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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 163 records · Page 9
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Progress Toward Evaluating Roughness-Resolved Aerothermodynamic Simulations for the Mars Sample Return Earth Entry System

This work pursues the efficient Navier-Stokes simulation, using NASA’s standard LAURA and DPLR simulation tools, of the flowfield and convective heating resulting from the patterned-roughness surface of the Mars Sample Return (MSR) Earth Entry System (EES). This type of simulation has been infeasible for past NASA missions. However, for EES, the combination of a patterned roughness heatshield approximated with a sinusoidal pattern, the zero degrees angle of attack nominal flow, and the supersonic boundary layer edge Mach number, all combine to make these roughness resolved grid simulations feasible. The patterned roughness and zero degrees angle of attack nominal flow allow the simulation domain to be reduced to a thin axial flowfield slice that captures a minimum of single period of the roughness pattern. With a periodic boundary condition applied along the boundaries of this slice, simulation on the reduced domain is identical to the full domain but with significant cost saving. The supersonic boundary layer edge Mach number prevents the upstream influence, which allows the smooth stagnation region to be frozen. This freezing of the stagnation region flow is required because of the numerical instability resulting from the tight spacing of the grid in the axial direction as the stagnation point is approached. Applying the developed analysis approach to a peak heating EES case results in a roughness augmentation factor for the convective heating of 1.32, which agrees well with correlations that predict values between 1.30 and 1.37. Analysis approach developed in this work provides the framework for future studies of turbulence modeling impacts and the influence of an ablating surface.

Earth Entry System↗
DOE OSTI2020

Laser propagation in a subcritical foam: Subgrid model

Here, we present a subgrid model for laser propagation in a subcritical foam. Our model describes the expansion of laser-irradiated foam elements that are below the resolution of the simulation grid and predicts the plasma conditions that result from burning down the foam. Our model can be included as a module within a larger multiphysics code, and we have implemented it within the code pF3D, which is used for simulating a laser-plasma interaction. The model predicts a reduced propagation velocity for a laser through a subcritical foam compared to simulating that foam as a homogeneous gas. This is attributed to the laser energy that goes into burning down the foam microstructure. We compare our model against experimental data by simulating a 2 mg/cc SiO 2 foam shot performed at the Janus laser facility at the Lawrence Livermore National Laboratory. pF3D simulations with the foam model predict hot ion temperatures. This leads to a reduction in the level of stimulated Brillouin scattering (SBS), bringing the simulated level of SBS into agreement with the data. Intensity fluctuations at the foam front due to laser speckles and refraction result in ion temperature fluctuations when the foam burns down. These drive long-lived electron density fluctuations on scales that are large compared to the pore size.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

Coupling Visualization, Simulation, and Deep Learning for Ensemble Steering of Complex Energy Models

We describe a new framework that allows users to explore and steer ensembles of energy systems simulations by coupling multiple energy models and interactive visualization through a dataflow API. Through the visual interface, users can interactively explore complex parameter spaces populated by hundreds, or thousands, of simulation runs and interactively spawn new simulations to 'fill in' regions of interest in the parameter space. The computational and visualization capabilities reside within a general-purpose dataflow architecture for connecting producers of multidimensional timeseries data, such as energy simulations, with consumers of that data, whether they be visualizations, statistical analyses, or datastores. Fast computation and agile dataflow can enhance the engagement with energy simulations, allowing users to populate the parameter space in real time. However, many energy simulations are far too slow to provide an interactive response. To support interactive feedback, we are creating reduced-form simulations developed through machine learning techniques, which provide statistically sound estimates of the results of the full simulations at a fraction of the computational cost. These reduced-form simulations have response times on the order of seconds, suitable for real-time human-in-the-loop design and analysis. The approximation methods apply to a wide range of computational models, including supply-chain models, electric power grid simulations, and building models. Such reduced-form representations do not replace or re-implement existing simulations, but instead supplement them by enabling rapid scenario design and exploration for large ensembles of simulations. The improved understanding, facilitated by the reduced-form models, dataflow API, and visualization tools, allows researchers to better allocate computational resources to capture informative relationships within the system as well as provide a low-cost method for validating and quality-checking large-scale modeling efforts.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Virtual Oscillator Control Maintains Grid Operations with High Inverter Penetrations

VOC makes each inverter behave electrically like a spring, 'bouncing back' to its normal operating range when disturbed. Coupling these inverters electronically could result in a new way to stabilize power grids. VOC has been demonstrated in a microgrid using several small inverters. In addition, five custom-designed inverters have been built and will be tested with grid simulations at NREL using power hardware-in-the-loop technology. VOC may provide a simple method to keep microgrids stable -- a topic of growing interest as resilience to energy disruptions gains prominence. VOC may also provide a means to transition power grids from today's inertia-dominated systems to systems that do not rely on rotating machinery.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Cooperative Transmission Expansion Planning Experiment Data and Results

GO WEST is an open-source power grid modeling framework for U.S. Western Interconnection, which allows users to tailor the model depending on their research study and science questions. It covers 28 balancing authorities (BA) and 12 states in U.S. Western Interconnection. GO WEST allows users to select different number of nodes and come up with a simplified network by utilizing 10,000 nodal topology of U.S. Western Interconnection created by Texas A&M University. Users can try and select different number of nodes, mathematical formulations (linear programming vs. mixed-integer linear programming), transmission line limit scaling factors, and hurdle rate scaling factors. GO WEST offers a unit commitment and economic dispatch (UC/ED) module to simulate grid operations on an hourly scale. In this sense, users can calibrate and validate their model versions by comparing model outputs to historical datasets. TEP is an open-source transmission capacity expansion model, built on GO WEST framework. It utilizes linear programming to optimize transmission capacity addition investment on existing lines within GO WEST framework. In this sense, TEP model only increases the thermal capacity of existing transmission lines and does not add new lines to the system, which leaves the topology preserved. TEP minimizes the total cost of the system which comprises the operational cost of satisfying electricity demand (i.e., generation cost), cost of loss of load (i.e., unserved energy), cost of power flow, and cost of new transmission capacity additions (i.e., investment cost). In order to use TEP model, users need to create scenarios with GO WEST framework. In this analysis, outputs from several models are used to create future inputs to GO WEST and TEP models, including GCAM-USA, TELL, CERF and reV. This dataset includes experiment inputs and outputs from three different transmission expansion scenarios (cooperative, intermediate, and individual) for 2019 and 2059. For 2019, a base scenario to illustrate the default (i.e., historical) power grid operations is also included. This study utilizes rcp45hotter_ssp3 scenario from a previous version of GCAM-USA simulations. Sources of the shapefiles in supplementary data are HIFLD Open and U.S. Energy Atlas. Please see the README file for a detailed description of the main and supplementary data.

Capacity Expansion Model↗
DOE OSTI2024

A valuation framework for customers impacted by extreme temperature-related outages

Extreme temperature outages can lead to not just economic losses but also various non-energy impacts (NEI), such as increased mortality rates, property damage, and reduced productivity, due to significant degradation of indoor operating conditions caused by service disruptions. However, existing resilience assessment approaches lack specificity for extreme temperature conditions. They often overlook temperature-related mortality and neglect the customer characteristics and grid response in the calculation, despite the significant influence of these factors on NEI-related economic losses. This paper aims to address these gaps by introducing a comprehensive framework to estimate the impact of resilience enhancement not only on the direct economic losses incurred by customers but also on potential NEI, including mortality and the value of statistical life during extreme temperature-related outages. The proposed resilience valuation integrates customer characteristics and grid response variables based on a scalable grid simulation environment. This study adopts a holistic approach to quantify customer-oriented economic impacts, utilizing probabilistic loss scenarios that incorporate health-related factors and damage/loss models as a function of exposure for valuation. The proposed methodology is demonstrated through comparative resilient outage planning, using grid response models emulating a Texas weather zone during the 2021 winter storm Uri. The case study results show that enhanced outage planning with hardened infrastructure can improve the system resilience and thereby reduce the relative risk of mortality by 16% and save the total costs related to non-energy impacts by 74%. In conclusion, these findings underscore the efficacy of the framework by assessing the financial implications of each case, providing valuable insights for decision-makers and stakeholders involved in extreme-weather related resilience planning for risk management and mitigation strategies.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Geologic Carbon Storage of Anthropogenic CO2 under the Colorado Plateau in Emery County, Utah

Geologic Carbon Storage (GCS) is a promising technology for storing large volumes of anthropogenic CO2 effectively and permanently. Numerical simulations are an integral part of site selection and characterization for any potential GCS site. As part of the DOE-funded CarbonSAFE Rocky Mountains Phase I project, a regional GCS analysis was undertaken to understand the efficacy of storing CO2 emissions from the power generation and heavy industry in central Utah’s favorable geology. In this study, the injection of CO2 for geologic storage was simulated in the Navajo Sandstone Formation in Emery County, Utah. Carbon dioxide was sourced from regional power generation stations and heavy industries throughout Utah, with an emphasis on emissions reduction at the Hunter Power Plant near Castle Dale, Utah. A simulation grid was extracted from the project’s geological model encompassing an area around Price, Huntington, and Castle Dale in central Utah. The Navajo Sandstone Member of the Glen Canyon Group was the target of CO2 injection with the overlying Carmel formation providing the primary seal. A suite of simulations was performed assessing the viability of this area for permanent CO2 storage. Results indicate that the area can not only store 46 million metric tons of anthropogenic CO2, meeting the project goals, but this area has the capacity to securely store at least 1.3 billion tons of CO2, suggesting the injection site and surrounding geology are suitable locations for commercial-scale GCS.

58 GEOSCIENCES↗
DOE OSTI2014

A Runtime Verification Framework for Control System Simulation

n a standard workflow for the validation of a control system, the control system is implemented as an extension to a simulator. Such simulators are complex software systems, and engineers may unknowingly violate constraints a simulator places on extensions. As such, errors may be introduced in the implementation of either the control system or the simulator leading to invalid simulation results. This paper presents a novel runtime verification approach for verifying control system implementations within simulators. The major contribution of the approach is the two-tier specification process. In the first tier, engineers model constraints using a domain-specific language tailored to modeling a controller’s response to changes in its input. The language is high-level and effectively hides the implementation details of the simulator, allowing engineers to specify design-level constraints independent of low-level simulator interfaces. In the second tier, simulator developers provide mapping rules for mapping design-level constraints to the implementation of the simulator. Using the rules, an automated tool transforms the design-level specifications into simulator-specific runtime verification specifications and generates monitoring code which is injected into the implementation of the simulator. During simulation, these monitors observe the input and output variables of the control system and report changes to the verifier. The verifier checks whether these changes follow the constraints of the control system. We describe application of this approach to the verification of the constraints of an HVAC control system implemented with the power grid simulator GridLAB-D.

control system↗
DOE OSTI2022

How will United States commercial building energy use be impacted by IPCC climate scenarios?

Climate change and anthropogenically-forced shift of weather in the future will impact energy use and resilience of both the built environment and the electric grid. The aim of this analysis is to understand how future climate scenarios will impact electricity and natural gas use of commercial buildings in the United States. Here, this study analyzes this impact for 2030, 2045, and 2100 using Representative Concentration Pathways (RCP) scenarios defined in Intergovernmental Panel on Climate Change (IPCC) Assessment Report 5. The large, gridded simulation of meteorological variables for RCPs 2.6, 4.5, 6.0, and 8.5 are selected and downscaled to make available hourly Future Meteorological Year (FMY) weather files for use and improvement in subsequent studies. High performance computing resources use these FMYs to simulate commercial prototype buildings in every American Society of Heating, Refrigeration, and Air Conditioning Engineers (ASHRAE) climate zone of the United States (US), and results are scaled to nation-wide energy use using conditioned floor area multipliers. The analysis is conducted without speculating the physical and performance traits of future buildings or the grid characteristics. This analysis quantifies the impact of climate change on source electrical and natural gas usage for commercial buildings in the United States over the next 80 years. If US commercial floorspace remained constant, total energy use by 2100 is predicted between an 1.75% decrease under the greatest emission scenario (8.5) and a 1.76% increase under the lowest emission scenario (2.6). When adjusted for anticipated urban growth by 2100, the predicted range is 65% increase (8.5) and 71% increase (2.6). Under a global temperature rise climate scenario, the warmest US climate zones will see a large increases in electricity use derived from space cooling while the coldest US climate zones will see significant decreases in natural gas use caused by the decrease in heating necessary. While climate change may ultimately require adaptations of the built environment to withstand its effects and because the United States is a country that requires more heating than cooling, from a building energy perspective, climate change (average temperature rise) is a net energy saver for the United States.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Stringent σ8 constraints from small-scale galaxy clustering using a hybrid MCMC + emulator framework

ABSTRACT We present a novel simulation-based hybrid emulator approach that maximally derives cosmological and Halo Occupation Distribution (HOD) information from non-linear galaxy clustering, with sufficient precision for DESI Year 1 (Y1) analysis. Our hybrid approach first samples the HOD space on a fixed cosmological simulation grid to constrain the high-likelihood region of cosmology + HOD parameter space, and then constructs the emulator within this constrained region. This approach significantly reduces the parameter volume emulated over, thus achieving much smaller emulator errors with fixed number of training points. We demonstrate that this combined with state-of-the-art simulations result in tight emulator errors comparable to expected DESI Y1 LRG sample variance. We leverage the new abacussummit simulations and apply our hybrid approach to CMASS non-linear galaxy clustering data. We infer constraints on σ8 = 0.762 ± 0.024 and fσ8(zeff = 0.52) = 0.444 ± 0.016, the tightest among contemporary galaxy clustering studies. We also demonstrate that our fσ8 constraint is robust against secondary biases and other HOD model choices, a critical first step towards showcasing the robust cosmology information accessible in non-linear scales. We speculate that the additional statistical power of DESI Y1 should tighten the growth rate constraints by at least another 50–60 ${{\ \rm per\ cent}}$, significantly elucidating any potential tension with Planck. We also address the ‘lensing is low’ tension, which we find to be in the same direction as a potential tension in fσ8. We show that the combined effect of a lower fσ8 and environment-based bias accounts for approximately $50{{\ \rm per\ cent}}$ of the discrepancy.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Bus.py

GridLAB-D is an agent? based distribution system simulation environment that allows fine-grained end-user models, including geospatial and network topology detail. GridLAB-D addresses the lack of runtime interaction by designing a flexible communication interface, Bus.py (pronounced bus-dot-pie), that uses Python to pass messages between one or more GridLAB-D instances and a Smart Grid simulator.

Hansen, Timothy↗
DOE OSTI2016

RAY-RAMSES: a code for ray tracing on the fly in N-body simulations

We present a ray tracing code to compute integrated cosmological observables on the fly in AMR N-body simulations. Unlike conventional ray tracing techniques, our code takes full advantage of the time and spatial resolution attained by the N-body simulation by computing the integrals along the line of sight on a cell-by-cell basis through the AMR simulation grid. Moroever, since it runs on the fly in the N-body run, our code can produce maps of the desired observables without storing large (or any) amounts of data for post-processing. We implemented our routines in the RAMSES N-body code and tested the implementation using an example of weak lensing simulation. We analyse basic statistics of lensing convergence maps and find good agreement with semi-analytical methods. The ray tracing methodology presented here can be used in several cosmological analysis such as Sunyaev-Zel'dovich and integrated Sachs-Wolfe effect studies as well as modified gravity. Our code can also be used in cross-checks of the more conventional methods, which can be important in tests of theory systematics in preparation for upcoming large scale structure surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

A Testbed Environment for Buildings-to-Grid Cyber Resilience Research and Development

The Smart Grid is characterized by the proliferation of advanced digital controllers at all levels of its operational hierarchy from generation to end consumption. Such controllers within modern residential and commercial buildings enable grid operators to exercise fine-grained control over energy consumption through several emerging Buildings-to-Grid (B2G) applications. Though this capability promises significant benefits in terms of operational economics and improved reliability, cybersecurity weaknesses in the supporting infrastructure could be exploited to cause a detrimental effect and this necessitates focused research efforts on two fronts. First, the understanding of how cyber attacks in the B2G space could impact grid reliability and to what extent. Second, the development and validation of cyber-physical application-specific countermeasures that are complementary to traditional infrastructure cybersecurity mechanisms for enhanced cyber attack detection and mitigation. The PNNL B2G testbed is currently being developed to address these core research needs. Specifically, the B2G testbed combines high-fidelity buildings+grid simulators, industry-grade building automation and Supervisory Control and Data Acquisition (SCADA) systems in an integrated, realistic, and reconfigurable environment capable of supporting attack-impact-detection-mitigation experimentation. In this paper, we articulate the need for research testbeds to model various B2G applications broadly by looking at the end-to-end operational hierarchy of the Smart Grid. Finally, the paper not only describes the architecture of the B2G testbed in detail, but also addresses the broad spectrum of B2G resilience research it is capable of supporting based on the smart grid operational hierarchy identified earlier.

Sridhar, Siddharth↗
DOE OSTI2013

Western Wind and Solar Integration Study Phase 2

The electric grid is a highly complex, interconnected machine, and changing one part of the grid can have consequences elsewhere. Adding wind and solar affects the operation of the other power plants and adding high penetrations can induce cycling of fossil-fueled generators. Cycling leads to wear-and-tear costs and changes in emissions. Phase 2 of the Western Wind and Solar Integration Study(WWSIS-2) evaluated these costs and emissions and simulated grid operations for a year to investigate the detailed impact of wind and solar on the fossil-fueled fleet. This built on Phase 1, one of the largest wind and solar integration studies ever conducted, which examined operational impacts of high wind and solar penetrations in the West.

14 SOLAR ENERGY↗
DOE OSTI2013

The Western Wind and Solar Integration Study Phase 2

The electric grid is a highly complex, interconnected machine, and changing one part of the grid can have consequences elsewhere. Adding wind and solar affects the operation of the other power plants and adding high penetrations can induce cycling of fossil-fueled generators. Cycling leads to wear-and-tear costs and changes in emissions. Phase 2 of the Western Wind and Solar Integration Study (WWSIS-2) evaluated these costs and emissions and simulated grid operations for a year to investigate the detailed impact of wind and solar on the fossil-fueled fleet. This built on Phase 1, one of the largest wind and solar integration studies ever conducted, which examined operational impacts of high wind and solar penetrations in the West(GE Energy 2010).

14 SOLAR ENERGY↗
DOE OSTI2013

The Western Wind and Solar Integration Study Phase 2 (Executive Summary)

The electric grid is a highly complex, interconnected machine, and changing one part of the grid can have consequences elsewhere. Adding wind and solar affects the operation of the other power plants and adding high penetrations can induce cycling of fossil-fueled generators. Cycling leads to wear-and-tear costs and changes in emissions. Phase 2 of the Western Wind and Solar Integration Study (WWSIS-2) evaluated these costs and emissions and simulated grid operations for a year to investigate the detailed impact of wind and solar on the fossil-fueled fleet. This built on Phase 1, one of the largest wind and solar integration studies ever conducted, which examined operational impacts of high wind and solar penetrations in the West(GE Energy 2010).

14 SOLAR ENERGY↗
DOE OSTI2020

Data-Enhanced Hierarchical Control to Improve Distribution Voltage with Extremely High PV Penetration

Dynamic, scalable, and interoperable control paradigms are required to enable efficient, secure, reliable, and resilient distribution grid operations with widespread grid integration of renewable energy resources. This paper presents our recent research on developing a novel, holistic, data-enhanced hierarchical control architecture that addresses the formidable challenges faced by emerging distribution grids with increasing penetrations of distributed energy resources. The proposed architecture integrates centralized monitoring and control with distributed grid-edge control and thus effectively deals with multi-spatiotemporal dynamics existing in the grid. Simulation results are provided to demonstrate the effectiveness of the proposed control architecture.

14 SOLAR ENERGY↗
DOE OSTI2019

Data Enhanced Hierarchical Control to Improve Distribution Voltage with Extremely High PV Penetration: Preprint

Dynamic, scalable and interoperable control paradigm is required to enable efficient, secure, reliable and resilient distribution grid operations with widespread grid integration of renewable energy resources. This paper presents our recent research work on developing a novel, holistic, data enhanced hierarchical control architecture that addresses the formidable challenges faced by emerging distribution grids with increasing penetrations of distributed energy resources. The proposed architecture integrates centralized monitoring and control together with distributed grid edge control, and thus effectively deals with multi-spatiotemporal dynamics existing in the grid. Simulation results are provided to demonstrate the effectiveness of the proposed control architecture.

14 SOLAR ENERGY↗