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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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NASA NTRS1979

Concepts for 18/30 GHz satellite communication system study. Executive summary

An examination of a multiplicity of interconnected parameters ranging from specific technology details to total system economic costs for satellite communication systems at the 18/30 GHz transmission bands are presented. It was determined that K sub A band systems can incur a small communications outage during very heavy rainfall periods and that reducing the outage to zero would lead to prohibitive system costs. On the other hand, the economics of scale, ie, one spacecraft accommodating 2.5 GHz of bandwidth coupled with multiple beam frequency reuse, leads to very low costs for those users who can tolerate the 5 to 50 hours per year of downtime. A multiple frequency band satellite network can provide the ultimate optimized match to the consumer performance/economics demands.

Baker, M.↗

DOE OSTI2023

Base Station Antenna Uptilt Optimization for Cellular-Connected Drone Corridors

Reliable wireless coverage in drone corridors is critical to enable a connected, safe, and secure airspace. To support beyond visual line of sight (BVLOS) operations of aerial vehicles in a drone corridor, cellular base stations (BSs) can serve as a convenient infrastructure as they are widely deployed to provide seamless wireless coverage. However, antennas in the existing cellular networks are down-tilted to optimally serve their ground users, which results in coverage holes at higher altitudes when they are used to serve drones. In this paper, we consider the use of additional uptilted antennas at each cellular BS and optimize the uptilt angle to maximize the wireless coverage probability across a given drone corridor. Through numerical results, we can characterize the optimal value of the antenna uptilt angle for a given antenna pattern as well as the minimum/maximum altitudes of the drone corridor.

42 ENGINEERING↗

DOE OSTI2022

Dynamics Informed Optimization for Resilient Energy Systems

Optimal mitigation planning for highly disruptive contingencies to a transmission-level power system requires optimization with dynamic power system constraints, due to the key role of dynamics in system stability to major perturbations. We formulate a generalized disjunctive program to determine optimal grid component hardening choices for protecting against major failures, with differential algebraic constraints representing system dynamics (specifically, differential equations representing generator and load behavior and algebraic equations representing instantaneous power balance over the transmission system). We optionally allow stochastic optimal pre-positioning across all considered failure scenarios, and optimal emergency control within each scenario. This novel formulation allows, for the first time, analyzing the resilience interdependencies of mitigation planning, preventive control, and emergency control. Using all three strategies in concert is particularly effective at maintaining robust power system operation under severe contingencies, as we demonstrate on the Western System Coordinating Council (WSCC) 9-bus test system using synthetic multi-device outage scenarios. Towards integrating our modeling framework with real threats and more realistic power systems, we explore applying hybrid dynamics to power systems. Our work is applied to basic RL circuits with the ultimate goal of using the methodology to model protective tripping schemes in the grid. Finally, we survey mitigation techniques for HEMP threats and describe a GIS application developed to create threat scenarios in a grid with geographic detail.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Robust Restoration From Cyber-Physical Attacks in Active Distribution Grids With Grid-Edge IBRs

The inverter-based resources (IBRs) have enabled the integration of renewable energy at the grid edge with enhanced control capabilities to support the reliable operation of power grids. Different control frameworks, such as hierarchical or distributed architecture, have been proposed with the expansion of cyber networks for real-time monitoring and control. This evolution of critical infrastructure into cyber-physical systems also brings more vulnerabilities for the broadened attack surfaces, and significantly increases the possibility of physical system failures or outages caused by cyberattacks. Among tremendous efforts in the defense-in-depth approach, it remains challenging to provide prompt detection and accurate location of attack entry points or paths. Therefore, the prevailing restoration framework may struggle to fully consider the cyber-physical interdependence, successfully isolate the compromised cyber and physical components, and safely recover the systems without the potential risks leading to secondary outages. This paper is motivated to develop a cyber-physical restoration framework for distribution grids to recover from cyber attacks by harnessing grid-edge IBRs. The framework is first built on the operational guidelines of IBRs considering the compromised cyber layer. Then, an ambiguity set is established to represent the uncertainty of attack scenarios and their possibility levels. Next, a distributionally robust optimization model is developed to provide the optimal load restoration strategy across all scenarios. The effectiveness of the proposed model is demonstrated through various use cases on the modified IEEE 13-node and 123-node test systems. Finally, simulation results demonstrate the effectiveness and advancement of developed post-attack restoration strategies.

Cybersecurity↗

DOE OSTI2020

Smart-DS: Synthetic Models for Advanced, Realistic Testing: Distribution Systems and Scenarios

The explosion of new ideas for distributed energy resources and advanced distribution grid algorithms faces a critical challenge: how can one effectively develop and evaluate these breakthrough technologies without an adequate set of power systems network, load, and resource data to test against? Today's open test systems, particularly for distribution systems, are tiny and incomplete; and though with enough effort, obtaining utility data under NDA can overcome scale challenges, the results can't be openly shared, preventing fair comparison. The Smart-DS project-led by NREL in partnership with MIT, Universidad Pontificia Comillas, CYME, and EDD-is working to overcome this gap by generating multiple large-scale, open, synthetic, distribution systems that are realistic but not real. These datasets go beyond a single medium voltage feeder (~1000 customers) to cover entire metropolitan areas and their surrounds with up to hundreds of feeders and millions of customers, complete with low voltage customer connections and high voltage sub-transmission. This scale allows adequate testing and analysis of not just local controls and advanced DERs, but also multiple substation interactions, optimized switching, full-scale distribution-OPF, and more. To accompany these datasets, the project is also building a rich set of scenario generation tools that can be used for distribution and transmission systems alike. This includes automated, spatially aware access to world-class, high-resolution solar, wind, and weather data: forward looking generation mixes: and highly configurable DER, load, climate, outage, control-scheme, and other scenarios. We will also highlight DiTTo, an exciting open-source, multi-way distribution dataset transformation tool for many-to-many format translation with scenario, merge/split, and many other manipulation capabilities.

DERs↗

NASA NTRS2018

Optimization of Second Fault Detection Thresholds to Maximize Mission POS

In order to support manned spaceflight safety requirements, the Space Launch System (SLS) has defined program-level requirements for key systems to ensure successful operation under single fault conditions. To accommodate this with regards to Navigation, the SLS utilizes an internally redundant Inertial Navigation System (INS) with built-in capability to detect, isolate, and recover from first failure conditions and still maintain adherence to performance requirements. The unit utilizes multiple hardware- and software-level techniques to enable detection, isolation, and recovery from these events in terms of its built-in Fault Detection, Isolation, and Recovery (FDIR) algorithms. Successful operation is defined in terms of sufficient navigation accuracy at insertion while operating under worst case single sensor outages (gyroscope and accelerometer faults at launch). In addition to first fault detection and recovery, the SLS program has also levied requirements relating to the capability of the INS to detect a second fault, tracking any unacceptable uncertainty in knowledge of the vehicle's state. This detection functionality is required in order to feed abort analysis and ensure crew safety. Increases in navigation state error and sensor faults can drive the vehicle outside of its operational as-designed environments and outside of its performance envelope causing loss of mission, or worse, loss of crew. The criteria for operation under second faults allows for a larger set of achievable missions in terms of potential fault conditions, due to the INS operating at the edge of its capability. As this performance is defined and controlled at the vehicle level, it allows for the use of system level margins to increase probability of mission success on the operational edges of the design space. Due to the implications of the vehicle response to abort conditions (such as a potentially failed INS), it is important to consider a wide range of failure scenarios in terms of both magnitude and time. As such, the Navigation team is taking advantage of the INS's capability to schedule and change fault detection thresholds in flight. These values are optimized along a nominal trajectory in order to maximize probability of mission success, and reducing the probability of false positives (defined as when the INS would report a second fault condition resulting in loss of mission, but the vehicle would still meet insertion requirements within system-level margins). This paper will describe an optimization approach using Genetic Algorithms to tune the threshold parameters to maximize vehicle resilience to second fault events as a function of potential fault magnitude and time of fault over an ascent mission profile. The analysis approach, and performance assessment of the results will be presented to demonstrate the applicability of this process to second fault detection to maximize mission probability of success.

Anzalone, Evan↗

NASA NTRSDate not supplied

Ray Tracing Techniques for the Characterization of Lunar Communication Architectures

This paper provides an overview of the computational techniques used to characterize the viability of different lunar architectures and their ability to provide communication services to the lunar surface. This analysis was done with modern ray tracing techniques that allow for the computations to be done on Graphics Processing Unit (GPU) clusters for a high level of parallelism and severe reduction in computation time. The ray tracing computations were done with the GPU platform Compute Unified Device Architecture (CUDA) provided by NVIDIA which utilizes general-purpose computing on graphics processing units (GPGPU). This new method provides the advantage of being able to characterize a much larger portion of the lunar surface due to its computational efficiency as well as providing a more accurate representation of elevation angle limits instead of the typical and often inaccurate elevation angle mask. The Lunar surface can now be characterized with metrics such as contact time, outage time, and received data rate. With these metrics, different proposed Lunar architectures can be rapidly evaluated. This reduction in computation time not only leads to more accurate results but allows these results to be obtained in a time frame that allows for the complete characterization of the trade space. It is expected that these different architecture comparisons will lead to a conclusive determination of the optimal Lunar architecture and will allow for future Lunar missions to operate as close to real time as possible. In addition, this computation method can be used to recreate visibility figures generated by previous methods but with an increased level of accuracy.

Thomas Montano↗

DOE OSTI2024

Assessing the Reliability Benefits of Energy Storage as a Transmission Asset

Utilizing energy storage solutions to reduce the need for traditional transmission investments has been recognized by system planners and supported by federal policies in recent years. This work demonstrates the need for detailed reliability assessment for quantitative comparison of the reliability benefits of energy storage and traditional transmission investments. First, a mixed-integer linear programming expansion planning model considering candidate transmission lines and storage technologies is solved to find the least-cost investment decisions. Next, operations under the resulting system configuration are simulated in a probabilistic reliability assessment which accounts for weather-dependent forced outages. The outcome of this work, when applied to TPPs, is to further equalize the consideration of energy storage compared to traditional transmission assets by capturing the value of storage for system reliability.

co-optimization↗

DOE OSTI2024

Cooperation in Transmission Expansion Planning: Enhancing Grid Reliability and Efficiency Under a Changing Climate

Electricity grids are challenged to maintain reliability during more intense and frequent extreme weather events due to climate change. This challenge is exacerbated by multi-sector electrification and power sector decarbonization through increased reliance on variable renewable energy, which necessitates the expansion of transmission infrastructure. However, transmission expansion planning is often complicated by intertwined planning authorities and jurisdictions, and allocation of large capital investment needs. These factors cause authorities to manage transmission investments individually (i.e., only/mostly intraregional planning), which can lead to suboptimal transmission networks. This study investigates the potential benefits of cooperative transmission expansion planning (i.e., both intraregional and interregional planning that optimizes transmission investments across the entire physical system). Using sectoral and economic optimization, and machine learning models, it analyzes the impact of different levels of cooperation among transmission planning regions within U.S. Western Interconnection in 2019 and 2059 via an iterative investment process. Furthermore, it examines the effects of future climate change on transmission cooperation by simulating historical heat waves from 2019 under conditions of 2059. The results indicate that cooperative transmission planning leads to lower wholesale electricity prices, decreased energy outages, and reduced greenhouse gas emissions. However, the advantages of collaboration diminish during widespread heat waves, despite remaining beneficial especially for regions like California Independent System Operator with substantial solar installations. The study underscores the importance of transmission cooperation in reducing costs and enhancing reliability, emphasizing the need for strategic investments in storage to address challenges posed by future extreme weather events with varying spatial scales.

Capacity Expansion Model↗

DOE OSTI2025

Quantifying and Optimizing the Energy Benefits of Mass Timber Construction

The International Mass Timber Alliance (IMTA) is a global organization of industry leaders, engineers, scientists, and associations dedicated to advancing mass timber construction. Its mission is to generate and disseminate scientific data supporting the development of standardized construction and energy efficient practices that promote the adoption of mass timber worldwide. IMTA collaborated with Oak Ridge National Laboratory (ORNL) to leverage ORNL’s expertise in building envelope modeling and testing to evaluate how mass timber construction can reduce peak heating and cooling demand, lower overall energy use, and improve resilience during power outages. A previous study of 80 mass timber buildings in Finland found measured energy use up to 50% lower than predicted by simulation. This project aimed to validate and extend those findings for U.S. buildings through analytical modeling, laboratory testing, and full-scale building evaluations. The research focused on the thermal performance of low-embodied-energy wall assemblies, such as cross-laminated timber (CLT) panels and log walls, with particular attention to the effects of thermal inertia on indoor comfort and energy performance. While mass timber’s structural and fire-resistance properties are well documented, its whole-building thermal behavior has received limited attention. Field data, simulation results, and resilience testing from this study will inform future modeling practices, design guidelines, and construction practices by quantifying the unique thermal and demand-flexibility benefits of mass timber construction.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

Preliminary Analysis of Nuclear-Powered Data Center Scenarios

This report provides a comprehensive analysis of the potential for nuclear energy to meet the growing energy demands of data centers (DCs). It evaluates the technical, economic, and socio-environmental implications of coupling Nuclear Power Plants (NPPs) with DCs, providing initial responses to several key research questions: What is the potential increased energy demand from DCs in the U.S., in the short, medium and long term? The U.S. is experiencing a rapid increase in energy demand from DCs, with projections indicating a total increase of 24-74 GWy(e) by 2028. Meeting this demand with nuclear energy would require 27–85 GWe of installed capacity. While this surge is expected to slow in the long term, the DC industry needs reliable, scalable, and clean energy sources. How much nuclear capacity can be deployed to meet DC demand and in which timeframe? Several pathways for increasing nuclear capacity were identified, including uprates, restarts of recently retired reactors, power purchase agreements with existing fleet, and new construction. Approximately 20‒28 GWe of nuclear capacity could be dedicated to DCs by the early 2030s. How much High Assay Low Enriched Uranium (HALEU) would be needed to support some nuclear deployment scenarios for DCs? Meeting the deployment targets announced by Google and Amazon for the Kairos Power Fluoride-Salt-Cooled High-Temperature Reactor or KP-FHR (~500 MWe by 2035) and the Xe-100 (~1 GWe by 2040), respectively, requires ramping up 19.75% enriched HALEU production to ~6 t/yr by 2040. What types of nuclear energy/DC coupling options exist, and what are the different benefits/challenges? Five coupling options were analyzed, ranging from grid-connected configurations to colocated, behind-the-meter setups. Key design considerations include the proximity to high- and/or medium-voltage transmission lines, the desired internal fault tolerance, and the sources of alternative/backup power during outages. Each coupling option offers unique benefits and challenges in terms of reliability, system costs, regulation, timeline, etc. A list of NPP/DC deployment scenarios was developed, considering existing or newly built NPP or DC projects. Colocated DCs with new small modular reactors or large reactors on greenfield and brownfield sites are the focus of this report. What types of reactors, especially what size, may be incentivized by DCs? Reactor sizing optimization revealed that the ideal reactor size and number of units depend on DC demand, coupling configurations defined in this report, and other economic factors. Larger reactors are preferred for high-demand DCs and grid-connected systems, while larger number of smaller reactors are better suited for DC configurations without grid backup. Which sites may be compatible with co-located nuclear-powered DCs? Siting those projects is a complicated evaluation factoring local water resources, grid connection availability and reliability, IT infrastructure, local work force, proximity to population zones, etc. For this effort greenfield and brownfield sites such as retired coal-fired plants were used to evaluate this question. This evaluation is not meant to recommend any particular site but it highlights key siting criteria and demonstrates large-scale site availability. What are the socio-economic impacts of co-located nuclear-powered DCs? Those projects generate substantial economic benefits to the local economy, particularly in urban settings. Hyperscale DCs colocated with nuclear power plants (sized around 1 GW of power) can create nearly 1,700 jobs for annual operations and more than 7,300 jobs among the supply chain and local businesses as a result of increased household spending. Rural projects also provide significant benefits, but at lower magnitudes compared to urban deployments.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRS1997

Predictive Attitude Estimation Using Global Positioning System Signals

In this paper, a new algorithm is developed for attitude estimation using Global Positioning System (GPS) signals. The new algorithm is based on a predictive filtering scheme designed for spacecraft without rate measuring devices. The major advantage of this new algorithm over traditional Kalman filter approaches is that the model error is not assumed to represented by an unbiased Gaussian noise process with known covariance, but instead is determined during the estimation process. This is achieved by simultaneously solving system optimality conditions and an output error constraint. This approach is well suited for GPS attitude estimation since some error sources that contribute to attitude inaccuracy, such as signal multipath, are known to be non-Gaussian processes. Also, the predictive filter scheme can use either GPS signals or vector observations or a combination of both for attitude estimation, so that performance characteristics can be maintained during periods of GPS attitude sensor outage. The performance of the new algorithm is tested using flight data from the REX-2 spacecraft. Results are shown using the predictive filter to estimate the attitude from both GPS signals and magnetometer measurements, and comparing that solution to a magnetometer-only based solution. Results using the new estimation algorithm indicate that GPS-based solutions are verified to within 2 degrees using the magnetometer cross-check for the REX-2 spacecraft. GPS attitude accuracy of better than 1 degree is expected per axis, but cannot be reliably proven due to inaccuracies in the magnetic field model.

Crassidis, John L.↗

DOE OSTI2023

A Distributionally Robust Resilience Enhancement Strategy for Distribution Networks Considering Decision-Dependent Contingencies

When performing the resilience enhancement for distribution networks, there are two obstacles to reliably model the uncertain contingencies: 1) decision-dependent uncertainty (DDU) due to various line hardening decisions, and 2) distributional ambiguity due to limited outage information during extreme weather events (EWEs). Here, to address these two challenges, this paper develops scenario-wise decision-dependent ambiguity sets (SWDD-ASs), where the DDU and distributional ambiguity inherent in EWE-induced contingencies are simultaneously captured for each possible EWE scenario. Then, a two-stage tri-level decision-dependent distributionally robust resilient enhancement (DD-DRRE) model is formulated, whose outputs include the optimal line hardening, distributed generation (DG) allocation, and proactive network reconfiguration strategy under the worst-case distributions in SWDD-ASs. Subsequently, the DD-DRRE model is equivalently recast to a mixed-integer linear programming (MILP)-based master problem and multiple scenario-wise subproblems, facilitating the adoption of a customized column-and-constraint generation (C&CG) algorithm. Finally, case studies demonstrate a remarkable improvement in the out-of-sample performance of our model, compared to its prevailing stochastic and robust counterparts. Moreover, the potential values of incorporating the ambiguity and distributional information are quantitatively estimated, providing a useful reference for planners with different budgets and risk-aversion levels.

decision-dependent uncertainty↗

DOE OSTI2022

Techno-Economic Analysis Using REopt for Community Solar on Multifamily Affordable Housing Properties [Slides]

Multifamily affordable housing (MFAH) providers can identify and prioritize properties in their portfolios for which community solar development is feasible by following portfolio screening steps in a process outlined by NREL. Once MFAH providers have identified the most feasible sites, they can conduct more detailed analyses for a select number of sites to assess how distributed energy resources such as solar plus storage can help them meet their goals. The step is completed using NREL's REopt (https://reopt.nrel.gov/tool), a free techno-economic optimization model that determines DER sizes and dispatch strategies that minimize the life cycle cost of energy at a site. This presentation describes how to perform this step using REopt to help MFAH providers answer questions such as: What size solar PV system will result in the most energy bill savings at this site? What size solar-plus-storage system would be needed to power critical loads through a utility grid outage? What is the financial impact of rate switching, net metering, and/or meter aggregation? What percentage of the site's load can be offset with renewable energy? What are the emissions benefits of this renewable generation?

14 SOLAR ENERGY↗

DOE OSTI2025

Core design and performance of the Westinghouse lead fast reactor with UO 2 and MOX configurations

For this work, Westinghouse partnered with Argonne National Laboratory to design, model and optimize UO 2 - and MOX-fueled core designs for a medium size (950 MWt) Lead Fast Reactor that was pursued by Westinghouse. Using Argonne’s suite of reactor analysis codes together with Westinghouse fuel cost economic models, thousands of candidate cores were considered to achieve the economics-optimized cores presented in this paper. This optimization process considered detailed reactor physics, fuel performance, transient performance, and fuel economics models. The reactor performance of the resulting optimized UO 2 - and MOX-fueled core designs are described and compared in this paper. Both cores show fuel performance and transient behavior that is considered acceptable for the optimization presented herein, while further testing campaigns on material performance in high-temperature liquid lead will be required to confirm acceptability at the operating conditions chosen. A multi-batch strategy was selected for the UO 2 core for best fuel utilization with minimum fuel inventory costs. A single-batch fuel management was instead selected for the MOX core to maximize cycle length and minimize the impact of the longer refueling outage resulting from the higher decay heat of the discharged MOX fuel relative to the discharged UO 2 fuel, requiring a longer cooling time before dry-lift of discharged fuel could take place.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2024

Evaluating Utility Costs Savings and Resilience: A Case Study in Port Arthur, Texas

This study evaluates the techno-economic feasibility of integrating solar photovoltaics (PV), battery energy storage systems (BESS), and generators to enhance both cost savings and resilience in critical community facilities in Port Arthur, Texas. Using NREL's REopt model, we analyze four facilities: the Golden Triangle Empowerment Center (GTEC), Lamar State College (LSC), Port Arthur Independent School District (PAISD), and Port Arthur Transit (PAT). A key aspect of the analysis is the incorporation of the Value of Lost Load (VoLL) and microgrid upgrade costs to assess the hidden value of resilience during grid outages. While standalone PV scenarios show moderate cost reductions and a 10-15% decrease in CO2 emissions, the inclusion of resilience measures with BESS and generators significantly increases system costs. However, the hidden value of resilience - quantified through avoided outage costs - leads to a substantial improvement in financial outcomes, resulting in positive Net Present Value (NPV) at many sites. The study demonstrates that resilient solar and storage systems offer both economic and resilience benefits, particularly for underserved communities, by balancing energy savings and enhanced operational continuity during outages.

14 SOLAR ENERGY↗

DOE OSTI2026

Impacts of Regional Coordination on Transmission Needs for Power System Resource Adequacy [Slides]

Resource adequacy (RA) is an important component of bulk power system reliability that addresses whether there are sufficient resources available to meet electricity demand at all times. RA analysis is used to assess whether the planned power system will provide reliable electricity to consumers while accounting for equipment outages, weather variability, and load uncertainty. Coordination between regions can enable resource sharing to meet RA needs if sufficient transmission capacity exists. Transmission's role in RA coordination can be particularly pronounced for large power systems like the U.S. electricity grid which contains geographically diverse demand and weather-dependent resources. Depending on the level of coordination desired, existing inter-regional transmission capacity may not be sufficient. This study is designed to assess optimal pathways for the development of inter-regional transmission in the U.S. under varying levels of RA coordination. Results can inform long-term grid infrastructure planning and provide insights into potential benefits of greater coordination for generation and transmission planning between regional U.S. power systems.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NASA NTRS1990

Loop current eddy shedding estimated using Geosat altimeter data

A method for extracting periodic signals from altimeter data is applied in the Gulf of Mexico using data from the first two years of the Geosat Exact Repeat Mission. The least squares fitting of selected frequencies of sine and cosine functions to the time series of sea surface height at each point of the Geosat ground track is used to estimate the dominant frequency in the gulf for this time period. Optimal interpolation of the sine and cosine coefficients at the dominant frequency to a uniformly spaced grid allows reconstruction of the time series in the gulf and shows eddies shedding from the Loop Current with a period of approximately 10.5 months, consistent with shedding periods determined from numerical models and analysis of satellite infrared data. This technique is a novel method for investigation of periodic signals in Geosat altimetry and is not severely affected by the data outages present in the time series.

Jacobs, Gregg A.↗