iii Executive SummaryThe purpose of this research is to develop and maintain numerical groundwater flow and transport models that can be used to refine the conceptual site model for groundwater beneath the 300 Area, and to assist in evaluating alternative remediation technologies focused on the 300 Area uranium plume. Groundwater flow rates and directions in the 300 Area are very dynamic because of the high hydraulic conductivities, along with the large daily, weekly, and seasonal fluctuations in the Columbia River stage. Quantifying the dynamics of groundwater flow and transport in the 300 Area aquifer will help understand the significant seasonal variability of uranium plume concentrations seen in biannual groundwater monitoring, and will help evaluate remediation options. Groundwater flow rates are very high in the upper portion of the 300 Area unconfined aquifer (within the Hanford formation), with velocities up to 10 to 15 m/d (35 to 50 ft/d) based on a tracer test and limited plume-migration data. Variability in the groundwater-flow directions is apparent from analysis of hourly and subhourly automated water-level measurements from monitoring networks established in the 300 Area. Generalized flow directions in the area between the north and south process ponds are toward the east to south, with the directions changing toward the south and west during periods of increases in the river stage (daily and seasonal).High-resolution water level and river stage data were required to simulate the dynamics of the 300 Area aquifer. Two scales of groundwater flow and transport models were developed based on the availability of high-resolution water-level monitoring data. A larger-domain model was developed that includes the 300 Area and extends north and south using data from the early 1990s water-level monitoring network. A smaller domain model was developed for a portion of the large scale model domain in the north of the 300 Area that used water-level data from another smaller monitoring well network that was established in 2004. These models focus on the highly permeable upper portion of the unconfined aquifer within the Hanford formation that has hydraulic conductivity values 2 to 3 orders of magnitude higher than the underlying Ringold Formation aquifers. These models simulate saturated and unsaturated groundwater flow and transport with the STOMP code, which was developed at Pacific Northwest National Laboratory. 1The hydrostratigraphy, topography, and bathymetry for the three-dimensional models used a consistent framework using EarthVision software.The model domains include the lower portion of the vadose zone to encompass the range of river stage and water- The hydrostratigraphic units were determined from previously published interpretations of the 300 Area, along with data from additional wells installed since those studies. A reanalysis of some of the older geologic unit picks from well logs in the area, along with using geophysical logs, was conducted based on the detailed knowledge gained from the 300 ...
In Energy Management Systems, contingency analysis is commonly performed for identifying and mitigating potentially harmful power grid component failures. The exponentially increasing combinatorial number of failure modes imposes a significant computational burden for massive contingency analysis. It is critical to select a limited set of highimpact contingency cases within the constraint of computing power and time requirements to make it possible for real-time power system vulnerability assessment. In this paper, we present a novel application of parallel betweenness centrality to power grid contingency selection. We cross-validate the proposed method using the model and data of the western US power grid, and implement it on a Cray XMT system -a massively multithreaded architecture -leveraging its advantages for parallel execution of irregular algorithms, such as graph analysis. We achieve a speedup of 55 times (on 64 processors) compared against the single-processor version of the same code running on the Cray XMT. We also compare an OpenMP-based version of the same code running on an HP Superdome shared-memory machine. The performance of the Cray XMT code shows better scalability and resource utilization, and shorter execution time for large-scale power grids. This proposed approach has been evaluated in PNNL's Electricity Infrastructure Operations Center (EIOC). It is expected to provide a quick and efficient solution to massive contingency selection problems to help power grid operators to identify and mitigate potential widespread cascading power grid failures in real time.
this paper is a result of ongoing activity carried out by Understanding, Prediction, Mitigation and Restoration of Cascading Failures Task Force under IEEE Computer Analytical Methods Subcommittee (CAMS). The task force's previous papers [1, 2] are focused on general aspects of cascading outages such as understanding, prediction, prevention and restoration from cascading failures. This is the second of two new papers, which extend this previous work to summarize the state of the art in cascading failure risk analysis methodologies and modeling tools. The first paper reviews the state of the art in methodologies for performing risk assessment of potential cascading outages [3]. This paper describes the state of the art in cascading failure modeling tools, documenting the view of experts representing utilities, universities and consulting companies. The paper is intended to constitute a valid source of information and references about presently available tools that deal with prediction of cascading failure events. This effort involves reviewing published literature and other documentation from vendors, universities and research institutions. The assessment of cascading outages risk evaluation is in continuous evolution. Investigations to gain even better understanding and identification of cascading events are the subject of several research programs underway aimed at solving the complexity of these events that electrical utilities face today. Assessing the risk of cascading failure events in planning and operation for power transmission systems require adequate mathematical tools/software.
Printed in the United Executive SummarySmall signal stability problems are one of the major threats to grid stability and reliability in the U.S. power grid. An undamped mode can cause growing oscillations and may result in system breakups and large-scale blackouts. There have been several incidents of system-wide oscillations. Of those incidents, the most notable is the August 10, 1996 western system breakup, a result of undamped system-wide oscillations. Significant efforts have been devoted to monitoring system oscillatory behavior from measurements in the past 20 years. The deployment of phasor measurement units (PMU) provides highprecision, time-synchronized data needed for detecting oscillation modes. Measurement-based modal analysis, also known as ModeMeter, uses real-time phasor measurements to identify system oscillation modes and their damping. Low damping indicates potential system stability issues. Modal analysis has been demonstrated with phasor measurements to have the capability of estimating system modes from oscillation signals, probing data, and ambient data.With more and more phasor measurements available and ModeMeter techniques maturing, there is yet a need for methods to bring modal analysis from monitoring to actions. The methods should be able to associate low damping with grid operating conditions, so operators or automated operation schemes can respond when low damping is observed. The work presented in this report aims to develop such a method and establish a Modal Analysis for Grid Operation (MANGO) procedure to provide recommended actions (such as generation re-dispatch or load reduction), and aid grid operation decision making for mitigating inter-area oscillations. This project directly contributes to the Department of Energy Transmission Reliability Program's goal of "improving reliability of the nation's electricity delivery infrastructure."The fundamental part of the work explores the relationship between low damping and grid operating conditions to develop recommended actions for damping improvement, and therefore reduce the chance of system breakup and power outages. Different from power system stabilizers and other modulation control mechanisms, MANGO improves damping through operating point adjustments. Traditionally, the modulation-based methods do not change the system's operating point, but improve damping through automatic feedback control. Figure S-1 illustrates the difference of these two types of damping improvement methods. MANGO, represented in red, and modulation control, represented in magenta, are complementary towards the same goal.MANGO is a measurement-based procedure, as shown in Figure S-2. As the first stage of development, the MANGO procedure is targeted to have operators in the loop. Practical implementation is envisioned to be achieved by integrating MANGO recommendations into existing operating procedures. The MANGO model can be updated according to the current measurement and mode estimation results. Operators are included into the loop to bring in exp...
As the power grid technology evolution and information technology revolution converge, power grids are witnessing a revolutionary transition, represented by emerging grid technologies and large scale deployment of new sensors and meters in networks. This transition brings opportunities, as well as computational challenges in the field of power grid analysis and operation. This paper presents some research outcomes in the areas of parallel state estimation using the preconditioned conjugated gradient method, parallel contingency analysis with a dynamic load balancing scheme and distributed system architecture. Based on this research, three types of computational challenges are identified: highly coupled applications, loosely coupled applications, and centralized and distributed applications. Recommendations for future work for power grid applications are also presented.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.