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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 1,117 records · Page 62

Advanced Signal Decomposition Analysis and Anomaly Detection in Photovoltaic Systems

With the rapid expansion of large-scale photovoltaic (PV) plants, it is paramount for solar stakeholders to understand the reliability and efficiency of their plants to inform maintenance decisions, increase production, and understand the design factors that impact performance. Diagnosing underperformance in PV plants is challenging due to the relatively few monitoring points with respect to the large geographic footprint of the plant. This work introduces a cutting-edge method that transforms the analysis and management of key factors influencing PV plant performance, including performance loss rate (PLR), recoverable soiling, and major system changes. Identifying these factors is critical for deriving actionable insights. Leveraging advanced analytical techniques such as wavelet transformation, robust regression, and extreme point analysis, this approach provides a nuanced understanding of these factors. This method has been tested across two synthetic datasets and one real dataset, consistently surpassing existing benchmarks by achieving a lower median mean absolute error and reduced error variability across all comparable components.

14 SOLAR ENERGY↗

Link statistics of dislocation network during strain hardening

Dislocations are line defects in crystals that multiply and self-organize into a complex network during strain hardening. The length of dislocation links, connecting neighboring nodes within this network, contains crucial information about the evolving dislocation microstructure. By analyzing data from Discrete Dislocation Dynamics (DDD) simulations in face-centered cubic (fcc) Cu, we characterize the statistical distribution of link lengths of dislocation networks during strain hardening on individual slip systems. Here, our analysis reveals that link lengths on active slip systems follow a double-exponential distribution, while those on inactive slip systems conform to a single-exponential distribution. The distinctive long tail observed in the double-exponential distribution is attributed to the stress-induced bowing out of long links on active slip systems, a feature that disappears upon removal of the applied stress. We further demonstrate that both observed link length distributions can be explained by extending a one-dimensional Poisson process to include different growth functions. Specifically, the double-exponential distribution emerges when the growth rate for links exceeding a critical length becomes super-linear, which aligns with the physical phenomenon of long links bowing out under stress. This work advances our understanding of dislocation microstructure evolution during strain hardening and elucidates the underlying physical mechanisms governing its formation.

Crystal plasticity↗

Impacts of Dispatch Strategies and Forecast Errors on the Economics of Behind-the-Meter PV-Battery Systems

To assess the economic value of batteries in hybrid PV-battery systems, one must create a dispatch profile for the battery. Many analyses of battery value assume perfect forecasts of PV generation and load, determining an upper limit on the value of the battery. Prior work that accounts for forecast uncer- tainty often does so in the context of a single dispatch algorithm, which does not provide a baseline for comparison. Furthermore, when multiple dispatch algorithms are assessed with uncertainty, the benefits considered are for diesel generation in a microgrid, not retail rate savings. This work addresses the gaps in the literature by comparing the performance of both heuristic and optimal dispatch algorithms for retail rate savings under forecast uncertainty, and provides comparisons of the robustness of these algorithms and their associated estimates of economic value. We find that using a perfect forecast can overestimate the value of hybrid PV-battery systems between 1% and 8% compared to the reality of using a day-ahead forecast, depending on the dispatch algorithm used. Thus, accounting for forecast uncertainty in system design and analysis will significantly improve the accuracy of modeled system values.

batteries↗

Independent Analyses of Antares R1 Core Design

This report summarizes the reactor analysis work performed by Oak Ridge National Laboratory (ORNL) for Antares Nuclear Incorporated's R1 Mark-1 heat pipe reactor design. The work was performed under a collaboration through the Department of Energy GAIN Nuclear Energy Voucher program. The purpose of this work is to perform an independent reactor analysis of the Antares reactor design and, where possible, compare ORNL's results with the results obtained by Antares. The overarching goal is to provide Antares with an independent review and calculation of their design, thereby contributing to Antares' mission to further their reactor design concept. A report with all ORNL technical results and proprietary details was provided to Antares Nuclear Incorporated separately; the present report provides a summary of the work completed, and all proprietary information is omitted. The independent reactor analysis was performed using both the SCALE code system for neutronics analysis and Flownex for thermal hydraulics analysis.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Impacts of Dispatch Strategies and Forecast Errors on the Economics of Behind-the-Meter PV-Battery Systems

To assess the economic value of batteries in hybrid PV-battery systems, one must create a dispatch profile for the battery. Many analyses of battery value assume perfect forecasts of PV generation and load, determining an upper limit on the value of the battery. Prior work that accounts for forecast uncertainty often does so in the context of a single dispatch algorithm, which does not provide a baseline for comparison. Furthermore, when multiple dispatch algorithms are assessed with uncertainty, the benefits considered are for diesel generation in a microgrid, not retail rate savings. This work addresses the gaps in the literature by comparing the performance of both heuristic and optimal dispatch algorithms for retail rate savings under forecast uncertainty, and provides comparisons of the robustness of these algorithms and their associated estimates of economic value. We find that using a perfect forecast can overestimate the value of hybrid PV-battery systems between 1% and 8% compared to the reality of using a day-ahead forecast, depending on the dispatch algorithm used. Thus, accounting for forecast uncertainty in system design and analysis will significantly improve the accuracy of modeled system values.

batteries↗

Impacts of Dispatch Strategies and Forecast Errors on the Economics of Behind-the-Meter PV-Battery Systems: Preprint

To assess the economic value of batteries in hybrid PV-battery systems, one must create a dispatch profile for the battery. Many analyses of battery value assume perfect forecasts of PV generation and load, determining an upper limit on the value of the battery. Prior work that accounts for forecast uncertainty often does so in the context of a single dispatch algorithm, which does not provide a baseline for comparison. Furthermore, when multiple dispatch algorithms are assessed with uncertainty, the benefits considered are for diesel generation in a microgrid, not retail rate savings. This work addresses the gaps in the literature by comparing the performance of both heuristic and optimal dispatch algorithms for retail rate savings under forecast uncertainty, and provides comparisons of the robustness of these algorithms and their associated estimates of economic value. We find that using a perfect forecast can overestimate the value of hybrid PV-battery systems between 1% and 8% compared to the reality of using a day-ahead forecast, depending on the dispatch algorithm used. Thus, accounting for forecast uncertainty in system design and analysis will significantly improve the accuracy of modeled system values.

batteries↗

A python package for analyzing Resilience of Complex Systems (pyRoCS) v.0.0

SAND2024-01040O PyRoCS software synthesizes mathematical equations from several domains—including information theory, ecology, and engineering sciences—to support resilience analysis for complex systems. Resilience is the ability of the complex system being analyzed to withstand, operate through, and recover from a disruption. The complex system can be a physical system such as an electric grid, an organization such as a company, or even a subfunction of an organization. Existing mathematical equations for resilience analysis are found within multiple domains including information theory, biological sciences, and complex systems. This package synthesizes and refactors equations from these various domains to make them more generalizable for application across different types of complex systems relevant for resilience analysis. Users will be able to apply these equations to characterize different components of complex systems based on available data. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Verzi, Stephen↗

Nuclear's Role in the U.S. Electricity System: A Multi-Model Inter-Comparison Analysis

Multiple capacity expansion models (CEMs) for the U.S. power system represent the balance of options among generation, transmission, and storage assets that can satisfy electric loads, operating and planning reserves, and policy requirements. These models are typically set up to find the least-cost portfolio of assets that meet specified requirements, and model decisions can include both investments in new, and retirement of existing, resources. The scenarios explored by CEMs can help inform strategies for meeting future electricity and energy needs under a range of future conditions. However, projections can differ between models, sometimes dramatically, for a seemingly similar scenario. Differences in model coverage, structure, and input assumptions contribute to the range of model outcomes. Understanding what drives the biggest differences in model outputs improves model insights and provides context for interpreting results. This summary presents analysis that was performed through a forum of analysts who own, update, and apply CEMs, as well as nuclear experts from national laboratories, industry, and the research community. The following sections describe methods, results, and findings from an original, innovative inter-model comparison that provides insights into what drives the greatest differences in nuclear retirement and deployment projections across models and a range of technology, market, and policy conditions.

capacity expansion model↗

Economic and environmental performance of biomass gasification for renewable natural gas production in the context of the U.S. natural gas supply

Bioenergy technologies offer potential for reducing greenhouse gas (GHG) emissions. One such promising technology is biomass gasification, which is the conversion of biomass into renewable natural gas (RNG) for use with a natural gas combined-cycle power generation system. However, the associated economic and emission effects need to be better understood to enable optimal decision-making and avoid missed opportunities for enhancing efficiency and increasing system circularity. This analysis explores opportunities to (1) decarbonize natural-gas-based systems and (2) leverage the extensive US natural gas infrastructure to mobilize biomass resources to achieve environmental and economic benefits. Here, in this analysis, the research team used a spatially explicit biomass logistics model (integrated with relevant biomass availability, technoeconomic analysis, and life cycle assessment information) to simulate economically optimal biomass allocation for RNG production and use for decarbonization in the United States. Results show that the United States has the potential to produce 9203 million GJ of RNG within the expected range of $\$$12–30/GJ. Further analyses tested the overall RNG production system's sensitivity to economic and emissions parameters of nine different processes. The sensitivity analysis results indicate that the median carbon abatement cost of RNG is most sensitive to changes in emissions associated with conversion processes and land use changes. These findings provide a deeper understanding of RNG's economic and emission potential for decision-making and guiding future research.

09 BIOMASS FUELS↗

Nonequilibrium steady state and heat transport in nonlinear open quantum systems: Stochastic influence action and functional perturbative analysis

In this paper, we show that a nonequilibrium steady state (NESS) exists at late times in open quantum systems with weak nonlinearity by following its nonequilibrium dynamics with a perturbative analysis. We consider an oscillator chain containing three-types of anharmonicity: cubic α- and quartic β-type Fermi–Pasta–Ulam–Tsingou (FPUT) nearest-oscillator interactions and the on-site (pinned) Klein–Gordon (KG) quartic self-interaction. Assuming weak nonlinearity, we introduce a stochastic influence action approach to the problem and obtain the energy flows in different junctures across the chain. The formal results obtained here can be used for quantum transport problems in weakly nonlinear quantum systems. For α-type anharmonicity, we observe that the first-order corrections do not play any role in the thermal transport in the NESS of the configuration we considered. For KG and β-types anharmonicity, we work out explicitly the case of two weakly nonlinearly coupled oscillators, with results scalable to any number of oscillators. We examine the late-time energy flows from one thermal bath to the other via the coupled oscillators, and show that both the zeroth- and the first-order contributions of the energy flows become constant in time at late times, signaling the existence of a late-time NESS to first order in nonlinearity. Our perturbative calculations provide a measure of the strength of nonlinearity for nonlinear open quantum systems, which may help control the mesoscopic heat transport distinct from or close to linear transport. Furthermore, our results also give a benchmark for the numerical challenge of simulating heat transport. Our setup and predictions can be implemented and verified by investigating heat flow in an array of Josephson junctions in the limit of large Josephson energy with the platform of circuit QED.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Method—Practices and Pitfalls in Voltage Breakdown Analysis of Electrochemical Energy-Conversion Systems

Many electrochemical energy-conversion systems are evaluated by polarization curves, which report the cell voltage across a range of current densities and are a global measure of operation and state of health. Mathematical models can be used to deconstruct the measured overall voltage and identify and quantify the voltage-loss sources, such as kinetic, ohmic, and mass-transport effects. These results elucidate the best pathways for improved performance. In this work, we discuss several voltage-breakdown methods and provide examples across different low-temperature, membrane-based electrochemical systems including electrolyzers, fuel cells, and related electrochemical energy-conversion devices. We present best practices to guide experimentalists and theorists in polarization-curve breakdown analysis.

30 DIRECT ENERGY CONVERSION↗

Technology Innovation Pathways for Distributed Wind Balance-of-System Cost Reduction

This exploratory analysis characterizes the balance-of-system (BOS) cost reduction opportunity for small, commercial, medium, and large distributed wind systems. To do this, we used the National Renewable Energy Laboratory’s (NREL’s) Land-based Balance of System Systems Engineering (LandBOSSE) model (Eberle et al. 2019). This model calculates the capital expenditures (CapEx) associated with installation and the system components (e.g., foundation and electrical infrastructure) other than the rotor nacelle assembly and tower. Then, building on the cost reduction potential assessment, we provide a more qualitative evaluation of prospective technology innovation concepts that may enable realization of those cost reductions for distributed wind systems.

17 WIND ENERGY↗

Identification of uncommon objects in containers

A system for identifying in an image an object that is commonly found in a collection of images and for identifying a portion of an image that represents an object based on a consensus analysis of segmentations of the image. The system collects images of containers that contain objects for generating a collection of common objects within the containers. To process the images, the system generates a segmentation of each image. The image analysis system may also generate multiple segmentations for each image by introducing variations in the selection of voxels to be merged into a segment. The system then generates clusters of the segments based on similarity among the segments. Each cluster represents a common object found in the containers. Once the clustering is complete, the system may be used to identify common objects in images of new containers based on similarity between segments of images and the clusters.

97 MATHEMATICS AND COMPUTING↗

Optimizing Residential HVAC Systems: Evaluating How the Usage of Smart Diagnostic Tools for Quality Installation and Commissioning Impacts System Performance and HVAC Contractor Businesses

The adoption of digital quality installation and fault detection tools has the potential to transform the $14 billon residential heating, ventilating, and air conditioning (HVAC) service and installation industry. Increased market penetration can be accelerated by providing an increased understanding of the energy and economic value proposition of the usage of these tools. In tandem with energy and HVAC system performance impact research and analysis, the Southface Team investigated the economic business implications for HVAC service and installation contractors adopting the use of measureQuick (mQ), a smart diagnostic app that aids in quality installation and fault detection and works agnostically with Bluetooth-enabled HVAC technician tools.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Techno-Economic Analysis of Solid Oxide Fuel Cell-Gas Turbine Hybrid Systems for Stationary Power Applications Using Renewable Hydrogen

Solid oxide fuel cell (SOFC)–gas turbine (GT) hybrid systems can produce power at high electrical efficiencies while emitting virtually zero criteria pollutants (e.g., ozone, carbon monoxide, oxides of nitrogen and sulfur, and particulate matters). This study presents new insights into renewable hydrogen (RH 2 )-powered SOFC–GT hybrid systems with respect to their system configuration and techno-economic analysis motivated by the need for clean on-demand power. First, three system configurations are thermodynamically assessed: (I) a reference case with no SOFC off-gas recirculation, (II) a case with cathode off-gas recirculation, and (III) a case with anode off-gas recirculation. While these configurations have been studied in isolation, here we provide a detailed performance comparison. Moreover, a techno-economic analysis is conducted to study the economic competitiveness of RH 2 -fueled hybrid systems and the economies of scale by offering a comparison to natural gas (NG)-fueled systems. Results show that the case with anode off-gas recirculation, with 68.50%-lower heating value (LHV) at a 10 MW scale, has the highest efficiency among the studied scenarios. When moving from 10 MW to 50 MW, the efficiency increases to 70.22%-LHV. These high efficiency values make SOFC–GT hybrid systems highly attractive in the context of a circular economy as they outcompete most other power generation technologies. The cost-of-electricity (COE) is reduced by about 10% when moving from 10 MW to 50 MW, from USD 1976/kW to USD 1668/kW, respectively. Renewable H 2 is expected to be economically competitive with NG by 2030, when the U.S. Department of Energy’s target of USD 1/kg RH 2 is reached.

25 ENERGY STORAGE↗

Assessment of Nuclear Energy to Support Negative Emission Technologies

The feasibility and performance of nuclear energy coupled with Negative Emission Technology (NET) processes were investigated in this report. Three overarching questions from nuclear NET systems guided this research: which NET would be able to use heat and/or electricity from nuclear power plants (NPPs); what is the performance and cost of a nuclear NET system; and what would be the market outlook for this system? Among the various NETs that are actively being developed, several were found to potentially benefit from coupling with an NPP via (1) large amounts of decarbonized and constant-output electricity; (2) free waste heat or cheap low-temperature heat; or (3) high-temperature heat. NPPs were found to be compatible with Direct Air Capture (DAC) systems, and a detailed techno-economic analysis of coupled NPP&DAC systems was performed. Preliminary analysis also indicated that biomass and water-based NETs are potentially compatible with NPPs, but further work is needed to quantify the performance of these nuclear NET systems. Design and performance analyses were completed for both liquid solvent DAC (L-DAC) and solid sorbent DAC (S-DAC) technologies. A 1.0-GWth NPP coupled with L-DAC and S-DAC was found to be able to capture 12–15 Mt CO 2 /yr and 1.0–1.5 Mt CO 2 /yr, respectively. While the L-DAC process enables much greater CO 2 capture than the S-DAC process when both are sized with a 1 GWth NPP, the NPP&L-DAC system considered also requires >2 GWth natural gas oxy-combustion to reach adequate temperature in the calciner. CO 2 generated from natural gas combustion is also captured as part of the calcination process, in addition to the CO 2 captured from air, resulting in overall CO 2 sequestration of close to 30% more than what is captured from air. The cost of carbon capture calculated with the levelized cost of DAC (LCOD) had a range of $\$170–260$/tCO 2 for NPP&L-DAC systems and a range of $\$650–680$/tCO 2 for NPP&S-DAC systems. For both DAC systems, the NPP provides economic benefit when compared to previous National Energy Technology Laboratory (NETL) studies of non-nuclear DAC systems, leading to reduction of LCOD by 5–7% for L-DAC, and 8–13% for S-DAC. For the NPP&DAC systems, a preliminary market analysis reviewed potential CO 2 market prices and eligibility for incentives. The estimated potential revenues for CO 2 capture (coming from federal incentive, CO 2 commodity markets, or offset market) is in the range of $\$170–979$ tCO 2 , and the results show that because of lower LCOD, the NPP&L-DAC process would be more attractive to a market than the NPP&S-DAC process. The large investment needed for NPP&DAC processes would require long-term certainty of sufficient market size, CO 2 prices, and incentives. Enabling NPPs to ramp DAC operation up or down based on electricity market price is not expected to significantly increase revenues of the NPP&DAC system. This is because the revenues from CO 2 sequestration are required to be very high to justify the deployment and continuous operation of the very expensive DAC technologies. In this analysis, several new research questions were uncovered, and follow-up analyses are recommended for further investigation, including a detailed feasibility study of NPP coupled with other NET systems such as biomass pyrolysis and gasification with carbon capture and storage, and seawater carbon capture.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗