Engineering topics

Anderson, Kevin K

Publications and source records attributed to Anderson, Kevin K.

10 records

DOE OSTI2012

Calibrating Multi-machine Power System Parameters with the Extended Kalman Filter

Large-scale renewable resources and novel smart-grid technologies continue to increase the complexity of power systems. As power systems continue to become more complex, accurate modeling for planning and operation becomes a necessity. Inaccurate system models would result in an unreliable assessment of system security conditions and could cause large-scale blackouts. This motivates the need for model parameter calibration, since some or all of the model parameters could be unknown or inaccurate. In this paper, the extended Kalman filter is used to calibrate the parameters of a multi-machine power system. The calibration performance is tested under varying fault locations, parameter errors and measurement noise giving an insight into how many generators and which generators could be difficult to calibrate.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2012

Disaggregating measurement uncertainty from population variability and Bayesian treatment of uncensored results

In making low-level radioactivity measurements of populations, it is commonly observed that a substantial portion of net results are negative. Furthermore, the observed variance of the measurement results arises from a combination of measurement uncertainty and population variability. This paper presents a method for disaggregating measurement uncertainty from population variability to produce a probability density function (PDF) of possibly true results. To do this, simple, justifiable, and reasonable assumptions are made about the relationship of the measurements to the measurands (the 'true values'). The measurements are assumed to be unbiased, that is, that their average value is the average of the measurands. Using traditional estimates of each measurement's uncertainty to disaggregate population variability from measurement uncertainty, a PDF of measurands for the population is produced. Then, using Bayes's theorem, the same assumptions, and all the data from the population of individuals, a prior PDF is computed for each individual's measurand. These PDFs are non-negative, and their average is equal to the average of the measurement results for the population. The uncertainty in these Bayesian posterior PDFs is all Berkson with no remaining classical component. The methods are applied to baseline bioassay data from the Hanford site. The data include 90Sr urinalysis measurements on 128 people, 137Cs in vivo measurements on 5,337 people, and 239Pu urinalysis measurements on 3,270 people. The method produces excellent results for the 90Sr and 137Cs measurements, since there are nonzero concentrations of these global fallout radionuclides in people who have not been occupationally exposed. The method does not work for the 239Pu measurements in non-occupationally exposed people because the population average is essentially zero.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2011

Distributed Dynamic State Estimation with Extended Kalman Filter

Increasing complexity associated with large-scale renewable resources and novel smart-grid technologies necessitates real-time monitoring and control. Our previous work applied the extended Kalman filter (EKF) with the use of phasor measurement data (PMU) for dynamic state estimation. However, high computation complexity creates significant challenges for real-time applications. In this paper, the problem of distributed dynamic state estimation is investigated. One domain decomposition method is proposed to utilize decentralized computing resources. The performance of distributed dynamic state estimation is tested on a 16-machine, 68-bus test system.

42 ENGINEERING↗

DOE OSTI2011

PMU Placement for Dynamic State Tracking of Power Systems

Accurately tracking the state variables (rotor angle and speed) is a necessity for monitoring system stability conditions and assessing the risks of large-scale system collapse. This paper explores how the number and locations of PMUs installed in the system are determined to ensure satisfactory state tracking performance. A search algorithm is presented for determining PMU placement (location and quantity). The algorithm determines a placement that gives small tracking error in polynomial time. A modified, scalable algorithm is also presented. Observability in the presence of faults is considered. Simulation results for a 16-machine and a 50-machine system are provided.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2011

Lead Slowing-Down Spectrometry for Spent Fuel Assay: FY11 Status Report

Executive Summary Developing a method for the accurate, direct, and independent assay of the fissile isotopes in bulk materials (such as used fuel) from next-generation domestic nuclear fuel cycles is a goal of the Office of Nuclear Energy, Fuel Cycle R&D, Material Protection and Control Technology (MPACT) Campaign. To meet this goal, MPACT supports a multi-institutional collaboration to study the feasibility of Lead Slowing Down Spectroscopy (LSDS). This technique is an active nondestructive assay method that has the potential to provide independent, direct measurement of Pu and U isotopic masses in used fuel with an uncertainty considerably lower than the approximately 10% typical of today’s confirmatory assay methods. This document is a progress report for FY2011 collaboration activities. Progress made by the collaboration in FY2011 continues to indicate the promise of LSDS techniques applied to used fuel. PNNL developed an empirical model based on calibration of the LSDS to responses generated from well-characterized used fuel. The empirical model demonstrated the potential for the direct and independent assay of the sum of the masses of 239Pu and 241Pu to within approximately 3% over a wide used fuel parameter space. Similar results were obtained using a perturbation approach developed by LANL. Benchmark measurements have been successfully conducted at LANL and at RPI using their respective LSDS instruments. The ISU and UNLV collaborative effort is focused on the fabrication and testing of prototype fission chambers lined with ultra-depleted 238U and 232Th, and uranium deposition on a stainless steel disc using spiked U3O8 from room temperature ionic liquid was successful, with improving thickness obtained. In FY2012, the collaboration plans a broad array of activities. PNNL will focus on optimizing its empirical model and minimizing its reliance on calibration data, as well continuing efforts on developing an analytical model. Additional measurements are planned at LANL and RPI. LANL measurements will include a Pu sample, which is expected to provide more counts at longer slowing-down times to help identify discrepancies between experimental data and MCNPX simulations. RPI measurements will include the assay of an entire fresh fuel assembly for the study of self-shielding effects as well as the ability to detect diversion by detecting a missing fuel pin in the fuel assembly. The development of threshold neutron sensors will continue, and UNLV will calibrate existing ultra-depleted uranium deposits at ISU.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2010

PMU Placement for Enhancing Dynamic Observability of a Power Grid

Power grids are operated in an increasingly complicated environment. However, operators lack effective and accurate tools for real-time monitoring and control of power systems. The U.S. Department of Energy, along with several utilities and system operators, is making a major $108 million investment in the Western Interconnection for phasor measurement unit (PMU) installation and phasor application development. This phasor measurement network opens up many opportunities for the estimation and prediction of power system states in real time, which enable operators to evaluate the system dynamic security in advance and allow them more time to respond to disturbances. Kalman filter based dynamic state estimation offers a solution suitable for this purpose. Our work indicates that the performance of Kalman filters in dynamic state estimation would degrade if PMU measurements cannot adequately capture the system dynamics. This paper develops a framework to identify how to place PMUs to improve dynamic observability of the power grid. Simulation results validate the concept, and the guidelines for PMU placement are derived.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2010

Acceptance sampling using judgmental and randomly selected samples

We present a Bayesian model for acceptance sampling where the population consists of two groups, each with different levels of risk of containing unacceptable items. Expert opinion, or judgment, may be required to distinguish between the high and low-risk groups. Hence, high-risk items are likely to be identifed (and sampled) using expert judgment, while the remaining low-risk items are sampled randomly. We focus on the situation where all observed samples must be acceptable. Consequently, the objective of the statistical inference is to quantify the probability that a large percentage of the unsampled items in the population are also acceptable. We demonstrate that traditional (frequentist) acceptance sampling and simpler Bayesian formulations of the problem are essentially special cases of the proposed model. We explore the properties of the model in detail, and discuss the conditions necessary to ensure that required samples sizes are non-decreasing function of the population size. The method is applicable to a variety of acceptance sampling problems, and, in particular, to environmental sampling where the objective is to demonstrate the safety of reoccupying a remediated facility that has been contaminated with a lethal agent.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2010

Predicting the detectability of thin gaseous plumes in hyperspectral images using basis vectors

This paper describes a new method for predicting the detectability of thin gaseous plumes in hyperspectral images. The novelty of this method is the use of basis vectors for each of the spectral channels of a collection instrument to calculate noise-equivalent concentration-pathlengths instead of matching scene pixels to absorbance spectra of gases in a library. This method provides insight into regions of the spectrum where gas detection will be relatively easier or harder, as influenced by ground emissivity, temperature contrast, and the atmosphere. We relate a three-layer physics-based radiance model to basis vector noise-equivalent concentration-pathlengths, to signal-to-noise ratios, and finally to minimum detectable concentration-pathlengths. We illustrate the method using an Airborne Hyperspectral Imager image. Our results show that data collection planning could be in°uenced by information about when potential plumes are likely to be over background segments that are most conducive to detection.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2010

ADVANCEMENTS IN TIME-SPECTRA ANALYSIS METHODS FOR LEAD SLOWING-DOWN SPECTROSCOPY

Direct measurement of Pu in spent nuclear fuel remains a key challenge for safeguarding nuclear fuel cycles of today and tomorrow. Lead slowing-down spectroscopy (LSDS) is an active nondestructive assay method that has the potential to provide independent, direct measurement of Pu and U isotopic mass with an uncertainty lower than the approximately 10 percent typical of today’s confirmatory assay methods. Pacific Northwest National Laboratory’s (PNNL) previous work to assess the viability of LSDS for the assay of pressurized water reactor (PWR) assemblies indicated that the method could provide direct assay of Pu-239 and U-235 (and possibly Pu-240 and Pu-241) with uncertainties less than a few percent, assuming suitably efficient instrumentation, an intense pulsed neutron source, and improvements in the time-spectra analysis methods used to extract isotopic information from a complex LSDS signal. This previous simulation-based evaluation used relatively simple PWR fuel assembly definitions (e.g. constant burnup across the assembly) and a constant initial enrichment and cooling time. The time-spectra analysis method was founded on a preliminary analytical model of self-shielding intended to correct for assay-signal nonlinearities introduced by attenuation of the interrogating neutron flux within the assembly.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2010

Time-Spectral Analysis Methods for Spent Fuel Assay Using Lead Slowing-Down Spectroscopy of Spent Fuel

Nondestructive techniques for measuring the mass of fissile isotopes in spent nuclear fuel is a considerable challenge in the safeguarding of nuclear fuel cycles. A nondestructive assay technology that could provide direct measurement of fissile mass, particularly for the plutonium (Pu) isotopes, and improve upon the uncertainty of today’s confirmatory methods is needed. Lead slowing-down spectroscopy (LSDS) has been studied for the spent fuel application previously, but the nonlinear effects of assembly self shielding (of the interrogating neutron population) have led to discouraging assay accuracy for realistic pressurized water reactor fuels. In this paper, we describe the development of time-spectral analysis algorithms for LSDS intended to overcome these self-shielding effects. The algorithm incorporates the tabulated energy-dependent cross sections from key fissile and absorbing isotopes, but leaves their mass as free variables. Multi-parameter regression analysis is then used to directly calculate not only the mass of fissile isotopes in the fuel assembly (e.g., Pu-239, U-235, and Pu-241), but also the mass of key absorbing isotopes such as Pu-240 and U-238. Modeling-based assay results using a first-order self-shielding relationship indicate that LSDS has the potential to directly measure fissile isotopes with less than 5% average relative error, over a wide fuel burnup range. Shortcomings in the first-order self-shielding model and methods to improve the formulation are described.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗