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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 991 records · Page 55
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Performance of an Isobaric Hybrid Compressed Air Energy Storage System at Minimum Entropy Generation

Efficient, large-scale, and cost-effective energy storage systems provide a means of managing the inherent intermittency of renewable energy sources and drastically increasing their utilization. Compressed air energy storage (CAES) and its derivative architectures have received much attention as a viable solution; however, optimization objectives for these systems have not been thoroughly investigated in the literature. In this work, a hybrid thermal and compressed air energy storage (HT-CAES) system is investigated that mitigates the shortcomings of the otherwise attractive conventional CAES systems and its derivatives—shortcomings such as strict geological locations, low energy densities, and the production of greenhouse gas emissions. The HT-CAES system allows a portion of the available energy to operate a compressor and the remainder to be converted and stored in the form of heat through joule/resistive heating in a high-temperature, sensible, thermal energy storage medium. Internally reversible and irreversible HT-CAES system assumptions were investigated, in addition to regenerative and non-regenerative design configurations. Several system optimization criteria were examined—including maximum energy efficiency, maximum exergy efficiency, maximum work output, and minimum entropy generation—with a focus on whether the latter may lead to conclusive design guidelines in a real system. It is shown that an HT-CAES system designed based on a minimum entropy generation objective may operate at a lower energy and exergy efficiency as well as lower output power than otherwise achievable. Furthermore, optimization objective equivalence is shown to be limited to certain design conditions.

25 ENERGY STORAGE↗
DOE OSTI2026

Findings from Large Bench-Scale Testing of Denitration Electrolyzers for the EDCGe Project

This report highlights the key findings and outcomes relevant to the processability of waste supernatant at Hanford using a denitration electrolyzer. The Electrosynthesis Company issued a Phase 1 report to the Savannah River National Laboratory (SRNL), summarizing the evaluation of large bench-scale denitration electrolyzers to support the electrochemical denitration and caustic generation (EDCGe) project. The Electrosynthesis Company’s report (attached as Appendix A) provides insights into the initial steps required to implement an electrolyzer system at Hanford. Phase 1 experiments focused on validating the denitration electrolyzer’s performance, operating parameters, and reaction products. The robustness of the electrochemical denitration process was demonstrated by two electrolyzer flow cell systems (a 100 cm 2 ElectroCell MP and a 150 cm 2 NESI NS01 cell), both of which achieved significant nitrate and nitrite removal (>50%) with a current efficiency of ~95% for both systems. Higher current densities (500 mA cm –2 ) improved nitrate and nitrite removal rates compared to lower current densities (333 mA cm –2 ), while maintaining a current efficiency of ~94%. The NS01 cell achieved a nitrate species removal rate of ~0.41 mol h –1 at 5 kA m –2 (equiv. to 500 mA cm –2 ). The primary reaction product was ammonia (NH 3 ), constituting 78.3–91.6% of the products (excluding OH – formation). NH 3 was predominantly retained in the catholyte liquid phase rather than being off-gassed. Additionally, the NS01 cell reported an NH 3 generation rate of ~0.36 mol h –1 at 5 kA m –2 . Other gas formation included ~7% N 2 , ~7% H 2 , and trace amounts of N 2 O. The estimated power requirement (extrapolated from the 0.015 m 2 cell data) for a full-scale denitration electrolyzer is approximated to be ~1.6 MW (DC-only) to treat 50% of nitrate and nitrite in a waste stream and generates ~2.1 kmol h –1 of NH 3 with an initial concentration of 4 M NO 3 – /NO 2 – at 300 gal h –1 . Simulated waste containing aluminate, carbonate, oxalate, and halogens exhibited no adverse effects on denitration performance. A preliminary experiment comparing alkaline anolyte (5 M NaOH) with a nickel based anode to acidic media (2 M H 2 SO 4 ) with a DSA-O 2 anode showed a lower operating voltage and generated less H 2 than the acid media. Maintaining a stable 5 M OH – concentration in the anolyte through periodic additions of caustic did not significantly impact denitration performance. This operational mode will be required for long-term experiments. All the experiments demonstrated that electrochemical denitration is a promising approach for treating nitrate and nitrite in simulated waste streams, achieving significant conversion and robustness across varying experimental conditions and electrochemical cell configurations. Lastly, the ability to generate a nearly pure NH 3 stream may prove advantageous for processing at other locations within the Hanford site.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Economic dispatch for electricity merchant with energy storage and wind plant: State of charge based decision making considering market impact and uncertainties

Here this paper investigates how the market impact of electricity merchants and uncertainty of wind generation affect their co-optimized scheduling policy, specifically for merchants who have both energy storage and wind plants. In the existing literature, merchants' trading actions are usually assumed not to affect market prices; however, a large-scale energy storage merchant's actions can affect market prices. To this end, we approximate the electricity price by a linear function of the quantity of power traded by the merchant in the reward function to achieve decision-making incorporating the market impact. This paper utilizes the dynamic programming approach to analyze merchants' optimal multi-period decision-making incorporating market impact, uncertain wind generation, and energy storage constraints. First, our results demonstrate that for a merchant with co-located energy storage facilities and wind power plants, the energy storage's feasible state of charge (SOC) range can be segmented into four possible sub-ranges by three analytically developed SOC reference points. The unique optimal trading decision can be achieved by comparing the current energy inventory and the SOC references of the next period. Second, our results show that market impact and uncertainties substantially change the optimal storage scheduling policy by impacting the values of the reference points. To mitigate the negative effect of the merchant's market impact on buying and selling actions, the merchant may reduce the amount of generating or pumping electricity each period to maximize profit. Moreover, we identify and investigate the trade-off between market price and transaction quantity. Our findings provide co-optimized scheduling guidance for electricity merchants with co-located energy storage and renewable power plants systems.

17 WIND ENERGY↗
DOE OSTI2024

Correlations Between In-Line X-ray Diffraction Data and In-Field Critical Current of Long, 4-μm Thick Film REBCO Tapes Made by Advanced MOCVD

REBa 2 Cu 3 O 7-δ (REBCO, RE = rare earth) tapes with high critical current can be very impactful in high magnetic field applications at low temperatures and power applications at high temperatures. A pilot-scale Advanced Metal Organic Chemical Vapor Deposition (MOCVD) method was used to fabricate 50-m-long, 4+μm-thick REBCO tape in a single pass. Critical currents 3.3x that of commercial HTS tapes were achieved at 20 K, 12 T in these 50-m-long tapes. An in-line 2D X-ray Diffraction (XRD) system has been used to assess the quality of the long tapes in real-time, during manufacturing. The key peaks of REBCO, REO, and BZO phases were identified and utilized for tape quality analysis. Furthermore, a 20-m tape made by Advanced MOCVD was tested over its entire length by reel-to-reel (R2R) scanning Hall-probe microscopy (SHPM) at 65 K, 0.25 T, 2 T, and 4 T. 4-mm-wide strands of Advanced MOCVD tapes showed mean critical currents at 65 K of 530 A, 200 A, and 104 A at 0.25 T, 2 T, and 4 T respectively. The combined use of in-line and offline characterization techniques provides a reliable approach for assessing long REBCO tapes during manufacturing, serving as an effective feedback source for quality control in scaled-up REBCO tape deposition processes. This advancement contributes to the production of longer and more uniform high-performance REBCO tapes for large-scale, high-field superconducting applications

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Variability in Wind Energy Generation across the Contiguous United States

ERA5 provides high-resolution, high-quality hourly wind speeds at 100 m and is a unique resource for quantifying temporal variability in likely wind-derived power production across the United States. Gross capacity factors (CF) in seven independent system operators (ISOs) are estimated using the location and rated power of each wind turbine, a simplified power curve, and ERA5 output from 1979 to 2018. Excluding the California ISO, the marginal probability of a calm (zero power production) is less than 0.1 in any ERA5 grid cell. When a calm occurs, the mean co-occurrence across wind-turbine-containing grid cells ranges from 0.38 to 0.39 for ISOs in the Midwest and central plains [Midcontinent (or Midwest) ISO (MISO), Southwest Power Pool (SPP), and the Electric Reliability Council of Texas (ERCOT) region], increasing to 0.54–0.58 for ISOs in the eastern United States [Pennsylvania–New Jersey–Maryland interconnection (PJM), New York ISO (NYISO), and New England ISO (NEISO)]. Periods with low gross CF have a median duration of ≤6 h, except in California, and are most likely during summer. Additionally, gross CF exhibit highest variance at periods of 1 day in ERCOT and SPP; on synoptic scales in MISO, NEISO, and NYISO; and on interannual time scales in PJM. This implies differences in optimal strategies for ensuring resilience of supply. Theoretical scenarios show adding wind energy capacity near existing wind farms is advantageous even in areas with high existing installed capacity (IC), while expanding into areas with lower IC is more beneficial to reducing ramps and the probability of gross CF falling below 20%. These results emphasize the benefits of large balancing areas and aggregation in reducing wind power variability and the likelihood of wind droughts.

17 WIND ENERGY↗
DOE OSTI2020

Multiresolution GPC-Structured Control of a Single-Loop Cold-Flow Chemical Looping Testbed

Chemical looping is a near-zero emission process for generating power from coal. It is based on a multi-phase gas-solid flow and has extremely challenging nonlinear, multi-scale dynamics with jumps, producing large dynamic model uncertainty, which renders traditional robust control techniques, such as linear parameter varying H ∞ design, largely inapplicable. This process complexity is addressed in the present work through the temporal and the spatiotemporal multiresolution modeling along with the corresponding model-based control laws. Namely, the nonlinear autoregressive with exogenous input model structure, nonlinear in the wavelet basis, but linear in parameters, is used to identify the dominant temporal chemical looping process dynamics. The control inputs and the wavelet model parameters are calculated by optimizing a quadratic cost function using a gradient descent method. The respective identification and tracking error convergence of the proposed self-tuning identification and control schemes, the latter using the unconstrained generalized predictive control structure, is separately ascertained through the Lyapunov stability theorem. The rate constraint on the control signal in the temporal control law is then imposed and the control topology is augmented by an additional control loop with self-tuning deadbeat controller which uses the spatiotemporal wavelet riser dynamics representation. The novelty of this work is three-fold: (1) developing the self-tuning controller design methodology that consists in embedding the real-time tunable temporal highly nonlinear, but linearly parametrizable, multiresolution system representations into the classical rate-constrained generalized predictive quadratic optimal control structure, (2) augmenting the temporal multiresolution loop by a more complex spatiotemporal multiresolution self-tuning deadbeat control loop, and (3) demonstrating the effectiveness of the proposed methodology in producing fast recursive real-time algorithms for controlling highly uncertain nonlinear multiscale processes. The latter is shown through the data from the implemented temporal and augmented spatiotemporal solutions of a difficult chemical looping cold flow tracking control problem.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Advanced Mooring Lines for Marine Energy Workshop – Summary Report

This report summarizes the outcomes of the virtual Advanced Mooring Lines for Marine Energy Workshop. The workshop convened experts from industry, academia, and national laboratories to identify key challenges associated with the deployment of synthetic mooring lines for marine energy applications. Discussions focused on four technical areas—materials, failure and degradation, testing, and modeling. Despite the significant promise of leveraging synthetic mooring systems for marine energy applications, discussion highlighted broader research and development needed to address the lack of validated long-term performance data, insufficient structural health monitoring frameworks, limited large-scale testing capabilities, and gaps in predictive modeling. Overall, the workshop emphasized the importance of coordinated research and development efforts to advance reliable, durable, and cost-effective synthetic mooring solutions for marine energy applications.

16 TIDAL AND WAVE POWER↗
DOE OSTI2024

GPU-enabled extreme-scale turbulence simulations: Fourier pseudo-spectral algorithms at the exascale using OpenMP offloading

Fourier pseudo-spectral methods for nonlinear partial differential equations are of wide interest in many areas of advanced computational science, including direct numerical simulation of three-dimensional (3-D) turbulence governed by the Navier-Stokes equations in fluid dynamics. This paper presents a new capability for simulating turbulence at a new record resolution up to 35 trillion grid points, on the world's first exascale computer, Frontier, comprising AMD MI250x GPUs with HPE's Slingshot interconnect and operated by the US Department of Energy's Oak Ridge Leadership Computing Facility (OLCF). Key programming strategies designed to take maximum advantage of the machine architecture involve performing almost all computations on the GPU which has the same memory capacity as the CPU, performing all-to-all communication among sets of parallel processes directly on the GPU, and targeting GPUs efficiently using OpenMP offloading for intensive number-crunching including 1-D Fast Fourier Transforms (FFT) performed using AMD ROCm library calls. With 99% of computing power on Frontier being on the GPU, leaving the CPU idle leads to a net performance gain via avoiding the overhead of data movement between host and device except when needed for some I/O purposes. Memory footprint including the size of communication buffers for MPI_ALLTOALL is managed carefully to maximize the largest problem size possible for a given node count. Detailed performance data including separate contributions from different categories of operations to the elapsed wall time per step are reported for five grid resolutions, from 2048 3 on a single node to 32768 3 on 4096 or 8192 nodes out of 9408 on the system. Both 1D and 2D domain decompositions which divide a 3D periodic domain into slabs and pencils respectively are implemented. The present code suite (labeled by the acronym GESTS, GPUs for Extreme Scale Turbulence Simulations) achieves a figure of merit (in grid points per second) exceeding goals set in the Center for Accelerated Application Readiness (CAAR) program for Frontier. The performance attained is highly favorable in both weak scaling and strong scaling, with notable departures only for 2048 3 where communication is entirely intra-node, and for 32768 3 , where a challenge due to small message sizes does arise. Communication performance is addressed further using a lightweight test code that performs all-to-all communication in a manner matching the full turbulence simulation code. Performance at large problem sizes is affected by both small message size due to high node counts as well as dragonfly network topology features on the machine, but is consistent with official expectations of sustained performance on Frontier. Overall, although not perfect, the scalability achieved at the extreme problem size of 32768 3 (and up to 8192 nodes — which corresponds to hardware rated at just under 1 exaflop/sec of theoretical peak computational performance) is arguably better than the scalability observed using prior state-of-the-art algorithms on Frontier's predecessor machine (Summit) at OLCF. New science results for the study of intermittency in turbulence enabled by this code and its extensions are to be reported separately in the near future.

3D fast Fourier transform↗
DOE OSTI2022

Design of a Compact Dry Cooler With an Aluminum Heat Exchanger Core for a Supercritical CO2 Power Cycle Is Evaluated for a Concentrating Solar Power Application

Abstract As the supercritical CO2 power cycle develops and the component technologies mature, there is still a need to reduce the associated capital and operating costs to maintain a competitive levelized cost of electricity (LCOE) in order to enter the market. When considering concentrating solar power (CSP) coupled with an sCO2 power block and sensible thermal storage, the technology presents a clean source for utility-scale power generation to support baseload or peak-load electrical demand. However, the LCOE of the technology is still considered higher than the competing technologies and should be reduced to better compete in the market; 2030 targets for dispatchable solar plants are 5¢/kWh for baseload CSP and 10¢/kWh for peaker plants, as set by the United States Department of Energy. In response to this need, this study is targeting improvements in the power cycle precooler to reduce power block contribution to LCOE. This study considers a dry cooler, as CSP plants are sensitive to water consumption because many installations are slated for remote or arid locations where solar irradiance is very high, but water is scarce. Furthermore, the power block footprint for an sCO2 system is quite compact, especially as compared to a steam cycle. Therefore, there is interest in installing a more compact dry cooler that is proportional to the reduced footprint sCO2 power block, while conventional dry coolers are an order of magnitude larger. The competing goals of size, performance, and cost were considered in this study to develop a compact dry cooler that can easily be packaged with the power block, significantly reducing the installation and transport cost compared to the current state of the art, while maintaining or improving upon the heat transfer performance and impact on plant LCOE. This paper details the high-level findings of a large dry cooler sensitivity study for design point selection, design of the compact dry cooler, expected year-round performance for the dry cooler and the power cycle, and the predicted LCOE for a 30-year plant life. It was found that an aluminum heat exchanger core can be suitably designed to meet the pressure and temperature requirements for a precooler in an sCO2 recompression Brayton cycle. The dry cooler assembly was found to have improved heat transfer performance, allowing for increased cycle efficiencies and a reduced plant LCOE. When coupled with a centrifugal blower and compact transition duct, the dry cooler assembly was able to reduce the installation footprint by over 50%.

14 SOLAR ENERGY↗
DOE OSTI2021

Wyandotte Integrated Renewable Energy Strategy (WIRES 2) (Final Technical Report)

Wyandotte Municipal Services (WMS), a Michigan Municipal Utility offering electric generation, transmission & distribution, water filtration & distribution and Broadband/Video sought to deploy a set of renewable energy projects for their Electric Utility that contributed to reducing the City’s environmental and energy impact, provided examples that would encourage businesses and citizens to adopt cleaner energy practices and help WMS meet the required renewable energy standards of the State of Michigan (10% in 2015, 15% in 2021). WMS generates and delivers roughly 280,000 megawatt hours (MWh) of electricity annually to more than 10,000 homes and 1,000 businesses within the City of Wyandotte. The Wyandotte Integrated Renewable Energy Strategy – WIRES 2 resulted in deployment of a set of community-scale micro-wind turbines, evaluation and installation of energy-efficient and low-maintenance light-emitting diode (LED) street lights and park lights in highly visible locations in the City and expansion of the geothermal heating and cooling district that already included residential geothermal systems, to include larger scale business/institutional systems at the Utility’s largest electric customer and at the City Library. Finally, WMS identified the need for job training in energy efficiency and renewable energy technologies to further develop a local skilled workforce in these areas. Partially funded by the grant, the wind turbine project provides a benchmark for WMS, local businesses and residents in the evaluation of utility-scale wind v. micro-wind in an urban environment as a renewable energy strategy. Also partially funded by the grant, the LED project benefited the City of Wyandotte by reducing load on the electric system for the public utility but also reduced City costs for streetlighting, parking lot lighting and park lighting without a compromise in security. The project also resulted in a visual success that has led to additional approvals for non-Grant related LED lighting installations resulting in further reduction in the electric load in the City. Commercial Geothermal installations resulted in the Utility being able to eliminate steam customers who formerly utilized the byproduct of steam from WMS electric production. Due to the reduction in natural gas prices and the overall reduction in market purchased power, it was no longer feasible for WMS to operate its Power Plant as a base load plant and to only operate on a market dispatch philosophy when market prices dictated that WMS could produce electricity cheaper than the market purchase price. This has resulted in fewer operating days for the WMS Power Plant, resulting in less environmental impact. WMS has now completely exited the steam business and the ability to offer a geothermal option to two (2) former steam customers (BASF-Wyandotte and the Bacon Memorial Library) allowed for that. In addition, peak loads have been shaved for these two (2) large customers due to the consistent temperature offered by geothermal heating and cooling, reducing the swings associated with thermostat changes caused by outside temperature changes during extreme high and low temperatures. Finally, energy efficiency and renewable energy college-level classes at Wayne County Community College allowed a group of interested students to pursue studies in those technologies through grant provided tuition, books and course materials. This effort provided a foundation of potential future employees not only for WMS but other energy efficiency/renewable energy employers such as Franklin Energy, a partner with WMS in energy optimization efforts with Wyandotte businesses.

17 WIND ENERGY↗
DOE OSTI2025

Additive manufacturing of amorphous metal soft magnetic composites

Soft magnet alloys are used as magnetic cores for electric motors, transformers, wind turbines and other power generation systems. Soft magnetic cores are expensive and time consuming to manufacture in the complex shapes required for next-generation devices using conventional press and sinter powder metallurgy. The objective of this effort is to additively manufacture high performance soft magnets, with reduced cost and reduced material waste and 10x lower energy (core) loss at the high operating frequencies of many electric machines. Laser powder bed fusion additive manufacturing is used as the fabrication method. Electrical steel and amorphous alloys atomized powders are used as a feedstock materials. Magnetic cores are printed in topology optimized structures such as the Hilbert curve because this has been shown to reduce energy losses by minimizing the eddy currents that circulate within the magnet at high frequencies. In our project, we succeed in printing FeSi 3.5wt% and FeSi 6.5wt% electrical steels, and iron-based soft magnetic amorphous alloys in the shape of Hilbert and Peano curve topology optimized structures. We found that the Peano curve has a higher cut-off frequency than the Hilbert curve, and that amorphous alloys have high cut-off frequencies and higher mechanical hardness than electrical steels. Processing conditions such as laser power, scan speed, and hatching pattern were optimized to achieve high density prints, and optimize magnetic performance. We find that the printing of amorphous alloy soft magnetic cores may be technoeconomically feasible for large scale applications such as transformers, for which supply chain issues and the labor costs of manual fabrication of magnetic cores is prohibitive in some cases.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Powering the Blue Economy: Progress Exploring Marine Renewable Energy Integration With Ocean Observations

The blue economy is a dynamic and rapidly growing movement that captures the interplay between economic, social, and ecological sustainability of the ocean and encompasses numerous maritime sectors and activities (e.g., commerce and trade; living resources; renewable energy; minerals, materials, and freshwater; and ocean health and data). The demand for ocean data to inform scientific, risk reduction, and national security needs is leading to a large increase in the number of deployed ocean observation and monitoring systems, most of which require increased power. Because ocean observation systems are often placed in remote locations, they primarily rely on energy storage (or in some cases in situ energy generation) to power instruments and equipment, which imposes limits on sampling rates, deployment times, and spatiotemporal resolution of data. The U.S. Department of Energy Water Power Technologies Office is exploring the potential for marine renewable energy (MRE) devices (largely wave and tidal energy converters) to provide power to support multiple blue economy opportunities. A portion of these opportunities focus on power at sea markets for providing power in off-grid and offshore locations to support a variety of ocean-based activities, including ocean observation and navigation, underwater vehicle charging, marine aquaculture, marine algae farming, and seawater mining. Initially, research has focused on better understanding how and where MRE can provide a consistent source of reliable power to extend ocean observing missions, including operation of autonomous underwater vehicles. Online surveys as well as phone and inperson interviews were conducted with experts in the field of ocean observing systems and observatories to gather end-user requirements, determine energy needs, identify opportunities for codevelopment, and pinpoint constraints for MRE to meet those needs. The surveys and interviews provided feedback on the potential for powering devices and vehicles using MRE, including identifying common themes and challenges that will inform foundational research and development steps needed to advance the integration of MRE with ocean observing systems. In most cases, additional power generation on the order of watts was identified as significantly beneficial to enhancing ocean observations capabilities.

marine renewable energy, powering the blue economy↗
DOE OSTI2022

Reducing the Overnight Capital Cost of Advanced Reactors Using Equipment-Level Seismic Protective Systems

Consideration of the effects of earthquake shaking on the design and construction of nuclear power plants adds substantially to the overnight capital cost, with anecdotal estimates as high as 35+%, attributed to additional construction materials, need for one-off and sub-optimal designs of equipment due to conflicting design choices, the high cost of seismic qualification of equipment, and regulatory review. Safety-critical equipment in large light water reactors is designed and qualified for seismic demands imposed by the supporting reactor building, optimal mechanical designs are not possible, and designs of a given piece of equipment may vary with height above grade. Similar negative impacts are expected for advanced reactors unless the seismic design paradigm is changed. The overarching goal of this transformational MEITNER project, which involved a multidisciplinary engineering team and designers of three fundamentally different advanced reactors, was to adapt proven seismic isolation and damping technologies to operationalize modular protective systems for safety-class equipment inside advanced reactor buildings. Such seismic protective systems would be tightly integrated into design development for reactor support systems and balance-of-plant construction. The adoption of the technology, which is widely used in non-nuclear sectors, would simplify plant design, enable the use of standardized equipment and buildings, optimized for operational performance, and reduce plant size and weight. The need for site-specific equipment would be eliminated, enabling identical equipment to be used across multiple plants sited across the US and economies of scale, and catalyzing new interest and investment. The equipment-based protective systems would allow siting of advanced reactors in regions of high seismic hazard.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Development of Analysis Methods that Integrate Numeric and Textual Equipment Reliability Data

Within the Light Water Reactor Sustainability (LWRS) program, the Risk-Informed Systems Analysis (RISA) Pathway is performing collaborative research on the development and deployment of technologies designed to assist operating nuclear power plants (NPPs) to reduce operating costs improve plant reliability and availability. One of the RISA research areas is focusing on the development of methods and tools designed to optimize plant operations (e.g., maintenance/replacement schedules, optimal maintenance postures for plant structures, systems, and components [SSCs]) in a manner that is more cost effective than current approaches and makes better use of available SSC health data. The Risk-Informed Asset Management (RIAM) project targets this research area by creating a direct bridge between component equipment reliability (ER) data and system engineer decision making regarding maintenance activity scheduling and component aging management. In this respect, one challenge that NPP system engineers are facing is that the amount of ER data being continuously generated is not only extremely large in size, but it comes in different forms: textual (e.g., condition or maintenance reports) and numeric (e.g., generated by monitoring systems). All these data elements provide them with valuable insights and information regarding: 1) the discovery of anomalous behaviors or degradation trends, 2) the identification of the possible causes behind such behaviors/trends, and 3) the prediction of their direct consequences. However, several challenges have proved to be roadblocks to this process. While some of these challenges are technical in nature (i.e., data are often distributed over several physical servers/databases), others are conceptual in nature: data elements come in different formats (e.g., numeric or textual), and measured values have different scales (e.g., vibration spectra and oil temperature). The activities performed by the RIAM project during FY23 directly tackles the need to simultaneously integrate the analysis of ER data in all its forms, numeric and textual. Note that such task has never been performed before due to the complexity of the systems under consideration but, most importantly, because of the technical challenges behind the harmonization of ER data formats and the lack of adequate computational methods to analyze them. Our approach borrows ideas and concepts from the medical field where integration of several data sources is vital to assist medical practitioners to perform correct diagnosis and indicate optimal treatments. In our view a NPP asset is equivalent to a patient in a medical context. The main difference is the complexity of a human body is a magnitude more complex when compared to typical assets commonly present in NPPs (e.g., centrifugal pumps, or motor operated valves). This simplifies our first requirement when analyzing heterogenous ER data formats: to put data into “context”. Context is here intended as the additional piece of information that is needed by ER data analysis tools to understand what these data elements are referring to, i.e., which king of knowledge they are generating. In our context, this knowledge can be translated into models that capture the form and functional architecture of assets/systems, their dependencies, and how they interact. These models actually emulate the knowledge that that NPP system engineers possess about assets and systems; this is their key of success when analyzing ER data, their challenge is ability to handle large amount of data. Here, we employ model-based system engineering (MBSE) models of systems and assets to represent and capture their architecture and functional, i.e. cause-effect, relations. Then, ER data elements are processed by identifying first of all which elements of the developed MBSE elements they are referring to. For numeric ER data this task is fairly easy since it is possible to precisely pinpoint what MBSE elements the corresponding sensor are observing (e.g., bearing temperature of a centrifugal pump). Task is much harder for textual data since the information contained in issue or maintenance reports needs to “be understood” by a computational tool. Here we called this process as “knowledge extraction”. Once again, we borrow the experience in the medical field where methods to extract knowledge from textual data have been developed in the past decade. The missing element for us is the availability of a complete dictionary of NPP related concepts (in addition to the MBSE models presented earlier) that can put “text into context”. In FY23, such dictionary has been developed along with all the computational elements required for knowledge extraction. Lastly, once numeric and textual ER data elements have been processed and “understood”, then the last step is the discovery of possible cause-effect relations among them. This is performed by observing if a logical connection through the MBSE models exists, and if the

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

A computationally efficient algorithm for computing convex hull prices

Electricity markets worldwide allow participants to bid non-convex production offers. While non-convex offers can more accurately reflect a resource's capabilities, they create challenges for market clearing processes. For example, system operators may be required to execute side payments to participants whose costs are not covered through energy sales as determined via traditional locational marginal pricing schemes. Convex hull pricing minimizes this and other types of side payments while providing uniform (i.e., locationally and temporally consistent) prices. Computing convex hull prices involves solving either a large-scale linear program or the Lagrangian dual of the corresponding non-convex scheduling problem. Further, the former approach requires explicit descriptions of market participants' convex hulls. While linear programs for computing convex hull prices are large, their structure is naturally decomposable by generators. Here, in this work, we propose and empirically analyze a Benders decomposition approach to computing convex hull prices that leverages recent advances in convex hull formulations for thermal generating units. We demonstrate across a large set of test instances that our decomposition approach only requires modest computational effort, obtaining solutions at least an order of magnitude faster than the equivalent large-scale linear programming approach. Overall, we provide a computationally feasible method for computing convex hull prices for industrial scale market clearing problems, enabling the possibility of practical adoption of this advanced pricing mechanism.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

An assessment of the harvesting and fuel performance of a single-pass cut-and-chip harvester in commercial-scale short-rotation poplar crops as influenced by crop and weather conditions

There is a need for data on commercial-scale harvesting operations in hybrid poplar short rotation crops to better understand costs and logistics, especially for modeling large scale biorefineries. An investigation was conducted on the in-field performance of a single-pass cut-and-chip harvester operating in commercial fields for over 370 individual wagon loads representing a range of crop and field conditions. Mean material capacity peaked at 70 Mg h -1 in dry conditions in lower biomass (<60 Mg ha -1 ), but was only 28 Mg h -1 during wet conditions and often higher standing biomass. Wet ground conditions require the harvester to divert additional power to maintaining forward movement, which results in decreased material capacity and increased fuel consumption. Crops with higher standing biomass had taller trees that do not always feed as smoothly into the harvester, slowing forward progress and lowering material capacity. Mean crop specific fuel consumption, L of fuel per Mg of biomass processed, generally decreased as standing biomass increased. When standing biomass was above 40 Mg ha -1 mean crop specific fuel consumption (FCC) was 1.69 L Mg -1 in dry conditions and 3.98 L Mg -1 in wet conditions, but when standing biomass was below 40 Mg ha-1 FCC increased drastically (as high as 5 L Mg -1 ) because the harvester is putting more effort into forward speed instead of material processing. Developing relationships between material capacity and fuel consumption based on standing biomass and ground conditions at representative scales are essential for conducting environmental and economic analyses of these systems.

09 BIOMASS FUELS↗
DOE OSTI2023

Managing Wildfire Risk and Promoting Equity through Optimal Configuration of Networked Microgrids

As climate change increases the risk of large-scale wildfires, wildfire ignitions from electric power lines are a growing concern. To mitigate the wildfire ignition risk, many electric utilities de-energize power lines to prevent electric faults and failures. These preemptive power shutoffs are effective in reducing ignitions, but they could result in wide-scale power outages. Advanced technology, such as networked microgrids, can help reduce the size of the resulting power outages; however, even microgrid technology might not be sufficient to supply power to everyone, thus forcing hard questions about how to prioritize the provision of power among customers. In this paper, we present an optimization problem that configures networked microgrids to manage wildfire risk while maximizing the power served to customers; however, rather than simply maximizing the amount of power served in kilowatts, our formulation also considers the ability of customers to cope with power outages, as measured by social vulnerability, and it discourages the disconnection of particularly vulnerable customer groups. To test our model, we leverage a synthetic but realistic distribution feeder, along with publicly available social vulnerability indices and satellite-based wildfire risk map data, to quantify the parameters in our optimal decision-making model. Our case study results demonstrate the benefits of networked microgrids in limiting load shed and promoting equity during scenarios with high wildfire risk.

distribution systems↗
DOE OSTI2023

High average power ultrafast laser technologies for driving future advanced accelerators

Large scale laser facilities are needed to advance the energy frontier in high energy physics and accelerator physics. Laser plasma accelerators are core to advanced accelerator concepts aimed at reaching TeV electron electron colliders. In these facilities, intense laser pulses drive plasmas and are used to accelerate electrons to high energies in remarkably short distances. A laser plasma accelerator could in principle reach high energies with an accelerating length that is 1000 times shorter than in conventional RF based accelerators. Notionally, laser driven particle beam energies could scale beyond state of the art conventional accelerators. LPAs have produced multi GeV electron beams in about 20 cm with relative energy spread of about 2 percent, supported by highly developed laser technology. This validates key elements of the US DOE strategy for such accelerators to enable future colliders but extending best results to date to a TeV collider will require lasers with higher average power. While the per pulse energies envisioned for laser driven colliders are achievable with current lasers, low laser repetition rates limit potential collider luminosity. Applications will require rates of kHz to tens of kHz at Joules of energy and high efficiency, and a collider would require about 100 such stages, a leap from current Hz class LPAs. This represents a challenging 1000 fold increase in laser repetition rates beyond current state of the art. Here, this whitepaper describes current research and outlook for candidate laser systems as well as the accompanying broadband and high damage threshold optics needed for driving future advanced accelerators.

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