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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Evaluation of Steam Cycle Upgrades to Improve the Competitiveness of U.S. Coal Power Plants (Final Scientific / Technical Report)

Increasing the competitiveness of the existing pulverized-coal utility fleet in the United States may be achieved by decreasing heat rate, via increases in steam cycle efficiency through upgraded steam temperatures and use of latest technology available in steam turbine and blading design. The average net plant efficiency of the US coal-fired fleet is approximately 33% (HHV). Plant efficiency increases to approximately 41.4% (HHV) at 1,350°F (732°C) steam temperature. However, achieving these Advanced Ultra-Super Critical (AUSC) steam conditions requires the use of advanced high-temperature materials. While there has been a significant amount of DOE-funded materials R&D, most of the related design work has focused on new (greenfield) units, rather than on opportunities to retrofit this advanced technology to the existing utility fleet. If technology, based upon the advanced materials required for AUSC steam conditions, may be applied to the existing fleet, using an economically viable retrofit, a higher capacity factor can be expected as a result of the increased plant competitiveness. The Electric Power Research Institute (EPRI) was awarded a project by the US Department of Energy to examine the technical and economic feasibility of a series of steam cycle upgrades to the two most prevalent types of U.S. coal power plants: 2,400 psig (16.6 MPa) subcritical and 3,500 psig (24.1 MPa) supercritical pulverized coal units. The nine upgrade options that were originally being considered included increasing the main and reheat steam temperatures from 1,000°F (538°C) to 1,100°, 1,200°, and 1,350°F (593°C, 649°C, and 732°C) while holding the steam pressures constant at their original design values, and cases where just the main steam or reheat steam temperatures were increased. The objective was to minimize the modifications required to the existing power plant while still providing a significant improvement in heat rate. The upgrade options assumed that the boiler enclosure envelope remained unchanged from each base case, and that all applicable OEM design guidelines for normal commercial units were imposed. For the highest temperature supercritical case, an option of using a low-pressure molten salt loop to transfer heat from the furnace to the steam was examined. The first major task of the work scope was designed to examine the technical feasibility of various upgrade options, while the subsequent work determined economic viability of the technically feasible upgrade options. Prior to evaluating the effect of these increased temperatures, a “base case” model of a subcritical and supercritical PC boiler was created, which was used for comparative purposes. Upgrade options were evaluated at full-load, part-load and dynamic transient conditions. Once the technical feasibility of each upgrade option was evaluated, the economic value of the heat rate improvement of each feasible option was determined by detailed modeling of unit dispatch in several regional power markets. The dispatch model was used to estimate the amount of revenue from power sales the upgraded unit would receive in comparison to a non-upgraded version of the same power plant. As a parallel task to the dispatch analysis, the capital cost of implementing the upgrades was estimated. The capital cost estimates were then compared to the increased revenue estimated by the dispatch modeling to determine the economic attractiveness of each upgrade option. Several upgrade options were determined to be technically feasible. The net present value (NPV) of the costs for steam cycle upgrades considered in this study ranged from approximately $\$$111 to $\$$130 million. The economic modeling results show that the unit dispatch changes resulting from steam cycle upgrades are relatively small, due largely to heat rate (and operating cost) changes being relatively small. Additionally, the cost of each upgrade exceeds the net revenue increases associated with the upgrade case. Note that the breakeven values are higher for subcritical retrofits, but the capital costs for the subcritical upgrades are also slightly higher. In typical new pulverized coal plants, fuel accounts for approximately 25% of the cost of electricity (COE), while capital costs represent around 50% of the COE. Therefore, in order to improve the heat rate by 4% one can only afford to increase the capital cost by 2%, at the same cost of electricity. The conclusion of this study is that without a cost for emitting CO 2 , it will be difficult to pay for significant efficiency improvements on plants firing low cost coals.

01 COAL, LIGNITE, AND PEAT↗
NASA NTRS1983

The fundamental structure function of oscillator noise models

Continuous-time models of oscillator phase noise x(t) usually have stationary nth differences, for some n. The covariance structure of such a model can be characterized in the time domain by the structure function: D sub n (t;gamma sub 1, gamma sub 2) = E delta (n) sub gamma sub 1 x(s+t) delta(n) sub gamma sub 2 x (s). Although formulas for the special case D sub 2 (0;gamma,gamma) (the Allan variance times 2 gamma(2)) exist for power-law spectral models, certain estimation problems require a more complete knowledge of (0). Exhibited is a much simpler function of one time variable, D(t), from which (0) can easily be obtained from the spectral density by uncomplicated integrations. Believing that D(t) is the simplest function of time that holds the same information as (0), D(t) is called the fundamental structure function. D(t) is computed for several power-law spectral models. Two examples are D(t) = K/t/(3) for random walk FM, D(t) = Kt(2) 1n/t/ for flicker FM. Then, to demonstrate its use, a BASIC program is given that computes means and variances of two Allan variance estimators, one of which incorporates a method of frequency drift estimation and removal.

Greenhall, C. A.↗
DOE OSTI2021

Observability Analysis of a Power System Stochastic Dynamic Model Using a Derivative-Free Approach

Serving as a prerequisite to power system dynamic state estimation, the observability analysis of a power system dynamic model has recently attracted the attention of many power engineers. However, because this model is typically nonlinear and large-scale, the analysis of its observability is a challenge to the traditional derivative-based methods. Indeed, the linear-approximation-based approach may provide unreliable results while the nonlinear-technique-based approach inevitably faces extremely complicated derivations. Furthermore, because power systems are intrinsically stochastic, the traditional deterministic approaches may lead to inaccurate observability analyses. In this work, facing these challenges, we propose a novel polynomial-chaos-based derivative-free observability analysis approach that not only is free of any linear approximations, but also accounts for the stochasticity of the dynamic model while bringing a low implementation complexity. Furthermore, this approach enables us to quantify the degree of observability of a stochastic model, what conventional deterministic methods cannot do. The excellent performance of the proposed method has been demonstrated by performing extensive simulations using a synchronous generator model with IEEE-DC1A exciter and the TGOV1 turbine governor.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Estimating and Calibrating DER Model Parameters Using Levenberg–Marquardt Algorithm in Renewable Rich Power Grid

The proliferation of inverter-based distributed energy resources (IBDERs) has increased the number of control variables and dynamic interactions, leading to new grid control challenges. For stability analysis and designing appropriate protection controls, it is important that IBDER models are accurate. This paper focuses on the accurate estimation and parameter calibration of DER_A, a recently proposed aggregated IBDER model. In particular, we focus on the parameters of the reactive power–voltage regulation module. We formulate the problem of parameter tuning as a non-linear least square minimization problem and solve it using the Levenberg–Marquardt (LM) method. The LM method is primarily chosen due to its flexibility in adaptively selecting between the steepest descent and Gauss–Newton methods through a damping parameter. The LM approach is used to minimize the error between the actual measurements and the estimated response of the model. Further, the computational challenges posed by the numerical calculation of the Jacobian are tackled using a quasi-Newton root-finding approach. The proposed method is validated on a real feeder model in the northeastern part of the United States. The feeder is modeled in OpenDSS and the measurements thus obtained are fed to the DER_A model for calibration. The simulation results indicate that our approach is able to successfully calibrate the relevant model parameters quickly and with high accuracy, with a total sum of square error of 3.57 × 10 –7 .

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

A Model-Reference Adaptive Direct-Power Control Scheme for Grid-Interactive Inverters

This paper develops an adaptive direct power control scheme for grid-interactive inverters while the control parameters are adaptively adjusted as the grid and filter parameters vary under different conditions. To demonstrate the efficacy and robustness of the adaptive operation, the performance of the adaptive controller is compared with a typical direct power controller by estimating the filter and grid impedances using a model reference parameter estimation technique with small signal injection. The simulation results verify that the developed methodology can track the reference power setpoints under output circuit parameter uncertainties while the typical design leads to instability. To improve the performance of the adaptive technique and eliminate the need for filter parameter estimation, a Lyapunov stability criterion-based model-reference adaptive direct power controller is designed to track the filter impedance. The developed method was tested using MATLAB/Simulink software to demonstrate the effectiveness of the proposed method. The results verify that adaptively tuning the control parameter can still maintain stable operation if the control gains are poorly selected while applying the classical method leads to abnormal operation or instability.

Gursoy, Mehmetcan↗
DOE OSTI2025

Lidar-Based Evaluation of HRRR Performance in California’s Diablo Range

The performance of the NOAA High-Resolution Rapid Refresh (HRRR) model for capturing low-level winds near a wind energy production site during summer 2019 is evaluated. This study catalogs the ability of HRRR to predict boundary layer dynamics relevant to wind energy interests over complex terrain, which has presented challenges for weather and energy forecasting. Performance is evaluated by comparing HRRR output to wind-profiling Doppler lidars at Lawrence Livermore National Laboratory Site 300. HRRR captured the diurnal profile of horizontal winds in the observed 150-m layer, despite strong underpredictions (∼4 m s −1 ) during evening and nighttime hours. These underpredictions may be a result of local speedup flows observed by the lidars, which were unresolved in HRRR due to their small spatial extent. HRRR bias magnitude relative to observations was found to be minimal during days with synoptic-scale troughs and strong 850-hPa geopotential gradients, while bias magnitude was maximal during days with synoptic ridging and weak 850-hPa geopotential gradients. To translate wind speed predictions to energy forecasting, generic turbine models were used to estimate power generation for turbines characteristic of the nearby Altamont Pass Wind Resource Area. Results show that HRRR-based energy estimates predicted daytime power generation adequately relative to lidar-based estimates with an 18-h lead time (bias magnitude < 0.4 MW from 0900 to 1400 LT) but overpredicted power during the rest of the diurnal cycle (bias > 1 MW). These results demonstrate conditions under which HRRR performs well for wind energy applications in complex terrain, while highlighting biases that require further investigation to support usage of a high-resolution model for wind energy forecasts.

Boundary layer↗
NASA NTRS1988

Digital spectral estimation and modeling of Space Shuttle flight data

Application of the digital signal processing technique of autoregressive-moving-average (ARMA) modeling to the estimation of power spectra and shock spectra from Space Shuttle lift-off flight accelerograms is described in this paper. The background for application to ARMA of lift-off accelerograms which are non-stationary in nature is exemplified through a step-by-step discussion of actual numerical results. Included is a discussion of pertinent mathematical background for the ARMA approximations. Potential areas for application of ARMA modeling in payload integration activities are suggested.

Spanos, P. D.↗
DOE OSTI2025

Dynamics modeling of molten salt reactor with reduced and expanded representations of delayed neutron precursors

Molten salt reactors (MSRs) present unique challenges in dynamic behavior due to the mobility of their fuel. In these reactors, delayed neutron precursors (DNPs) drift with the fuel circulation through the primary loop. As a result, a fraction of DNPs decays outside the core, effectively reducing the available delayed neutron population for reactivity control. Consequently, precise modeling of the distribution and behavior of DNPs is critical for accurate reactor dynamics simulations. In this study, the System Dynamics Analysis Tool (SDAT) was used to simulate a thermal-spectrum MSR under steady-state conditions and following transients. The effects of using reduced and expanded representations of DNPs with fewer or more groups than the conventional 6-group model were investigated. Their impact on the simulated distribution of precursors in the primary loop, reactivity loss value, and reactor response to transients was analyzed. Simulation results showed that reduced models lead to the loss of the actual DNPs distribution data, resulting in less accurate estimates of reactivity loss. Reactor power predictions using these reduced models showed significant deviations compared to those using the conventional 6-group model in transient simulations. Expanded models offered a more accurate representation of the distribution of DNPs and reactivity loss estimates. Reactor power predictions using expanded models showed minimal deviation from the conventional 6-group model during the simulated transients.

analysis↗
DOE OSTI2023

Robust Real-Time Modeling of Distribution Systems with Data-Driven Grid-Wise Observability (Final Technical Report)

The overall objective of this project is to leverage existing and emerging sensor measurements to develop data-driven observability enhancement algorithms as well as robust state estimation and parameter identification techniques to enable real-time grid-wise monitoring and modeling of loads and distributed energy resources (DERs). The project resulted in a holistic framework with the following key components: 1) data-driven and machine learning-based grid-edge visibility enhancement, 2) robust branch-current-based state estimation (BCSE), and 3) robust real-time steady-state and dynamic-state modeling of loads and DERs. The research outcomes have provided utility companies better network visibility, higher-fidelity load/DER models, and more accurate assessment of DERs’ impacts, thus, facilitating the integration of renewable energy sources. The synergistic collaborative project among Iowa State University (ISU), Argonne National Laboratory (ANL), Electric Power Research Center (EPRC), SIEMENS Industry, Alliant Energy, Cedar Falls Utilities (CFU), and Maquoketa Valley Electric Cooperative (MVEC) to leverage the team’s extensive expertise and experience in power distribution systems, state estimation, online modeling and identification, and DER integrations. The proposed frameworks have been verified with industry adopted software and attempted integrated with existing tool wherever possible

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Shedding light on the economic costs of long-duration power outages: A review of resilience assessment methods and strategies

Here this paper provides a literature review of methods and modeling techniques to estimate the cost of power system outages, along with the value of outage mitigation or system resilience. Regulators, policymakers, and infrastructure owners have a growing need to understand the methods for estimating the benefits of resilience improvements of electric infrastructure against natural and man-made disasters. There is a broad literature that estimates the cost of short-duration outages and a small but developing literature on estimating the cost of long-duration outages. This article reviews the models used to estimate the cost of outages and discusses their relative strengths. Additionally, this paper identifies key questions from stakeholders regarding resilience investment and maps them to the relevant models that would help answer them. We include recommendations for future work to include recent advances in regional economic modeling that can estimate region and demographic-specific costs and the distributional consequences of potential resilience projects.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Bayesian Structural Time Series for Behind-the-Meter Photovoltaic Disaggregation: Preprint

Distributed photovoltaic (PV) generation often occurs ``behind the meter": a grid operator can only observe the net load, which is the sum of the gross load and distributed PV generation. This lack of observability poses a challenge to system operation at both bulk level and distribution level. The lack of real-time or near-future disaggregated estimates of gross load and PV generation will lead to over scheduling of energy production and regulation reserves, reliability constraints violations, wear and tear of controller devices, and potentially cascading failures of a system. In this paper we propose the use of a Bayesian Structural Time Series (BSTS) model with local solar irradiance measurements to disaggregate the summed PV generation and gross load signals at a downstream measurement site. BSTSs are a highly expressive model class that blends classic time series models with the powerful Bayesian state space estimation framework. Disaggregation is done probabilistically, which automatically quantifies the uncertainties of the estimated PV generation and gross load consumption. Depending on the data availability in real-time, it can be used to disaggragate PV and gross load at customer site, or can be used at the feeder level. In this paper, we focus on solving the problem at feeder level. We compare the performance of a BSTS model as well as a handful of state-of-the-art methods on a Pecan Street AMI dataset, using the National Solar Radiation Database (NSRDB) to estimate local irradiance.

Bayesian structural time series↗
DOE OSTI2023

Natural Language Processing-Enhanced Nuclear Industry Operating Experience Data Analysis: Aggregation and Interpretation of Multi-Report Analysis Results

Industry-wide operating experience is a critical source of raw data for reliability and risk model parameter estimations for nuclear power plants. A large portion of operating experience data are failure events stored as reports that contain unstructured data, such as narratives. In current practice, a failure report is usually reviewed and manually coded by analysts. The coding is based on extracting several event characteristics such as system name, component type, sub-part type, failure mode, and failure cause. Event narratives are mostly used to help understand events and extract their characteristics. In this line of research, we aim to maximize the usage of event narratives by leveraging natural language processing (NLP) methods to automatically convert an event narrative to a causal graph. This research has promise to improve physical understanding of failure initiation and propagation and to facilitate use of non-failure data (e.g., near-misses and degradations) to complement the limited data pool of failures. In our previous work, we developed an NLP tool and applied it to analyze a number of licensee event reports submitted by U.S. nuclear power plants to the Nuclear Regulatory Commission. In this paper, we will report our recent research progress in aggregating the results of multiple reports, developing network model(s), and drawing statistical insights.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

Theoretical investigation of decoherence channels in athermal phonon sensors

The creation and evolution of nonequilibrium phonons is central in applications ranging from cosmological particle searches to decoherence processes in qubits. However, the fundamental understanding of decoherence pathways for athermal phonon distributions in solid-state systems remains an open question. Using first-principles calculations, we investigate the primary decay channels of athermal phonons in two technologically relevant semiconductors—Si and GaAs. We quantify the contributions of anharmonic, isotopic, and interfacial scattering in these materials. From this, we construct a model to estimate the thermal power in a readout scheme as a function of time. We discuss the implication of our results on noise limitations in current phonon sensor designs and strategies for improving coherence in next-generation phonon sensors.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Robust Solution Verification Experiments on Nonuniform Meshes

The activities of verification, validation, and uncertainty quantification (VVUQ) provide a comprehensive means to assess the credibility of computational models. Within VVUQ, solution verification assesses numerical errors and evaluates whether the simulation is sufficiently accurate for its intended applications. As computational modeling gains traction in the development of complex, high-consequence systems, the need for robust solution verification intensifies, particularly because experimental data for these systems are often limited. This work examines improvements in the robustness of Richardson extrapolation (RE), a method commonly used in solution verification to study the discretization error of computational models using a power law. Nonuniform mesh refinement is discussed alongside other pollutants that affect the robustness of the power law model. Maximum likelihood estimation (MLE) is proposed as a robust strategy to address the uncertainty generated by nonuniform mesh refinement. An exploratory computational fluid dynamics (CFD) study of a 2D planar Poiseuille flow is conducted to determine if nonuniform mesh noise can be modeled with this MLE approach for more robust RE.

Weinmeister, Justin [ORNL] (ORCID:0000000160090237↗
DOE OSTI2021

Model Reduction by Generalized Falk Method for Efficient Field-Circuit Simulations

The Generalized Falk Method (GFM) for coordinate transformation, together with two model-reduction strategies based on this method, are presented for efficient coupled field-circuit simulations. Each model-reduction strategy is based on a decision to retain specific linearly-independent vectors, called trial vectors, to construct a vector basis for coordinate transformation. The reduced-order models are guaranteed to be stable and passive since the GFM is a congruence transformation of originally symmetric positive definite systems. We also show that, unlike the Pad´e-via-Lanczos (PVL) method, the GFM does not generate unstable positive poles while reducing the order of circuit problems. Further, the proposed GFM is also faster when compared to methods of the type Lanczos (or Krylov) that are already widely used in circuit simulations for electrothermal and electromagnetic problems. The concept of response participation factors is introduced for the selection of the trial vectors in the proposed model-reduction methods. Further, we present methods to develop simple equivalent circuit networks for the field component of the overall field-circuit system. The implementation of these equivalent circuit networks in circuit simulators is discussed. With the proposed model-reduction strategies, significant improvement on the efficiency of the generalized Falk method is illustrated for coupled field-circuit problems.

42 ENGINEERING↗
NASA NTRS1994

Observations of the anisotropy in the cosmic microwave background by the FIRS, SK93, and MSAM-I experiments

The observations and results from the FIRS, SK93, and MSAM-1, experiments are discussed. These experiments search for anisotropy in the cosmic microwave background over a range in angular scale from 180 deg to 0.5 deg and a range in frequency from 26 to 680 GHz. Emphasis is placed on the observing strategy and potential systematic errors. Contamination of the data by galactic sources is addressed. Future directions are indicated. The results for all three experiments, as found by us and others, are given in the context of the standard CDM model, Q(sub CDM), and the model-independent band-power estimates.

Kowitt, Matt↗
NASA NTRS2004

Analysis of the Variation of Energetic Electron Flux with Respect to Longitude and Distance Normal to the Magnetic Equatorial Plane for Galileo Energetic Particle Detector Data

In this study we examine ten-minute omni-directional averages of energetic electron data measured by the Galileo spacecraft Energetic Particle Detector (EPD). Count rates from electron channels B1, DC2, and DC3 are evaluated using a power law model to yield estimates of the differential electron fluxes from 1 MeV to 11 MeV at distances between 8 and 51 Jupiter radii. Whereas the orbit of the Galileo spacecraft remained close to the rotational equatorial plane of Jupiter, the approximately 11 degree tilt of the magnetic axis of Jupiter relative to its rotational axis allowed the EPD instrument to sample high energy electrons at limited distances normal to the magnetic equatorial plane. We present a Fourier analysis of the semi-diurnal variation of electron fluxes with longitude.

synchrotron radiation↗