponsored through the CHP program and the status of the technology development, which informs future program planning. This report summarizes the presentations that took place at this event.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Quality Control Methods for Advanced Metering Infrastructure Data

While urban-scale building energy modeling is becoming increasingly common, it currently lacks standards, guidelines, or empirical validation against measured data. Empirical validation necessary to enable best practices is becoming increasingly tractable. The growing prevalence of advanced metering infrastructure has led to significant data regarding the energy consumption within individual buildings, but is something utilities and countries are still struggling to analyze and use wisely. In partnership with the Electric Power Board of Chattanooga, Tennessee, a crude OpenStudio/EnergyPlus model of over 178,000 buildings has been created and used to compare simulated energy against actual, 15-min, whole-building electrical consumption of each building. In this study, classifying building type is treated as a use case for quantifying performance associated with smart meter data. This article attempts to provide guidance for working with advanced metering infrastructure for buildings related to: quality control, pathological data classifications, statistical metrics on performance, a methodology for classifying building types, and assess accuracy. Advanced metering infrastructure was used to collect whole-building electricity consumption for 178,333 buildings, define equations for common data issues (missing values, zeros, and spiking), propose a new method for assigning building type, and empirically validate gaps between real buildings and existing prototypes using industry-standard accuracy metrics.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Developing a Hybrid Electric Vehicle Eco-Cooperative Adaptive Cruise Control System at Signalized Intersections.

This study develops an eco-driving strategy for hybrid electric vehicles (HEVs) in the vicinity of signalized intersections, entitled HEV Eco-Cooperative Adaptive Cruise Control at Intersections (Eco-CACC-I). The proposed system computes real-time, energy-optimized vehicle trajectories using HEV vehicle dynamics and energy consumption models. In the proposed system, a simple HEV energy model is used to compute the instantaneous fuel consumption. This HEV energy model is selected since it is general, transferable, and can be easily used to compute instantaneous energy consumption levels for HEVs without the additional input of vehicle engine data or complicated power control strategies. In addition, a vehicle dynamics model is used to capture the relationship between speed, acceleration level, and tractive/resistance forces on vehicles. The energy-optimum problem is formulated as an optimization problem with constraints, which is solved using a moving-horizon dynamic programming approach. The proposed HEV Eco-CACC-I system was tested to evaluate its performance for various speed limits, roadway grades, and signal timings. Lastly, the proposed HEV controller was implemented in a microscopic traffic simulation software to test its network-wide performance. The test results from an arterial corridor with three signalized intersections demonstrate that the proposed system can effectively reduce stop-and-go traffic in the vicinity of signalized intersections producing savings of 7.4% in energy consumption, 5.8% in traffic delay and 23% vehicle stops, respectively.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Power-Capping Metric Evaluation for Improving Energy Efficiency in HPC Applications

With high-performance computing systems now running at exascale, optimizing power-scaling management and resource utilization has become more critical than ever. This paper explores runtime power-capping optimizations that leverage integrated CPU-GPU power management on architectures like the NVIDIA GH200 superchip. We evaluate energy-performance metrics that account for simultaneous CPU and GPU power-capping effects by using two complementary approaches: speedup-energy-delay and a Euclidean distance-based multi-objective optimization method. By targeting a mostly compute-bound exascale science application, the Locally Self-Consistent Multiple Scattering (LSMS), we explore challenging scenarios to identify potential opportunities for energy savings in exascale applications, and we recognize that even modest reductions in energy consumption can have significant overall impacts. Our results highlight how GPU task-specific dynamic power-cap adjustments combined with integrated CPU-GPU power steering can improve the energy utilization of certain GPU tasks, thereby laying the groundwork for future adaptive optimization strategies.

Patrou, Maria [ORNL] (ORCID:0000000339754638)↗
DOE OSTI2024

U.S. DOE Midwest Combined Heat and Power Technical Assistance Partnership (Midwest CHP TAP) (Final Technical Report)

The University of Illinois Chicago (UIC) was awarded the U.S. DOE Midwest Combined Heat and Power Technical Assistance Partnership (Midwest CHP TAP) program to provided technical and policy expertise to support local opportunities to promote CHP, waste heat to power, district energy, and microgrids in the Midwest and Central regions of the U.S. that included the states of Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri, Nebraska, Ohio, and Wisconsin. During this contract period, UIC, through the Midwest CHP TAP activities, provided significant regional support to the U.S. strategic goals of: 1) Stimulating America’s Energy Revolution and Promoting Energy Independence; 2) Promoting Jobs and Manufacturing Competitiveness; 3) Supporting a Positive Trade Balance; 4) Enhancing Energy System Resiliency and Energy Security; and 5) Improving the Nation’s Infrastructure. UIC met the annual go/no-go metrics each year and either met and/or exceeded the milestones each year.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Fermilab Automation of Coil Winding System

The automated coil winder project creates a repeatable, scalable method for producing superconducting magnet coils with increased accuracy and efficiency. The design uses an ortho cyclic winding method to achieve high fill factors by combining computer numerical control (CNC), microcontroller-based controls, and sophisticated optimization techniques. The method optimizes coil turns, core geometry, and current consumption by utilizing analytical models based on magnetic moment, Ohm’s law, and power constraints. For particle accelerator applications, prototype testing using a 3D-printed coil winder has shown enhanced winding repeatability, thermal management, and manufacturability.

Dzida, Rafal [Northern Illinois U.]↗
DOE OSTI2021

Multi-Area Distribution System State Estimation Using Decentralized Physics-Aware Neural Networks

The development of active distribution grids requires more accurate and lower computational cost state estimation. In this paper, the authors investigate a decentralized learning-based distribution system state estimation (DSSE) approach for large distribution grids. The proposed approach decomposes the feeder-level DSSE into subarea-level estimation problems that can be solved independently. The proposed method is decentralized pruned physics-aware neural network (D-P2N2). The physical grid topology is used to parsimoniously design the connections between different hidden layers of the D-P2N2. Monte Carlo simulations based on one-year of load consumption data collected from smart meters for a three-phase distribution system power flow are developed to generate the measurement and voltage state data. The IEEE 123-node system is selected as the test network to benchmark the proposed algorithm against the classic weighted least squares and state-of-the-art learning-based DSSE approaches. Numerical results show that the D-P2N2 outperforms the state-of-the-art methods in terms of estimation accuracy and computational efficiency.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Water Management for Power stems: Systems Analysis Tasks

This presentation was given at the 2023 U.S. Department of Energy National Energy Technology Laboratory Resource Sustainability Project Review Meeting. The presentation topics cover recent updates and current research directions for the Strategic Systems Analysis and Engineering Directorate in Water Management for Power Systems. The presentation includes preliminary results to meet objectives in reducing freshwater consumption and lowering the cost of treating effluent streams for energy production.

Fritz, Alison↗
DOE OSTI2021

Single-column cryogenic air separation: Enabling efficient oxygen production with rapid startup and low capital costs—application to low-carbon fossil-fuel plants

The rapid integration of intermittent renewable sources into the electricity grid is driving the need for more flexible, low-carbon fossil-fuel plants with lower capital costs. This then drives the need to improve the cryogenic air separation unit (ASU). To address this changing landscape, we explore a Praxair single-column ASU (PSC-ASU) design with the goal of reducing costs and improving flexibility, compared to a conventional double-column ASU. The PSC-ASU incorporates partial air condensation and air pre-separation in the bottom reboiler with a phase separator as well as N 2 -enriched vapor condensation in the upper reboiler to decrease energy consumption, as compared to Linde’s single-column ASU. All three of the above-mentioned ASU designs are simulated in Aspen Plus and analyzed. An economic analysis is applied to evaluate the relative cost savings of the PSC-ASU compared to the double-column ASU. Results suggest that the specific energy consumption of the PSC-ASU is significantly lower than that of Linde’s single-column ASU due to a drastically improved oxygen recovery rate. Although this improved oxygen recovery rate is still lower than that of the double-column ASU, the required pressure ratio of the main air compressor is 21% lower than that of the double-column ASU. As a result, the specific energy consumption of the PSC-ASU is only 1.9% greater than that of the double-column ASU for producing 95.1 mol% O 2 . However, the PSC-ASU reduces the hourly capital cost by 19% due to the elimination of a high-pressure column. This would effectively decrease the total hourly cost of the ASU, and thus the total hourly cost of low-carbon, fossil-fuel power plants that require oxygen.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2025

Hybrid Power Plants for Energy Resilience: A Case Study

As renewable energy technologies are increasingly adopted, they pose an opportunity to improve the sustainability and resilience of distributed grids, especially when their design and operation is coordinated as a hybrid power plant. When included in hybrid power plants, distributed wind turbines in particular have the potential to enhance the resilience of distributed grids in areas with good wind resource, due to their ability to provide more consistent generation and ancillary services as compared to photo-voltaic (PV) solar panels. Despite this benefit, U.S. distributed wind adoption is lower than other comparable renewable energy technologies. In this study, we seek to demonstrate how hybrid power plants that include distributed wind turbines can contribute to distribution grid resilience by meeting loads (especially critical loads) more consistently, increasing reserve capacity, and providing value to customers during outages. To demonstrate these contributions, we integrate three separate frameworks and apply them to a case study in a rural electric cooperative in Iowa. Through this case study, we simulate and compare hybrid power plant design and operation during two hazard events: a tornado that causes a 48-hour distribution outage and a winter weather event that causes a 6-hour generation outage. The inclusion of a hybrid power plant that leverages 1) increased battery duration and 2) advanced forecasting and dispatch strategies that reserve capacity leading up to a hazard event best reduce lost loads as well as diesel consumption that would otherwise be used to meet those loads during short- and long-duration hazard events. Depending on the hybrid power plant capacity and operation, we find that the outage mitigation value of a hybrid power plant (measured in value to customers to avoid an outage and avoided lost revenues for the utility) is significant in both hazard events; adding wind, solar, and battery assets to the existing system adds about $50-$100M in avoided lost load and at least $4-$8k in utility value in the tornado hazard event, and $570k-$2.2M in avoided lost load and at least $220-$650 in utility value in the winter hazard scenario. In both the tornado and winter hazard scenarios, optimizing the operation of the hybrid system for resilience can lend similar value as increasing battery duration by 5 MWh for the lower capacity systems considered.

17 WIND ENERGY↗
DOE OSTI2021

Net Zero Energy Model for Wastewater Treatment Plants

The primary objective of this study is to achieve net-zero energy (NZE) wastewater treatment plants (WWTPs) by utilizing energy efficiency opportunities (EEO), combined heat and power (CHP) systems, and other renewable energy (RE) sources, e.g., solar, water, and wind powers. Herein, this study discusses an innovative energy solution for WWTPs in the United States, and one of the WWTPs with a flow capacity of 1.5 million gallons per day (MGD) was selected as a case study. An optimization tool, Hybrid Optimization of Multiple Energy Resources (HOMER) software, is used in this study to find the best energy system configuration to run the system. An energy audit for one WWTP was conducted in early 2020 and the report is used to do this study. The proposed EEOs were able to reduce WWTP energy consumption by about 11%. The excess anaerobic digester gas was utilized in a CHP system to cover about 42% of the facility’s consumption. Also, 3% of the utility energy consumption can be claimed by microturbines in the aeration tanks. Another two renewable energy systems, solar photovoltaic (PV) with 29% and water turbines with 15%, contribute to covering 100% of the WWTP energy consumption and achieving an NZE WWTP.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗