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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 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Uncertainty Assessment of CFD Investigation of the Nonlinear Difference-Frequency Wave Loads on a Semisubmersible FOWT Platform

Current mid-fidelity modeling approaches for floating offshore wind turbines (FOWTs) have been found to underpredict the nonlinear, low-frequency wave excitation and the response of semisubmersible FOWTs. To examine the cause of this underprediction, the OC6 project is using computational fluid dynamics (CFD) tools to investigate the wave loads on the OC5-DeepCwind semisubmersible, with a focus on the nonlinear difference-frequency excitation. This paper focuses on assessing the uncertainty of the CFD predictions from simulations of the semisubmersible in a fixed condition under bichromatic wave loading and on establishing confidence in the results for use in improving mid-fidelity models. The uncertainty for the nonlinear wave excitation is found to be acceptable but larger than that for the wave-frequency excitation, with the spatial discretization error being the dominant contributor. Further, unwanted free waves at the difference frequency have been identified in the CFD solution. A wave-splitting and wave load-correction procedure are presented to remove the contamination from the free waves in the results. A preliminary comparison to second-order potential-flow theory shows that the CFD model predicted significantly higher difference-frequency wave excitations, especially in surge, suggesting that the CFD results can be used to better calibrate the mid-fidelity tools.

17 WIND ENERGY↗
DOE OSTI2020

Augmented Kalman filter with a reduced mechanical model to estimate tower loads on a land-based wind turbine: a step towards digital-twin simulations

This article presents an application of the Kalman filtering technique to estimate loads on a wind turbine. The approach combines a mechanical model and a set of measurements to estimate signals that are not available in the measurements, such as wind speed, thrust, tower position, and tower loads. The model is severalfold faster than real time and is intended to be run online, for instance, to evaluate real-time fatigue life consumption of a field turbine using a digital twin, perform condition monitoring, or assess loads for dedicated control strategies. The mechanical model is built using a Rayleigh–Ritz approach and a set of joint coordinates. We present a general method and illustrate it using a 2-degrees-of-freedom (DOF) model of a wind turbine and using rotor speed, generator torque, pitch, and tower-top acceleration as measurement signals. The different components of the model are tested individually. The overall method is evaluated by computing the errors in estimated tower-bottom-equivalent moment from a set of simulations. From this preliminary study, it appears that the tower-bottom-equivalent moment is obtained with about 10 % accuracy. The limitation of the model and the required steps forward are discussed.

17 WIND ENERGY↗
DOE OSTI2021

FAST.Farm load validation for single wake situations at alpha ventus

The main objective of the presented work is the validation of the simulation tool FAST.Farm for the calculation of power and structural loads in single wake situations; the basis for the validation is the measurement database of the operating offshore wind farm alpha ventus. The approach is described in detail and covers the calibration of the aeroelastic turbine model, transfer of environmental conditions to simulations, and comparison between simulations and adequately filtered measurements. It is shown that FAST.Farm accurately predicts power and structural load distributions over wind direction with discrepancies of less than 10 % for most of the cases compared to the measurements. Additionally, the frequency response of the structure is investigated, and it is calculated by FAST.Farm in good agreement with the measurements. In general, the calculation of fatigue loads is improved with a wake-added turbulence model added to FAST.Farm in the course of this study.

17 WIND ENERGY↗
DOE OSTI2020

High-Frequency, Multiclass Nonintrusive Load Monitoring for Grid-Interactive Residential Buildings

Smart buildings with net-load metering and control capabilities can provide valuable flexibility to grid operators. This article develops a novel approach for high-frequency, multiclass nonintrusive load monitoring (NILM) that enables effective net-load monitoring capabilities with minimal additional equipment and cost. Relative to existing NILM work, the proposed solution operates at a faster timescale, providing accurate multiclass state predictions for each 60-Hz ac cycle without relying on event-detection techniques. The approach is validated using a test bed with residential appliances and shown to have high accuracy, good generalization properties, and sufficient response time to support building grid-interactive control at fast timescales relevant to the provision of grid frequency support services.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Restoring Critical Loads in Resilient Distribution Systems Using a Curriculum Learned Controller: Preprint

In this paper, we propose a curriculum learned reinforcement learning (RL) controller to facilitate distribution system critical load restoration (CLR), leveraging RL's fast online response and its outstanding optimal sequential control capability. Like many grid control problems, CLR is complicated due to the large control action space and renewable uncertainty in a heavily constrained non-linear environment with strong intertemporal dependency. The nature of the problem oftentimes causes the RL policy to converge to a poor-performing local optimum if learned directly. To overcome this, we design a two-stage curriculum in which the RL agent will learn generation control and load restoration decision under different scenarios progressively. Via curriculum learning, the trained RL controller is expected to achieve a better control performance, with critical loads restored as rapidly and reliably as possible. Using the IEEE 13-bus test system, we illustrate the performance of the RL controller trained by the proposed curriculum-based method.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2021

Enhancing Distribution Grid Resilience Through Model Predictive Controller Enabled Prioritized Load Restoration Strategy: Preprint

Effective resilience improvement strategies enable the power grid to cope with disruptive extreme events. Most power grid outages are caused by disruptions in distribution grids. Motivated by the urgent need for power system resilience research, this paper proposes a priority-weighted optimal load restoration technique to enhance the resilience of distribution grids against extreme events. The proposed technique is based on smart distribution technology and framed as sequential multi-step decision process (MDP) and mixed integer linear program (MILP). It is formulated as optimal control problem with a model predictive control (MPC) approach. We applied the devised MILP-MPC-based load restoration technique to a simplified single-bus version of the IEEE 13-bus distribution system with integrated distributed energy resources (DERs) such as wind turbine, photovoltaic array, microturbine, and energy storage device. The technique executes a reducing and rolling horizon optimization in each control step in real-time using the forecasted information of the renewables, the fuel status of the microturbine and the state of charge of the energy storage device. We consider an extreme event which triggered outage of the upstream utility grid and caused islanded operation of the distribution grid. We demonstrated the effectiveness of the proposed MPC approach in restoring the distribution grid loads based on their priority during the main grid outage-caused islanded operation.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2021

Enhancing Distribution Grid Resilience Through Model Predictive Controller Enabled Prioritized Load Restoration Strategy

Effective resilience improvement strategies enable the power grid to cope with disruptive extreme events. Most power grid outages are caused by disruptions in distribution grids. Motivated by the urgent need for power system resilience research, this paper proposes a priority-weighted optimal load restoration technique to enhance the resilience of distribution grids against extreme events. The proposed technique is based on smart distribution technology and framed as sequential multi-step decision process (MDP) and mixed integer linear program (MILP). It is formulated as optimal control problem with a model predictive control (MPC) approach. We applied the devised MILP-MPC-based load restoration technique to a simplified single-bus version of the IEEE 13-bus distribution system with integrated distributed energy resources (DERs) such as wind turbine, photovoltaic array, microturbine, and energy storage device. The technique executes a reducing and rolling horizon optimization in each control step in real-time using the forecasted information of the renewables, the fuel status of the microturbine and the state of charge of the energy storage device. We consider an extreme event which triggered outage of the upstream utility grid and caused islanded operation of the distribution grid. We demonstrated the effectiveness of the proposed MPC approach in restoring the distribution grid loads based on their priority during the main grid outage-caused islanded operation.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2021

Peak Load Management in Distribution Systems Using Legacy Utility Equipment and Distributed Energy Resources: Preprint

The ability to perform peak load management in distribution systems has several benefits for utilities, including reduced demand charges and improved reliability, efficiency, and utilization of the network infrastructure. This paper demonstrates the coordinated operation of an advanced distribution management system (ADMS) and a distributed energy resource management system (DERMS) to achieve peak load management using a realistic laboratory test bed. A commercial ADMS reduces the peak demand by reducing system voltages using a dynamic voltage regulation (DVR) application. A prototype DERMS—based on real-time optimal power flow—controls distributed battery energy storage systems to further reduce the feeder power. Results from the experiments conducted using a model of a real distribution feeder show that the coordinated operation of the ADMS and DERMS is effective in accomplishing peak load management.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2021

An Integrated High-performance Computing and Digital Real-time Simulation Testbed to Benchmark Closed-loop Load Shedding Algorithms in Power Systems

An integrated testbed using digital real-time simulator (DRTS) and a high-performance computing (HPC) cluster is presented here to compare speed and performance of computational schemes to mitigate time-critical issues in electric power systems. The first approach in this testbed validation is taken by running a set of closed-loop load shedding algorithms to compare and contrast two paradigms of arresting cascading failure propagation. Two algorithms involve solving DC and AC power flow model-based optimization problems to compute load shedding at different buses, while a model-based stochastic search using parallel computing provides a viable alternative. The algorithms are implemented in the DRTS-HPC testbed for the IEEE 14-bus benchmark transmission system. As a proof of the concept, simulation results are presented for implementation of closed-loop load-shedding algorithms for cascading failures in the DRTS-HPC testbed

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Distributed Wind for Commercial Loads

Distributed wind can help meet on site energy and resilience needs for a wide variety of commercial loads .While it is a variable resource, it has predictable daily and annual production trends. The presence of on-site renewable generation can enhance resilience, supplying power for long periods of time without worrying about conserving fuel supply. The addition of properly sized storage or complementary solar resources can further reduce the challenges of intermittency and reduce the need for fuel-limited backup power during outage situations. This fact sheet explores further the energy and resilience requirements of commercial loads and how distributed wind may be a good match to meet their load needs.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2024

Distributed Wind for Commercial Loads

Distributed wind can help meet on site energy and resilience needs for a wide variety of commercial loads .While it is a variable resource, it has predictable daily and annual production trends. The presence of on-site renewable generation can enhance resilience, supplying power for long periods of time without worrying about conserving fuel supply. The addition of properly sized storage or complementary solar resources can further reduce the challenges of intermittency and reduce the need for fuel-limited backup power during outage situations. This fact sheet explores further the energy and resilience requirements of commercial loads and how distributed wind may be a good match to meet their load needs.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2026

LAF-Net: A Deep Residual and Cross-Attention Framework for Day-Ahead Load Forecasting: Preprint

Accurate day-ahead load forecasting is essential for reliable power system operations and market efficiency. System operators such as the Midcontinent Independent System Operator (MISO) rely on forecasts from multiple vendors, yet combining them effectively remains a persistent challenge due to vendor-specific biases. This paper presents a novel LSTM-Attention Fusion Network with Error Representation (LAF-Net) that enhances day-ahead hourly load forecasting through deep residual learning and multi-modal cross-attention. The proposed model builds a historical error memory from past vendor performance and dynamically queries it with future hour context to generate adaptive, hour-specific trust weights for each vendor. A bounded residual correction further refines forecasts by mitigating systematic and temporally localized errors. Tested on real MISO LBA data with multi-vendor forecasts, LAF-Net consistently outperforms the best vendor baseline across all 38 LBAs, achieving more than a 40% reduction in system-level mean absolute error (MAE) during peak load hours relative to the best vendor baseline.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Solvent Impregnated Polymers Loaded with Liquid-Like Nanoparticle Organic Hybrid Materials for Enhanced Kinetics of Direct Air Capture and Point Source CO 2 Capture

Hybrid CO 2 capture materials, solvent impregnated polymers (SIPs), are developed based on a simple and scalable encapsulation technique to enhance CO 2 capture kinetics of water-lean solvents with high viscosity. Liquid-like nanoparticle organic hybrid materials functionalized with polyethylenimine (NOHM-I-PEI) are incorporated into a shell material and UV-cured to produce gas-permeable solid sorbents with uniform NOHMs loading (NPEI-SIPs). The CO 2 capture kinetics of NPEI-SIPs show a remarkable 50-fold increase compared to that of neat NOHM-I-PEI due to a large increase in the NOHMs-CO 2 interfacial surface area provided by the SIP design. The optimum NOHM-I-PEI loading and sorption temperature are found to be ≈49 wt% and 50 °C, respectively, and NPEI-SIPs exhibit great thermal stability over 20 CO 2 capture/sorbent regeneration temperature swing cycles. The pseudoequilibrium CO 2 loadings of NPEI-SIPs under humid conditions are as high as 3.1 mmol CO 2 g -1 NPEI - SIPs for 15 vol% CO 2 (postcombustion capture) and 1.7 mmol CO 2 g -1 NPEI - SIPs for 400 ppm (direct air capture). Overall, these findings suggest that NPEI-SIPs can effectively capture CO 2 from a wide range of CO 2 concentrations including direct air capture while allowing the flexible design of CO 2 capture reactors by combining the benefits of liquid solvents and solid sorbents.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Palladium-Percolated Networks Enabled by Low Loadings of Branched Nanorods for Enhanced H 2 Separations

Nanoparticles (NPs) at high loadings are often used in mixed matrix membranes (MMMs) to improve gas separation properties, but they can lead to defects and poor processability that impede membrane fabrication. Herein, it is demonstrated that branched nanorods (NRs) with controlled aspect ratios can significantly reduce the required loading to achieve superior gas separation properties while maintaining excellent processability, as demonstrated by the dispersion of palladium (Pd) NRs in polybenzimidazole for H 2 /CO 2 separation. Increasing the aspect ratio from 1 for NPs to 40 for NRs decreases the percolation threshold volume fraction by a factor of 30, from 0.35 to 0.011. An MMM with percolated networks formed by Pd NRs at a volume fraction of 0.039 exhibits H 2 permeability of 110 Barrer and H 2 /CO 2 selectivity of 31 when challenged with simulated syngas at 200 °C, surpassing Robeson's upper bound. In conclusion, this work highlights the advantage of NRs over NPs and nanowires and shows that right-sizing nanofillers in MMMs is critical to construct highly sieving pathways at minimal loadings. In conclusion, this work paves the way for this general feature to be applied across materials systems for a variety of chemical separations.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Micron Size NaCrO 2 Particles Enable High‐loading Dry‐processed Electrode for Sodium Ion Batteries

Dry-process fabrication using fibrillatable binder is emerging as a promising method to produce high-loading electrodes for energy storage applications, favored by its cost-efficiency and eco-friendliness. While previous studies have demonstrated the advantages of dry process over the traditional slurry method, there remains a gap in understanding how the particle size of active materials influences the mechanical and electrochemical performance of dry electrodes. In this study, four different particle size NaCrO 2 materials (Average size, S-NCO: 0.6 µm, M1-NCO 1.5 µm, M2-NCO: 4.4 µm, and L-NCO: 9.9 µm) are synthesized to investigate the effect of particle size on dry-processed high-loading electrodes. The findings reveal that the larger micron-sized (>4.4 µm) NCO dry films exhibit significantly improved tensile strength and electrochemical performance, primarily ascribed to the low film porosity, abundant inter-particle connection by the binder, comprehensive carbon coverage, and efficient percolation of the conductive pathway. Notably, a full cell incorporated with a high loading (5.2 mAh cm −2 ) and high active material ratio (96.5 wt.%) L-NCO film electrode demonstrates promising cycling stability and rate capability. Furthermore, these results provide valuable insights regarding the design and fabrication of dry-processed electrodes for future energy storage applications.

25 ENERGY STORAGE↗
DOE OSTI2023

Virtual sensing of wind turbine hub loads and drivetrain fatigue damage, Virtuelle Sensoren für die Messung von Hauptwellenlasten und Ermüdungsschäden im Antriebstrang von Windenergieanlagen

Abstract: This paper presents a Digital Twin for virtual sensing of wind turbine aerodynamic hub loads, as well as monitoring the accumulated fatigue damage and remaining useful life in drivetrain bearings based on measurements of the Supervisory Control and Data Acquisition (SCADA) and the drivetrain condition monitoring system (CMS). The aerodynamic load estimation is realized with data-driven regression models, while the estimation of local bearing loads and damage is conducted with physics-based, analytical models. Field measurements of the DOE 1.5 research turbine are used for model training and validation. The results show low errors of 6.4% and 1.1% in the predicted damage at the main and the generator side high-speed bearing respectively. Zusammenfassung: In diesem Aufsatz wird ein digitaler Zwilling für Windenergieanlagen vorgestellt, welcher die virtuelle Erfassung der Hauptwellenlasten und die Zustandsüberwachung von Ermüdungschäden und der verbleibende Nutzungsdauer der Antriebsstranglager ermöglicht. Der digital Zwilling nutzt Messdaten des Supervisory Control and Data Acquisition (SCADA) Systems und des Zustandsüberwachungssystems des Antriebsstranges (CMS). Die Berechnung der Hauptwellenlasten ist mit datenbasierten Regressionsmodellen umgesetzt, während die Berechnung der Lagerkräfte und der Ermüdungsschaden mit physikbasierten Modelle durchgeführt wird. Für die Modellentwicklung und -validierung werden Feldmessdaten der DOE 1.5MW Turbine eingesetzt. Die Abweichungen in den Ermüdungsschäden am Hauptwellenlager und am Generatorwellenlager betragen lediglich 6,4% beziehungsweise 1,1%.

17 WIND ENERGY↗
DOE OSTI2024

Combining solution-, precipitation- and load-transfer strengthening in a cast Al-Ce-Mn- Sc -Zr alloy

Here, a cast Al-9Ce-0.75Mn-0.18Sc-0.12Zr (wt%) alloy is designed to combine three strengthening phases: (i) micron-scale Al 11 Ce 3 platelets formed during eutectic solidification, (ii) nano-scale L1 2 -Al 3 (Sc,Zr) precipitates formed during aging, and (iii) Mn in solid solution in the α-Al matrix. Microstructural analyses by SEM, TEM, and atom-probe tomography reveal that Mn remains in solid solution in the as-cast alloy, providing solution strengthening with no influence on the eutectic Al-Al 11 Ce 3 microstructure, which provides precipitation- and load-transfer strengthening. During long-term over-aging at 400 °C, Mn-rich precipitates grow at the Al-Al 11 Ce 3 interface, with no effect on the microhardness. However, after short aging at 350 °C, a high number density of fine L1 2 -Al 3 (Sc,Zr) nanoprecipitates form in the Al matrix (with a coarser size at the Al-Al 11 Ce 3 interface), providing precipitation strengthening. The synergistic combination of the three strengthening mechanisms (solution, precipitation, and load transfer) in our Al-Ce-Mn-Sc-Zr alloy results in higher microhardness after aging at 350 and 400 °C, and higher creep resistance at 300 °C, as compared to alloys with two strengthening mechanisms: an Al-10Ce-0.93Mn control alloy (without precipitation strengthening from Sc and Zr), Al-Ce-Sc-Zr (without solution strengthening from Mn), and Al-Mn-Zr-Er (without load-transfer strengthening from Ce). Furthermore, these dual-strengthened alloys are more creep resistant than alloys with a single strengthening mechanism (Al-Ce, Al-Mn, and Al-Sc-Zr), confirming that the three mechanisms can be combined in pairs or all together.

36 MATERIALS SCIENCE↗