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Results for “Distribution System State Estimation”

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 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Estimation of process steady state with autoregressive models and Bayesian inference

To improve efficiency, separations engineers will typically design process circuits containing recirculating streams, which mix one or more of the process outputs with the feed material. Doing so can improve efficiency, but will cause a delay in the system reaching steady state conditions until the recirculating load mass flows stabilize. In testing separation circuits, engineers will often test a variety of factors and complete an analysis from sample results. Knowledge of if a process is at steady state, as well as the steady state conditions of a process, is essential for a valid techno-economic analysis. However, the definition of process steady state is often poorly defined, or does not include uncertainty quantification. If the performance of a process operating under two different sets of conditions are compared, an engineer who does not test for steady state or quantify steady state conditions risks producing a faulty analysis. In this work, a Bayesian statistical method for testing if all streams are at steady state is further motivated and then derived. Then after testing for steady state, the same model is used with a prior distribution that enforces a steady state assumption to estimate steady state conditions. Further, these methods were validated in a solvent extraction pilot plant where steady state conditions for all outflows were inferred with uncertainty quantification. Analysis is completed with functions available to the reader as part of the BayesMassBal (V 1.1.0) software package written in R.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2019

Validating Performance Models for Hybrid Power Plant Control Assessment

The need for simple, but accurate performance models of wind turbine generators (WTGs), photovoltaic (PV) plants, and battery energy storage systems (BESS) for various hybrid power plant (HPP) studies motivates the present work. Particularly, the development and verification stage of HPP controls requires reduced-order models to minimize the complexity and computation effort of simulation platforms. In this paper, such models are proposed, and the most essential parts of the models are validated through field measurements. The models target power system integration studies involving active and reactive power, as well as frequency and voltage regulation where detailed models, as proposed in the standards, can be cumbersome. Field measurements of two Vestas WTGs, one 1-MW PV plant, and one 1-MW/1-MWh BESS are used for model validation. The results show that the WTG and PV performance models correctly estimate the power generation variability according to fluctuations in wind speed and solar irradiance. The BESS performance model provides satisfactory results related to grid-forming control performance and estimation of state-of-charge. The presented validation work enables using the proposed performance models for power system studies and HPP control design in all model-based design stages, that is, preliminary analysis, design, verification, and validation with a high level of confidence.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Calibrating Synchronous-Generator-Interfaced DG Models in Microgrids Using Multiple Event Data

Microgrids, consisting of distributed generators (DGs), loads, and energy storage systems, play an important role in future smart grids. In order to evaluate how microgrids operate and their dynamic response, it is necessary to develop accurate dynamic models of DGs in microgrids. This paper proposes a systematic method to calibrate synchronous-generator-interfaced DG models. Challenges associated with model validation in microgrids are analyzed. Underlying parameters are categorized into two groups, i.e., the steady-state parameters and time constants, which are estimated in two successive stages using multiple event data. This methodology ensures that the validated model with the estimated parameters are applicable for all events. A modified unscented Kalman filter (UKF) is proposed to deal with the cases in which measurement of power angle is unavailable. The effectiveness of the proposed method is validated using field test data of a 2.6 MVA diesel generator in a real microgrid.

Wang, Zhiwen↗
DOE OSTI2017

Rapid Active Power Control of Photovoltaic Systems for Grid Frequency Support

As deployment of power electronic coupled generation such as photovoltaic (PV) systems increases, grid operators have shown increasing interest in calling on inverter-coupled generation to help mitigate frequency contingency events by rapidly surging active power into the grid. When responding to contingency events, the faster the active power is provided, the more effective it may be for arresting the frequency event. This paper proposes a predictive PV inverter control method for very fast and accurate control of active power. This rapid active power control method will increase the effectiveness of various higher-level controls designed to mitigate grid frequency contingency events, including fast power-frequency droop, inertia emulation, and fast frequency response, without the need for energy storage. The rapid active power control method, coupled with a maximum power point estimation method, is implemented in a prototype PV inverter connected to a PV array. The prototype inverter's response to various frequency events is experimentally confirmed to be fast (beginning within 2 line cycles and completing within 4.5 line cycles of a severe test event) and accurate (below 2% steady-state error).

14 SOLAR ENERGY↗
DOE OSTI2020

Dynamic State Estimation for Radial Microgrid Protection

Dynamic state estimation (DSE) is a generalization of differential protection that offers a reduced likelihood of misoperation, particularly in the case of devices with nonlinear characteristics such as transformers which are being energized. It is also useful in cases where distance protection performs poorly, such as transmission lines with series compensation or mutually coupled transmission lines. DSE has been previously applied to microgrid branch protection. This study investigates the use of DSE for protection of radial portions of a microgrid or distribution system. This can be a challenge in microgrids or distribution systems with distributed generation on account of lack of fault current from inverter-interfaced generation, varying fault current between grid- connected and islanded modes, the potential for normally-meshed operation and unbalanced operation due to single-phase loads. Admittance relaying has been investigated as a solution for protection of microgrids, though it has been observed to have issues with grounded-wye connected loads, and additional relaying is necessary to prevent misoperation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1981

Modeling of the aircraft in-trail-following task during profile descent

The cockpit display of traffic information (CDTI) system concepts enable the pilot to observe the surrounding air traffic pattern. The impact of such a system is far reaching in terms of improved safety, pilot and controller workload, and aircraft fuel efficiency. One direct payoff is the ability to distribute the ATC workload to the pilot in such tasks as merging and spacing. The CDTI application of spacing approach aircraft in the terminal area is addressed. In-trail-following/CDTI experiments were performed using realistic cockpit simulators and profile descent approach scenarios. Based on collected experimental simulator data, pilot models were developed which include state estimation, decision making and flight control aspects. These models were coupled with models of aircraft and CDTI equipment to study the dynamic phenomena and stability of strings of aircraft along various approach patterns.

Goka, T.↗
NASA NTRS1986

Magnetic helicity as a constraint on coronal dissipation

The Taylor hypothesis has provided a model for the relaxed magnetic configurations of not only laboratory plasmas, but also of astrophysical plasmas. However, energy dissipation is possible only for systems which depart from a strict Taylor state, and hence a parameter describing that departure must be introduced, when the Taylor hypothesis is used to estimate the dissipation. An application of the Taylor hypothesis to the problem of coronal heating provides an insight into this difficult problem. When particular sorts of footpoint motions put energy and helicity in the corona, the conservation of helicity puts a constraint on how much of the energy can be dissipated. However, on considering a random distribution of footpoint motions, this constraint gets washed away, and the Taylor hypothesis is probably not going to play any significant role in the actual calculation of relevant physical quantities in the coronal heating problem.

Choudhuri, Arnab Rai↗
NASA NTRS1986

Controlling Flexible Manipulators, an Experimental Investigation

Lightweight, slender manipulators offer faster response and/or greater workspace range for the same size actuators than tradional manipulators. Lightweight construction of manipulator links results in increased structural flexibility. The increase flexibility must be considered in the design of control systems to properly account for the dynamic flexible vibrations and static deflections. Real time control of the flexible manipulator vibrations are experimentally investigated. Models intended for real-time control of distributed parameter system such as flexible manipulators rely on model approximation schemes. An linear model based on the application of Lagrangian dynamics to a rigid body mode and a series of separable flexible modes is examined with respect to model order requirements, and modal candidate selection. Balanced realizations are applied to the linear flexible model to obtain an estimate of appropriate order for a selected model. Describing the flexible deflections as a linear combination of modes results in measurements of beam state, which yield information about several modes. To realize the potential of linear systems theory, knowledge of each state must be available. State estimation is also accomplished by implementation of a Kalman Filter. State feedback control laws are implemented based upon linear quadratic regulator design.

Hastings, Gordon Greene↗
DOE OSTI2014

Multiwavelength observations of Swift J1753.5–0127

We present contemporaneous X-ray, ultraviolet (UV), optical, and near-infrared observations of the black hole binary system Swift J1753.5–0127 acquired in 2012 October. The UV observations, obtained with the Cosmic Origins Spectrograph on the Hubble Space Telescope, are the first UV spectra of this system. The dereddened UV spectrum is characterized by a smooth, blue continuum and broad emission lines of C IV and He II. The system was stable in the UV to <10% during our observations. We estimated the interstellar reddening by fitting the 2175 Å absorption feature and fit the interstellar absorption profile of Lyα to directly measure the neutral hydrogen column density along the line of sight. By comparing the UV continuum flux to steady-state thin accretion disk models, we determined upper limits on the distance to the system as a function of black hole mass. The continuum is well fit with disk models dominated by viscous heating rather than irradiation. The broadband spectral energy distribution shows the system has declined at all wavelengths since previous broadband observations in 2005 and 2007. If we assume that the UV emission is dominated by the accretion disk, the inner radius of the disk must be truncated at radii above the innermost stable circular orbit to be consistent with the X-ray flux, requiring significant mass loss from outflows and/or energy loss via advection into the black hole to maintain energy balance.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

Estimating the Energy-Efficiency Potential in the Eastern Interconnection

Comprehensive and integrated resource planning considers the potential for increases in energy efficiency to reduce the requirements for new generation and transmission investments. This study supports such planning efforts by developing robust estimates of the economically achievable potential for improving the energy-efficiency of homes, commercial buildings, and industrial plants located in the Eastern Interconnection. The approach of this study involves identifying a series of energy-efficiency policies and examining their impacts and cost-effectiveness using Georgia Tech's version of the National Energy Modeling System (GT-NEMS). The project emphasizes the impacts on electricity consumption, the levelized cost of policy-driven electricity savings, and distributive effects at the state and regional levels. Thirty-six states and the District of Columbia are covered by this study, and the time frame extends to 2035.

Electricity↗
DOE OSTI2017

The COS-Halos Survey: Metallicities in the Low-redshift Circumgalactic Medium

We analyze new far-ultraviolet spectra of 13 quasars from the z∼0.2 COS-Halos survey that cover the H i Lyman limit of 14 circumgalactic medium (CGM) systems. These data yield precise estimates or more constraining limits than previous COS-Halos measurements on the H i column densities N{sub HI}. We then apply a Monte-Carlo Markov chain approach on 32 systems from COS-Halos to estimate the metallicity of the cool (T∼10{sup 4} K) CGM gas that gives rise to low-ionization state metal lines, under the assumption of photoionization equilibrium with the extragalactic UV background. The principle results are: (1) the CGM of field L* galaxies exhibits a declining H i surface density with impact parameter R{sub ⊥} (at >99.5% confidence), (2) the transmission of ionizing radiation through CGM gas alone is 70 ± 7%; (3) the metallicity distribution function of the cool CGM is unimodal with a median of 10{sup −0.51} Z{sub ⊙} and a 95% interval ≈1/50 Z{sub ⊙} to >3 Z{sub ⊙}; the incidence of metal-poor (<1/100 Z{sub ⊙}) gas is low, implying any such gas discovered along quasar sightlines is typically unrelated to L* galaxies; (4) we find an unexpected increase in gas metallicity with declining N{sub HI} (at >99.9% confidence) and, therefore, also with increasing R{sub ⊥}; the high metallicity at large radii implies early enrichment; and (5) a non-parametric estimate of the cool CGM gas mass is M{sub CGM}{sup cool}=(9.2±4.3)×10{sup 10} M{sub ⊙}, which together with new mass estimates for the hot CGM may resolve the galactic missing baryons problem. Future analyses of halo gas should focus on the underlying astrophysics governing the CGM, rather than processes that simply expel the medium from the halo.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1982

The role of multispectral scanners as data sources for EPA hydrologic models

An estimated cost savings of 30% to 50% was realized from using LANDSAT-derived data as input into a program which simulates hydrologic and water quality processes in natural and man-made water systems. Data from the satellite were used in conjunction with EPA's 11-channel multispectral scanner to obtain maps for characterizing the distribution of turbidity plumes in Flathead Lake and to predict the effect of increasing urbanization in Montana's Flathead River Basin on the lake's trophic state. Multispectral data are also being studied as a possible source of the parameters needed to model the buffering capability of lakes in an effort to evaluate the effect of acid rain in the Adirondacks. Water quality in Lake Champlain, Vermont is being classified using data from the LANDSAT and the EPA MSS. Both contact-sensed and MSS data are being used with multivariate statistical analysis to classify the trophic status of 145 lakes in Illinois and to identify water sampling sites in Appalachicola Bay where contaminants threaten Florida's shellfish.

Slack, R.↗
DOE OSTI2023

Cryogenic System Preliminary Design for a 0.5m-Long, Conduction-Cooled Nb3Sn Undulator Magnet Prototype

There are several NbTi superconducting undulator (SCU) magnets currently in operation at the Advanced Photon Source (APS) at Argonne National Laboratory (ANL). The development on Nb3Sn-based superconducting undulator magnets at APS is underway due to the potential to further enhance the performance of the SCUs. Superconducting undulator magnets need to keep temperature gradients minimized in order to retain thermal and operating current margin. We have designed the thermal links for efficient heat conduction using 3D finite element analysis (FEA) simulation in COMSOL Multiphysics software, which was later used for the calculation of the temperature distribution across a 0.5 m long, conduction-cooled, Nb3Sn undulator magnet prototype that includes both conductive heat transfer and radiative heating components. We have modelled the evolution of the thermal properties of the magnet winding as well as other cold parts during cool-down from ambient temperature with the operation of a SHI RDK-415D cryocooler to examine the estimated time that is needed for the cooldown as well as the baseline temperature we could achieve. A key result was that a maximum coil delta T = 0.11 K along the designed thermal links and a temperature range of 3.42 K-3.53 K for the winding were predicted at steady state. A pair of G10 support rods for carrying the magnet as well as a pair of current leads made of metals were also designed and optimized for the testing system, targeting for an operation temperature of 4 K and a coil current of 950 A DC.

Zhang, Danlu↗
DOE OSTI2025

Solving high-dimensional inverse problems using amortized likelihood-free inference with noisy and incomplete data

Here, we present a likelihood-free probabilistic inversion method based on normalizing flows for high-dimensional inverse problems. The proposed method is composed of two complementary networks: a summary network for data compression and an inference network for parameter estimation. The summary network encodes raw observations into a fixed-size vector of summary features, while the inference network generates samples of the approximate posterior distribution of the model parameters based on these summary features. The posterior samples are produced in a deep generative fashion by sampling from a latent Gaussian distribution and passing these samples through an invertible transformation. We construct this invertible transformation by sequentially alternating conditional invertible neural network and conditional neural spline flow layers. The summary and inference networks are trained simultaneously. We apply the proposed method to an inversion problem in groundwater hydrology to estimate the posterior distribution of the log-conductivity field conditioned on spatially sparse time-series observations of the system’s hydraulic head responses. The conductivity field is represented with 706 degrees of freedom in the considered problem. Comparison with the likelihood-based iterative ensemble smoother PEST-IES method demonstrates that the proposed method accurately estimates the parameter posterior distribution and the observations’ predictive posterior distribution at a fraction of the inference time of PEST-IES.

conditional invertible neural network↗
DOE OSTI2017

The Impacts of Changes to Nevada's Net Metering Policy on the Financial Performance and Adoption of Distributed Photovoltaics

As the adoption of distributed photovoltaics (DPV) has continued to rapidly increase, a national conversation has begun about the efficacy of full-retail net metering as a means of achieving the diverse objectives of electricity pricing. This conversation has prompted studies that have primarily focused on the total costs and benefits of DPV. To compliment those studies, we here characterize the potential impacts of tariff design on the customer-economics and adoption of DPV, where recent changes in Nevada are taken as a case study. We show that an increase in fixed charges more strongly impacts the payback period of small systems, and a decrease in credit for exported electricity more strongly impacts the payback period of large systems. We project that these combined changes will reduce DPV adoption in Nevada; total capacity in 2030 was projected to reach up to 363 MW, with 226 MW having already been installed at the end of the second quarter of 2016. In contrast, if full retail net metering had continued, DPV capacity was projected to reach up to 1,280 MW at the end of 2030, which would account for an estimated 6.5% of the total sales of electricity by NV Energy at that time. We project that the DPV systems will decrease the gross revenue from bill collection by $48 million per year under the new tariffs, whereas the decrease in gross revenue could have reached $255 million per year if full retail net metering had been continued. Although these results are given in the context of Nevada, the trends shown are intended to help information similar upcoming decisions in other states.

14 SOLAR ENERGY↗
NASA NTRS2002

In vitro cell irradiation systems based on 210Po alpha source: construction and characterisation

One way of studying the risk to human health of low-level radiation exposure is to make biological experiments on living cell cultures. Two 210Po alpha-particle emitting devices, with 0.5 and 100 MBq activity, were designed and constructed to perform such experiments irradiating monolayers of cells. Estimates of dose rate at the cell surface were obtained from measurements by a PIPS alpha-particle spectrometer and from calculations by the SRIM 2000, Monte Carlo charged particle transport code. Particle fluence area distributions were measured by solid state nuclear track detectors. The design and dosimetric characterisation of the devices are discussed. c2002 Elsevier Science Ltd. All rights reserved.

Alpha Particles↗
NASA NTRS2012

Understanding Climate Policy Data Needs. NASA Carbon Monitoring System Briefing: Characterizing Flux Uncertainty, Washington D.C., 11 January 2012

Climate policy in the United States is currently guided by public-private partnerships and actions at the local and state levels. This mitigation strategy is made up of programs that focus on energy efficiency, renewable energy, agricultural practices and implementation of technologies to reduce greenhouse gases. How will policy makers know if these strategies are working, particularly at the scales at which they are being implemented? The NASA Carbon Monitoring System (CMS) will provide information on carbon dioxide fluxes derived from observations of earth's land, ocean and atmosphere used in state of the art models describing their interactions. This new modeling system could be used to assess the impact of specific policy interventions on CO2 reductions, enabling an iterative, results-oriented policy process. In January of 2012, the CMS team held a meeting with carbon policy and decision makers in Washington DC to describe the developing modeling system to policy makers. The NASA CMS will develop pilot studies to provide information across a range of spatial scales, consider carbon storage in biomass, and improve measures of the atmospheric distribution of carbon dioxide. The pilot involves multiple institutions (four NASA centers as well as several universities) and over 20 scientists in its work. This pilot study will generate CO2 flux maps for two years using observational constraints in NASA's state-of -the-art models. Bottom-up surface flux estimates will be computed using data-constrained land and ocean models; comparison of the different techniques will provide some knowledge of uncertainty in these estimates. Ensembles of atmospheric carbon distributions will be computed using an atmospheric general circulation model (GEOS-5), with perturbations to the surface fluxes and to transport. Top-down flux estimates will be computed from observed atmospheric CO2 distributions (ACOS/GOSAT retrievals) alongside the forward-model fields, in conjunction with an inverse approach based on the CO2 model of GEOS ]Chem. The forward model ensembles will be used to build understanding of relationships among surface flux perturbations, transport uncertainty and atmospheric carbon concentration. This will help construct uncertainty estimates and information on the true spatial resolution of the top-down flux calculations. The relationship between the top-down and bottom-up flux distributions will be documented. Because the goal of NASA CMS is to be policy relevant, the scientists involved in the flux modeling pilot need to understand and be focused on the needs of the climate policy and decision making community. If policy makers are to use CMS products, they must be aware of the modeling effort and begin to design policies that can be evaluated with information. Improving estimates of carbon sequestered in forests, for example, will require information on the spatial variability of forest biomass that is far more explicit than is presently possible using only ground observations. Carbon mitigation policies being implemented by cities around the United States could be designed with the CMS data in mind, enabling sequential evaluation and subsequent improvements in incentives, structures and programs. The success of climate mitigation programs being implemented in the United States today will hang on the depth of the relationship between scientists and their policy and decision making counterparts. Ensuring that there is two-way communication between data providers and users is important for the success both of the policies and the scientific products meant to support them..

Brown, Molly E.↗