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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Resource Conservation and Recovery Act General Contingency Plan for Hazardous Waste Treatment, Storage, and Disposal Units at the Y-12 National Security Complex. Revision 12

This document, Y/TS-1015/R12, Resource Conservation and Recovery Act General Contingency Plan for Hazardous Waste Treatment, Storage, and Disposal Units at the Y-12 National Security Complex, is for reference purposes. It is a consolidation of the August 10, 2018, versions of Attachment 6, “Contingency Plan,” from Tennessee Hazardous Waste Management Permits TNHW-122 and TNHW-127. It is not intended to supersede any requirements in these permits and any differences are unintentional. The decision to implement this contingency plan, as part of the Emergency Plan, depends upon whether an imminent or actual incident involving a RCRA treatment, storage, or disposal unit could threaten human health or the environment.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

Contingency Contractor Optimization Engineering Prototype – Release 2.3 (Phase 3 Extension – Training Examples)

This document provides training examples to provide users practice in using the tool. Detailed instructions on how to use the tool can be found in the User Manual (SAND2015-6028).The Contingency Contractor Optimization project is intended to address former Secretary Gates’ mandate in a January 2011 memo and DoDI 3020.41 by delivering a centralized strategic planning tool that allows senior decision makers to quickly and accurately assess the impacts, risks, and mitigation strategies associated with utilizing contract support. Based on an electronic storyboard prototype developed in Phase 2, the CCOT-P engineering prototype was refined in Phase 3 of the OSD ATL Contingency Contractor Optimization project to support strategic planning for contingency contractors. CCOT-P uses a model to optimize the total workforce mix by minimizing the combined total costs for the selected mission scenarios. The model will optimize the match of personnel groups (military, DoD civilian, and contractors) and capabilities to meet the mission requirements as effectively as possible, based on risk, cost, and other requirements.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2021

Topological Machine Learning Methods for Power System Responses to Contingencies: Preprint

While deep learning tools, coupled with the emerging machinery of topological data analysis, are proven to deliver various performance gains in a broad range of applications, from image classification to biosurveillance to blockchain fraud detection, their utility in areas of high societal importance such as power system modeling and, particularly, resilience quantification in the energy sector yet remain untapped. To provide fast acting synthetic regulation and contingency reserve services to the grid while having minimal disruptions on customer quality of service, we propose a new topologybased system that depends on neural network architecture for impact metrics classification and prediction in power systems. This novel topology-based system allows one to evaluate the impact of three power system contingency types, namely, in conjunction with transmission lines, transformers, and transmission lines combined with transformers. We show that the proposed new neural network architecture equipped with local topological measures facilitates both more accurate classification of unserved load as well as the amount of unserved load. In addition, we are able to learn complex relationships between electrical properties and local topological measurements on the simulated response to contingencies for NREL-SIIP power system.

graph theory↗
DOE OSTI2016

Contingencies in Decommissioning Cost Evaluations - Panel Session 24

Contingency costs apply to unforeseen, uncertain and unpredictable conditions, typically encountered during the decommissioning activities (known unknowns). Outside spent fuel management, the dismantling activities in the controlled area constitute the largest contributor to project risk and decommissioning cost. Using data from previous proven experience on site help minimize the contingencies and provide more accurate cost estimates. Technology improvement leads to cost and contingency reduction.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2015

UK regulatory review of the double contingency principle in criticality safety - 14379

The UK's regulatory regime is based on Licence Conditions (LCs) attached to a Nuclear Site Licence (NSL) and is non-prescriptive in nature. The law requires licensees to reduce health and safety risks to workers and the public 'so far as is reasonability practicable' (SFAIRP), and this framework provides licensees with flexibility to achieve this. Guidance for inspectors on the assessment of nuclear safety cases has been published in Office for Nuclear Regulation's (ONR) Safety Assessment Principles (SAPs) and supporting Technical Assessment Guides (TAGs). These guidance documents have recently been reviewed in the light of the Fukushima accident. The opportunity has also been taken to reconsider the use of the Double Contingency Principle used in criticality safety cases, an approach commonly regarded as the preferred means of criticality control internationally and featured in the SAPs and TAGs. Licensees in the UK have adopted several approaches in nuclear criticality safety cases based upon a combination of deterministic and probabilistic safety cases using the Double Contingency Principle and Design Basis Analysis. ONR has developed a targeted intervention to sample a number of nuclear safety cases in order to test the adequacy of methodologies used to secure nuclear criticality safety. This paper reports the results of this intervention and considers the need to review the advice currently given by the UK nuclear regulator, including on use of the Double Contingency Principle. (authors)

42 ENGINEERING↗
DOE OSTI2017

Smart Sampling and HPC-based Probabilistic Look-ahead Contingency Analysis Implementation and its Evaluation with Real-world Data

This paper describes a probabilistic look-ahead contingency analysis application that incorporates smart sampling and high-performance computing (HPC) techniques. Smart sampling techniques are implemented to effectively represent the structure and statistical characteristics of uncertainty introduced by different sources in the power system. They can significantly reduce the data set size required for multiple look-ahead contingency analyses, and therefore reduce the time required to compute them. High-performance-computing (HPC) techniques are used to further reduce computational time. These two techniques enable a predictive capability that forecasts the impact of various uncertainties on potential transmission limit violations. The developed package has been tested with real world data from the Bonneville Power Administration. Case study results are presented to demonstrate the performance of the applications developed.

high performance computing↗
DOE OSTI2019

Dynamic Contingency Analysis Tool 2.0 User Manual with Test System Examples

This document introduces Version 2 of the Dynamic Contingency Analysis Tool (DCAT) software package developed by Pacific Northwest National Laboratory and serves as a guide for using this package to conduct cascading failure simulations for the electric power system. The DCAT is an open-platform and publicly available software; it is intended to help develop applications that aim to improve the capabilities of power system planning engineers to assess the impact and likelihood of extreme contingencies and potential cascading events across their systems and interconnections. Outputs from the DCAT will support finding mitigating actions to reduce the risk of cascading outages in technically sound and effective ways. This manual provides detailed instructions on how to use this tool on multicore Windows workstations or servers. In the public version of DCAT, several improvements have been made over the previous version: (1) it was modularized; (2) a graphical user interface (GUI) was developed; (3) a new version of the MPjobs parallel processing module was incorporated; and (4) a batch-processing function was added. The features of the DCAT GUI are described, including some examples of how to use the GUI to perform simulations. A full explanation of the DCAT methodology is available in the Phase 1 report.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

An Improved Transmission Switching Algorithm for Managing Post-(N-1) Contingencies in Electricity Networks

In this presentation, we detail the shortcomings of existing transmission switching (TS) methodologies for preventing post-contingency loss of load in wide area electric power networks. Following that, we present a bi-level algorithm as an improvement to the state of the art. We show proof-of-concept level results that indicate computational viability, fast solutions, and the ability to pick the same best candidate as non computationally viable methods. Further, our method also minimizes load shedding after the contingency, thus enhancing the reliability and security of electricity supply. We also include a futuristic scenario of increased renewables and decreased natural gas sourced generators to show promising results. We grant permission for our presentation to be recorded and uploaded by the conference organizers.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

A Generic Advanced Computing Framework for Executing Windows-based Dynamic Contingency Analysis Tool in Parallel on Cluster Machines

Dynamic contingency analysis tool (DCAT) has been developed to assess the impact and likelihood of extreme contingencies and potential cascading events across their systems and interconnections. By including more customized protection models and corrective actions into the Windows-based commercial tools, DCAT can help operators understand the cascading behavior and find mitigation approaches to reduce the risk of cascading outages in a more realistic manner. In order to further enhance the capability of DCAT, this paper presents a design of an advanced computing framework that enables DCAT to run on a cluster machine to improve its computational performance. This framework is generic and can be applied to other Windows-based simulation tools to fill the technical gap of applying advanced computing technology to vendors' Windows-based tools. The preliminary tests using medium to large power systems have shown the effectiveness of this framework and its potential for accelerating the adoption of advanced computing in utilities.

Advanced computing, dynamic contingency analysis, ↗
DOE OSTI2020

Probabilistic Look-ahead Contingency Analysis Integration with Commercial Tool and Practical Data

This paper presents an initial effort of integrating a smart sampling-based probabilistic look-ahead contingency analysis algorithm with General Electric (GE) Grid Solutions’ commercial energy management system (EMS) tool as a proof-of-concept for a seamless research tool integration using real world large-scale grid data. With the increasing impact of random forces such as variable generation and load, their stochastic behaviors cannot be ignored. However, the current practices are still dominated by deterministic tools. They are becoming increasingly inadequate for the future grid. The developed look-ahead contingency analysis algorithm incorporates forecast errors of variable energy and load to address the challenges brought by the increasing uncertainty of power system. The algorithm can reveal the potential violations caused by the variance of variable energy and load that are not normally detected by traditional deterministic approaches. To test its performance under practical environments ( real data with real commercial tool), significant efforts have been made to prepare test cases, modify GE EMS tool, and adapt an extreme value distribution algorithm to analyze the GE EMS’s violation-only outputs. The test results clearly demonstrate the effectiveness of the developed algorithm as new transformer violations that were not previously detected have been identified. This performance provides better situational awareness to engineers for their decision-making process under uncertainty. Moreover, with the discussion of computational performance and future work, this paper has shown a clear path for integrating the probabilistic algorithm with commercial tools to make us better equipped for the changing power system.

Modeling and simulation of power systems, constrai↗
DOE OSTI2019

Contingency rules for pathogen competition and antagonism in a genetically based, plant defense hierarchy

Abstract Plant defense against pathogens includes a range of mechanisms, including, but not limited to, genetic resistance, pathogen‐antagonizing endophytes, and pathogen competitors. The relative importance of each mechanism can be expressed in a hierarchical view of defense. Several recent studies have shown that pathogen antagonism is inconsistently expressed within the plant defense hierarchy. Our hypothesis is that the hierarchy is governed by contingency rules that determine when and where antagonists reduce plant disease severity. Here, we investigated whether pathogen competition influences pathogen antagonism using Populus as a model system. In three independent field experiments, we asked whether competition for leaf mesophyll cells between a Melampsora rust pathogen and a microscopic, eriophyid mite affects rust pathogen antagonism by fungal leaf endophytes. The rust pathogen has an annual, phenological disadvantage in competition with the mite because the rust pathogen must infect its secondary host in spring before infecting Populus . We varied mite–rust competition by utilizing Populus genotypes characterized by differential genetic resistance to the two organisms. We inoculated plants with endophytes and allowed mites and rust to infect plants naturally. Two contingency rules emerged from the three field experiments: (a) Pathogen antagonism by endophytes can be preempted by host genes for resistance that suppress pathogen development, and (b) pathogen antagonism by endophytes can secondarily be preempted by competitive exclusion of the rust by the mite. Synthesis : Our results point to a Populus defense hierarchy with resistance genes on top, followed by pathogen competition, and finally pathogen antagonism by endophytes. We expect these rules will help to explain the variation in pathogen antagonism that is currently attributed to context dependency.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Integrated State Estimation and Contingency Analysis Software Implementation using High Performance Computing Techniques

Power system simulation tools are traditionally developed in sequential mode and codes are optimized for single core computing only. However, the increasing complexity in the power grid models requires more intensive computation. The traditional simulation tools will soon not be able to meet the grid operation requirements. Therefore, power system simulation tools need to evolve accordingly to provide faster and better results for grid operations. This paper presents an integrated state estimation and contingency analysis software implementation using high performance computing techniques. The software is able to solve large size state estimation problems within one second and achieve a near-linear speedup of 9,800 with 10,000 cores for contingency analysis application. The performance evaluation is presented to show its effectiveness.

Chen, Yousu↗
DOE OSTI2018

Fuel properties and steam reactivity of solid waste streams from contingency bases

Highlights: • Composite waste fuels were prepared for characterizing fuel property and reactivity. • Characterization of the composite fuels can be predicted by individual components. • A simple methodology for characterizing multi-component solid wastes was validated. • Plastic components increase carbon content and HHV of solid waste fuels. • Effects of fuel composition on syngas production and composition were explored. - Abstract: The solid waste generated from military contingency bases (CBs) is a potential fuel for appropriately-scaled, waste to energy (WTE) systems. To inform WTE system design, fuel properties of seventeen components of synthetic contingency-base waste recipes from the literature were characterized for ultimate analysis, heating values, proximate analysis and reactivity in a steam atmosphere at three temperature typical of gasification conditions. A simple mathematical approach was applied to predict the properties and reactive behavior of composite mixtures using the weighted sum of the corresponding components, assuming negligible interaction between components. The method was validated using prepared composite mixture samples. In addition, chemical equilibrium calculations for steam gasification of the composite samples were conducted to explore the effects of waste composition variability on syngas production and composition.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2017

Modeling Zone-3 Protection with Generic Relay Models for Dynamic Contingency Analysis

This paper presents a cohesive approach for calculating and coordinating the settings of multiple zone-3 protections for dynamic contingency analysis. The zone-3 protections are represented by generic distance relay models. A two-step approach for determining zone-3 relay settings is proposed. The first step is to calculate settings, particularly, the reach, of each zone-3 relay individually by iteratively running line open-end fault short circuit analysis; the blinder is also employed and properly set to meet the industry standard under extreme loading conditions. The second step is to systematically coordinate the protection settings of the zone-3 relays. The main objective of this coordination step is to address the over-reaching issues. We have developed a tool to automate the proposed approach and generate the settings of all distance relays in a PSS/E dyr format file. The calculated zone-3 settings have been tested on a modified IEEE 300 system using a dynamic contingency analysis tool (DCAT).

computational modeling↗
DOE OSTI2017

A Study of the Impact of Peak Demand on Increasing Vulnerability of Cascading Failures to Extreme Contingency Events

The vulnerability of large power systems to cascading failures and major blackouts has become evident since the Northeast blackout in 1965. Based on analyses of the series of cascading blackouts in the past decade, the research community realized the urgent need to develop better methods, tools, and practices for performing cascading-outage analysis and for evaluating mitigations that are easily accessible by utility planning engineers. PNNL has developed the Dynamic Contingency Analysis Tool (DCAT) as an open-platform and publicly available methodology to help develop applications that aim to improve the capabilities of power planning engineers to assess the impact and likelihood of extreme contingencies and potential cascading events across their systems and interconnections. DCAT analysis will help identify potential vulnerabilities and allow study of mitigation solutions to reduce the risk of cascading outages in technically sound and effective ways. Using the DCAT capability, we examined the impacts of various load conditions to identify situations in which the power grid may encounter cascading outages that could lead to potential blackouts. This paper describes the usefulness of the DCAT tool and how it helps to understand potential impacts of load demand on cascading failures on the power system.

indexes↗
DOE OSTI2024

Multi-Agent Graph-Attention Deep Reinforcement Learning for Post-Contingency Grid Emergency Voltage Control

Grid emergency voltage control (GEVC) is paramount in electric power systems to improve voltage stability and prevent cascading outages and blackouts in case of contingencies. While most deep reinforcement learning (DRL)-based paradigms perform single agents in a static environment, real-world agents for GEVC are expected to cooperate in a dynamically shifting grid. Moreover, due to high uncertainties from combinatory natures of various contingencies and load consumption, along with the complexity of dynamic grid operation, the data efficiency and control performance of the existing DRL-based methods are challenged. To address these limitations, we propose a multi-agent graph-attention (GATT)-based DRL algorithm for GEVC in multi-area power systems. Here, we develop graph convolutional network (GCN)-based agents for feature representation of the graph-structured voltages to improve the decision accuracy in a data-efficient manner. Furthermore, a cutting-edge attention mechanism concentrates on effective information sharing among multiple agents, synergizing different-sized subnetworks in the grid for cooperative learning. We address several key challenges in the existing DRL-based GEVC approaches, including low scalability and poor stability against high uncertainties. Test results in the IEEE benchmark system verify the advantages of the proposed method over several recent multi-agent DRL-based algorithms.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

A Distributionally Robust Resilience Enhancement Strategy for Distribution Networks Considering Decision-Dependent Contingencies

When performing the resilience enhancement for distribution networks, there are two obstacles to reliably model the uncertain contingencies: 1) decision-dependent uncertainty (DDU) due to various line hardening decisions, and 2) distributional ambiguity due to limited outage information during extreme weather events (EWEs). Here, to address these two challenges, this paper develops scenario-wise decision-dependent ambiguity sets (SWDD-ASs), where the DDU and distributional ambiguity inherent in EWE-induced contingencies are simultaneously captured for each possible EWE scenario. Then, a two-stage tri-level decision-dependent distributionally robust resilient enhancement (DD-DRRE) model is formulated, whose outputs include the optimal line hardening, distributed generation (DG) allocation, and proactive network reconfiguration strategy under the worst-case distributions in SWDD-ASs. Subsequently, the DD-DRRE model is equivalently recast to a mixed-integer linear programming (MILP)-based master problem and multiple scenario-wise subproblems, facilitating the adoption of a customized column-and-constraint generation (C&CG) algorithm. Finally, case studies demonstrate a remarkable improvement in the out-of-sample performance of our model, compared to its prevailing stochastic and robust counterparts. Moreover, the potential values of incorporating the ambiguity and distributional information are quantitatively estimated, providing a useful reference for planners with different budgets and risk-aversion levels.

decision-dependent uncertainty↗