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Big Data, Big Solutions
Data—lots of data—generated in seconds and piling up on the internet, streaming and stored in countless databases. Big data is important for commerce, society and our nation’s security. Yet the volume, velocity, variety and veracity of data is simply too great for any single analyst to make sense of alone. It requires advanced, data-intensive computing. Simply put, data-intensive computing is the use of sophisticated computers to sort through mounds of information and present analysts with solutions in the form of graphics, scenarios, formulas, new hypotheses and more. This scientific capability is foundational to PNNL’s energy, environment and security missions. Senior Scientist and Division Director Bill Pike and his team are developing analytic tools that are used to solve important national challenges, including cyber systems defense, power grid control systems, intelligence analysis, climate change and scientific exploration.
A 4 GS/s Feedback Processing System for Control of Intra-Bunch Instabilities
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A Touch Panel System for Control Applications
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An Active Feedback System to Control Synchrotron Oscillations in the SLC Damping Rings
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A FORMAL APPROACH TO THE DESIGN OF MULTIBUNCH FEEDBACK SYSTEMS: LQG CONTROLLERS
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Architecture and technology of 500 Msample/s feedback systems for control of coupled-bunch instabilities
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Power System Damping Control via Current Injections from Distributed Energy Storage.
Abstract not provided.
Power System Damping Control via Current Injections from Distributed Energy Storage.
Abstract not provided.
Blockchain: Next Generation Supply Chain Security for Energy Infrastructure and NERC Critical Infrastructure Protection (CIP) Compliance
The U.S. power grid is a complex system of systems that requires a secure, reliable and trustworthy global supply chain. This is especially true for the grid’s increasing number of networked energy delivery system (EDS) and industrial control systems (ICS) and associated vendors, distributers, integrators and end users. Grid modernization has increased the use of “smart” energy devices that network, digitize, automate and increasingly converge the cyber-physical energy supply chain. In this Energy Internet of Things (EIoT) environment there is an increasing number of both critical cyber assets as well as data speed and size requirements, creating new cyber supply chain security and North American Electric Reliability Corporation (NERC) CIP compliance challenges for utilities, regulators and vendors. In realization of these goals, improvements are needed in the process and technology to better monitor, audit and realize cyber security and compliance goals in complex EIoT environments. This paper explores how blockchain technology may present a disruptive solution to facilitate NERC CIP compliance and increase the security of the electricity infrastructure supply chain through a cryptographically signed distributed ledger that provides increased data provenance, attribution and auditability.
Distribution power system fault control apparatus and method
A method includes detecting a fault in a grid coupled to a distribution power network, the distribution power network comprising a distribution feeder, a plurality of distributed energy resources (DERs) coupled to the distribution feeder and a reference point of applicability (RPA) associated with the plurality of DERs, and in response to detecting the fault, determining an error voltage at the RPA, converting the error voltage into an error signal, broadcasting the error signal to the plurality of DERs, and based on the error signal, reducing the error voltage at the RPA by injecting a plurality of currents from the plurality of DERs to the distribution feeder.
Effectiveness And Nonlinear Characterization Of Energy Harvesting Absorbers With Stoppers In Controlling Dynamical Systems.
Abstract not provided.
Language-Theoretic Data Analysis to Support ICS Protocol Baselining
Critical infrastructure stakeholders need to baseline their systems to understand expected protocol communications. Baseline behaviors may vary based on operational context. Expected operations during a maintenance window, for example, may be different from normal operations. Furthermore, constructing system baselines for Industrial Control Systems (ICS) is difficult and time-consuming. ICS processes generate artifacts expressed across heterogeneous data sources such as network traffic and device logs. This paper explores the hypothesis that such ICS artifacts form a language in the language-theoretic sense. From a theoretical perspective, the variety of implementations of ICS protocols and constrained environment of OT networks provide a rich application domain for language-theoretic approaches. We present several use cases related to the practical construction of system baselines: grammars for data fusion, language dialects for device fingerprinting, and security automata for system baselining
Maintenance of the National Ignition Facility (NIF) Controls Hardware System
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Are System Baselines within OT Environments Feasible?
Critical infrastructure stakeholders need to baseline their systems to understand expected protocol communications.Baseline behaviors may vary based on operational context.Expected operations during a maintenance window, for example, may be different from normal operations.Furthermore, constructing system baselines for Industrial Control Systems (ICS) is difficult and time-consuming.ICS processes generate artifacts expressed across heterogeneous data sources such as network and device logs. There needs to be a corpus of data in order to develop and compare methods that evaluate the feasibility, performance, and generality of approaches to construct baselines for ICS events. Standalone repositories of network packet captures are insufficient to develop methods to classify or recognize operational events expressed across multiple data sources. Moreover, static data corpora do not enable researchers to compare the impact of changing the underlying system for which a baseline is being constructed and this limits the ability to evaluate the performance of system baselines given system changes (e.g. patches, configuration, maintenance events). In order to address these limitations within the community, this talk intends to promote discussion about the state of the practice of constructing baselines. In this manner, we can continue to understand requirements within industry that are not being met by current approaches to baseline construction. This talk builds on two previous talks on the topic of system baselines for OT environments. First, Weaver co-presented at the RSA Conference ICS Sandbox with Dan Gunter. The talk confirmed the need within industry to construct baselines across multiple types of data sources relative to the semantics of specific business processes. Second, Weaver presented at IEEE Security and Privacy Workshop on Language-Theoretic Security.
Recent Advancements and Prospects of Chemical Heat Pumps for Temperature Amplification for Nuclear Process Heat Applications
The energy economy is continually evolving, particularly in terms of primary energy sources, their conversions to useful forms such as electricity and heat, and their utilization in different sectors, in response to socio-political factors. Because nuclear energy source is a clean and non-carbon-emitting energy source, it is crucial to consider its role in the evolution of the energy economy. Integrated Energy Systems (IES) are collaboratively controlled systems that can dynamically apportion thermal and/or electrical energy to promote the production of various energy products and have the potential to reduce greenhouse gas (GHG) emissions, improve energy efficiency, improve electrical grid dependability, and enhance energy economics. To realize the benefits of IES with the current reactor fleets, selection and development of a complimentary temperature upgrading technology are necessary for providing process heat and improving economics.
Resilience for Advanced Distributed Wind Systems: Identifying the resilience benefits of advanced controls and hybrid systems for distributed wind
Under the Department of Energy (DOE) Wind Energy Technologies Office (WETO), Idaho National Laboratory (INL) has been tasked with defining the resilience benefits of distributed wind systems for the Microgrids, Infrastructure Resilience, and Advanced Controls Launchpad (MIRACL) project. This project is a collaboration between the National Renewable Energy Laboratory (NREL), Sandia National Laboratories (SNL) and Pacific Northwest National Laboratory (PNNL). In the final year of this project, INL is collaborating with the other labs to bring together key results from our previous work on resilience, cybersecurity and risk, distributed wind hybrid systems, and valuation of distributed wind.
Graded approach for assessing digital system failure susceptibilities - 305
Owner/operators of nuclear plants must be able to identify and assess susceptibilities to digital system failures and unintended behaviors that could lead to plant system malfunctions, including common-cause failures (CCFs) of multiple controlled components that may impact overall plant safety. Nuclear plant designers and regulators often assess and manage potential failure modes by assuming the failure occurs and showing by analysis that the results are acceptable. In 2016 EPRI published a guideline on Methods for Assuring Safety and Dependability when Applying Digital Instrumentation and Control Systems (EPRI 3002005326), which takes a more holistic approach that considers digital system failure modes from the perspective of their impact on plant risk and includes a graded approach based on safety significance. This paper describes that graded approach. The methodology in EPRI 3002005326 systematically identifies potential I and C vulnerabilities that could lead to significant malfunctions of controlled components and systems, including common-cause failures (CCF), and discusses in detail methods to protect against them. It considers both preventive measures that reduce the likelihood of failures, and plant systems and features that mitigate the effects of component failures and misbehaviors. Coping analysis is then performed as appropriate to provide additional assurance of protection. The safety significance based graded approach is an important feature in that it can help users focus attention on overall plant safety, including potentially risk-significant scenarios that might not be considered in traditional safety analyses. The purpose is to help the user ensure that modifications to the I and C that could potentially be safety significant are treated appropriately and at the same time not waste valuable resources on excessive protection against changes that have little or no impact on safety. The graded approach allows the design engineer to tailor the rigor of the preventive, limiting, and mitigative measures commensurately with the effects the I and C modification has on overall plant safety. The graded approach focuses on safety significance impact, which is effectively a qualitative measure of the potential change in safety (or risk) caused by a proposed I and C modification, as compared to the I and C that is being replaced. Safety significance impact should not be confused with importance to safety or risk significance. It is possible that an upgrade to safety-related and/or risk-significant I and C systems may have little or no safety significant impact and vice versa. The approach considers three factors that influence the impact on safety significance of a proposed I and C modification: context, likelihood of failure, and consequences of failure. The most significant of the three factors is context - what the I and C is connected to, both directly and indirectly, including its potential effects on plant systems that respond to transients or accidents. The graded approach is particularly helpful in assessing potential CCFs resulting from digital I and C failures, and shows why the most problematic CCFs will be those that can affect multiple plant systems. (authors)