On the Cyber-Physical Needs of DER-Based Voltage Control/Optimization Algorithms in Active Distribution Network
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Key components of power systems—such as energy management systems, automatic generation control, and state estimation—are under serious vulnerability from cyberattacks. Cyber threats in electric grids have increased significantly because of the increased interconnectivity of supervisory control and data acquisition systems and public network infrastructure. As the penetration level of distributed energy resources increases, it is imperative to employ system-monitoring techniques such as state estimation for the reliable operation of distribution systems. Recently, multiple methods have been developed that exploit the low rank property of distribution system state matrix and are robust to bad data, such as matrix completion. This paper analyzes the impact of various realistic cyberattack scenarios on matrix completion. Realistic cyberattack scenarios are converted into data corruption models that are used in an extensive simulation of a custom IEEE 123-bus system.
Solar generation is experiencing an exponential growth in power systems worldwide and, along with wind power, is posing new challenges to power system operations. Those challenges are characterized by an increase of system variability and uncertainty across many time scales: from days, down to hours, minutes, and seconds. Much of the research in the area has focused on the effect of solar forecasting across hours or days. This paper presents a methodology to capture the effect of short-term forecasting strategies and analyzes the economic and reliability implications of utilizing a simple, yet effective forecasting method for solar PV in intra-day operations.
As energy infrastructure becomes more interconnected, understanding cybersecurity risks to production systems requires integrating operational and computer security knowledge. We interviewed 18 experts working in the field of energy critical infrastructure to compare what information they find necessary to assess the impact of computer vulnerabilities on energy operational technology. These experts came from two groups: 1) computer security experts and 2) energy sector operations experts. We find that both groups responded similarly for general categories of information and displayed knowledge about both domains, perhaps due to their interdisciplinary work at the same organization. Yet, their discussion of each group’s domain-specific training, motivations, and limitations, as well as their suggestions for collaboration across domains, highlighted how these two groups can work together to help each other secure the energy grid. Our findings inform the development of interdisciplinary security approaches in critical-infrastructure contexts.
A system for processing network packet capture streams, extracting metadata and generating flow records (via Argus). The system can be used by network security operators and analysts to enable forensic investigations for network security events.
Modern processors offer a wide range of control and measurement features, such as performance counters, power capping, and thermal control. These features are ultimately controlled through Model Specific Registers (MSRs), which require elevated privileges for access. While this is often no problem on individual workstations, it is a significant security risk on multi-user systems and large-scale compute clusters. The msr-safe kernel module provides controlled user-level access to MSRs through a whitelisting mechanism. Is
Network intrusion detection systems (NIDS) are commonplace in network security but they frequently employ algorithms that are computational demanding requiring hardware and software with significant power requirements. Two examples of such resource-intensive algorithms used for network security are regular expression matching and broader signature pattern matching which are commonly used in deep packet inspection (DPI). Network security algorithms that have large power requirements may be a challenge for low-power internet-of-things (IoT) environments, which generally lack the power resources to implement complex security measures like computationally expensive DPI at the edge. Furthermore, IoT environments incorporating 5G standalone networks have network latency constraints beyond just power that make DPI at the edge even more difficult. Programmable logic is ideally suited for machine learning inference for DPI because of its deep instruction level parallelism and single-cycle memory access. Machine learning approaches for DPI have been explored before using the programmable logic of field programmable gate arrays (FPGA) as a potential solution for NIDS approaches that would be power-suitable for IoT. However, those previous programmable logic NIDS approaches utilize either a supervised or unsupervised learning model. Sentinel utilizes the ensemble of these two machine learning approaches known as a semi-supervised approach which has shown promise in NIDS implementations. Sentinel provides a programmable logic implementation of a semi-supervised approach for DPI which operates at much lower power and latency than a GPU implementation with negligible loss of accuracy due to quantization through a logistic regressor.
The purpose of this document is to identify laws, rules, model codes, codes, standards, regulations, specifications (CSR) related to safety that could apply to stationary energy storage systems (ESS) and experiences to date securing approval of ESS in relation to CSR. This information is intended to assist in securing approval of ESS under current CSR and to identification of new CRS or revisions to existing CRS and necessary supporting research and documentation that can foster the deployment of safe ESS.
The mission of the U.S. Department of Energy (DOE), Office of Nuclear Energy is to advance nuclear power in order to meet the nation's energy, environmental, and energy security needs. Advanced high temperature reactor systems such as sodium fast reactors and high and very high temperature gas-cooled reactors are being considered for the next generation of nuclear reactor plant designs. The coolants for these high temperature reactor systems include liquid sodium and helium gas. Supercritical carbon dioxide (sCO₂), a fluid at a temperature and pressure above the supercritical point of CO₂, is currently being investigated by DOE as a working fluid for a nuclear or fossil-heated recompression closed Brayton cycle energy conversion system that operates at 550°C (1022°F) at 200 bar (2900 psi). Higher operating temperatures are envisioned in future developments. All of these design concepts require a highly effective heat exchanger that transfers heat from the nuclear or chemical reactor to the chemical process fluid or the to the power cycle. In the nuclear designs described above, heat is transferred from the primary to the secondary loop via an intermediate heat exchanger (IHX) and then from the intermediate loop to either a working process or a power cycle via a secondary heat exchanger (SHX). The IHX is a component in the primary coolant loop which will be classified as "safety related." The intermediate loop will likely be classified as "not safety related but important to safety." These safety classifications have a direct bearing on heat exchanger design approaches for the IHX and SHX. The very high temperatures being considered for the VHTR will require the use of very high temperature alloys for the IHX and SHX. Material cost considerations alone will dictate that the IHX and SHX be highly effective; that is, provide high heat transfer area in a small volume. This feature must be accompanied by low pressure drop and mechanical reliability and robustness. Classic shell and tube designs will be large and costly, and may only be appropriate in steam generator service in the SHX where boiling inside the tubes occurs. For other energy conversion systems, all of these features can be met in a compact heat exchanger design. This report will examine some of the ASME Code issues that will need to be addressed to allow use of a Code-qualified compact heat exchanger in IHX or SHX nuclear service. Most effort will focus on the IHX, since the safety-related (Class A) design rules are more extensive than those for important-to-safety (Class B) or commercial rules that are relevant to the SHX.
This Protocol provides a set of “best practices” for characterizing energy storage systems (ESSs) and measuring and reporting their performance. It serves as a basis for assessing how an ESS will perform with respect to key performance attributes relevant to different applications. It is intended to provide a valid and accurate basis for the comparison of different ESSs. By achieving the stated purpose, the Protocol will enable more informed decision-making in the selection of ESSs for various stationary applications. The Protocol identifies general information and technical specifications relevant in describing an ESS and also defines a set of test, measurement, and evaluation criteria with which to express the performance of ESSs that are intended for energy-intensive and/or power-intensive stationary applications. An ESS includes a storage device, battery management system, and any power conversion systems installed with the storage device. The Protocol is agnostic with respect to the storage technology and the size and rating of the ESS. The Protocol does not apply to single-use storage devices and storage devices that are not coupled with power conversion systems, nor does it address safety, security, or operations and maintenance of ESSs, or provide any pass/fail criteria.
The LDRD Program achieves continual improvement through internal and external reviews of Program management, execution, and oversight of each LDRD project. In accordance with DOE Order 226.1B of the prime contract between NNSA and Lawrence Livermore National Security, LLC, a contractor-assurance system is in place at the Laboratory; the LDRD office uses this system and tools provided to support improvements in LDRD Program performance. The FY17 portfolio was carefully structured to promote the Program’s vigorous strategic vision and the long-term goals of DOE, NNSA, and Livermore.
The Biological and Environmental Research (BER) program champions the predictive understanding of complex biological systems to enable energy and infrastructure security. To support this challenging endeavor, BER began funding Science Focus Area (SFA) projects at the national labs a decade ago in order to foster scientific advances that are more easily achieved by sustained team research. BER has recently encouraged collaboration among SFAs as a means to accelerate innovation and scientific impact. To facilitate BER’s vision, the Bioscience Division at Los Alamos National Laboratory (LANL) proposed an annual pan-SFA workshop that would rotate among the National Labs. LANL hosted the first workshop in September 2019 to explore a common challenge—understanding how microbiomes function—and to promote collaboration opportunities among SFAs in BER’s Microbial Genomics Program. The workshop comprised overview presentations of the eight SFAs and two SFA pilots and discussions of near- and midterm opportunities to foster collaboration. These opportunities include 1) sharing isolates, 2) sharing data and storage, 3) establishing common standards and best practices, and 4) fostering scientific exchanges.
Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the United States Department of Energy (DOE) National Nuclear Security Administration. The National Nuclear Security Administration's Sandia Field Office administers the contract and oversees contractor operations at Sandia National Laboratories, New Mexico. Activities at the site support research and development programs with a wide variety of national security missions, resulting in technologies for nonproliferation, homeland security, energy and infrastructure, and defense systems and assessments. DOE and its management and operating contractor for Sandia are committed to safeguarding the environment reassessing sustainability practices and ensuring the validity and accuracy of the monitoring data presented in this Annual Site Environmental Report. This report summarizes the environmental protection and monitoring programs in place at Sandia National Laboratories, New Mexico, during calendar year 2018. Environmental topics include air quality, ecology, environmental restoration, oil storage, site sustainability, terrestrial surveillance, waste management, water quality, and implementation of the National Environmental Policy Act. This report is prepared in accordance with and as required by DOE O 231.1B, Admin Change 1, Environment, Safety, and Health Reporting and has been approved for public distribution.
Mission Statement: Provide an improved snout to airbox interface design for the National Security Applications (NSA) snouts. The new system will improve the alignment, operator installation, and strength of the existing design.
Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the United States Department of Energy (DOE) National Nuclear Security Administration. The National Nuclear Security Administration’s Sandia Field Office administers the contract and oversees contractor operations at Sandia National Laboratories, New Mexico. Activities at the site support research and development programs with a wide variety of national security missions, resulting in technologies for nonproliferation, homeland security, energy and infrastructure, and defense systems and assessments. DOE and its management and operating contractor are committed to safeguarding the environment, assessing sustainability practices, and ensuring the validity and accuracy of the monitoring data presented in this Annual Site Environmental Report. This report summarizes the environmental protection and monitoring programs in place at Sandia National Laboratories, New Mexico, during calendar year 2019. Environmental topics include air quality, ecology, environmental restoration, oil storage, site sustainability, terrestrial surveillance, waste management, water quality, and implementation of the National Environmental Policy Act. This report is prepared in accordance with and as required by DOE O 231.1B, Admin Change 1, Environment, Safety, and Health Reporting, and has been approved for public distribution.
This report summarizes a two-year LDRD project that investigated the problem of representing complex supply chains, identifying the worst risks and evaluating mitigation options. Our team developed a framework that includes a representation for business processes, risk assessment questions, risk indicators and methods for analyzing and summarizing the data. In our approach, the Process Matrix represents an overall supply chain for an end product in a high-level, tabular form. It connects the various touch-points of a business process including people, external vendors, tools, storage locations and transportation services while capturing the flow of both physical and intellectual artifacts. We believe these direct connections are exactly the things that a process owner can typically control. These material flows (both physical and intellectual) are also represented in a graph. This enables us to use graph-oriented analysis such as fault tree analysis and attack graph generation. Our approach is top-down, which helps users to get a more holistic understanding for a given amount of resources. Understanding the provenance of materials is difficult and it is easy to exhaust the analysts' resources. Rather than a tool to do vendor analysis or product comparison, our framework enables an enterprise-level analysis. The risk assessment questionnaires have a varying levels of detail and cover various aspects of the supply chain such as process steps, artifacts, suppliers, etc. and connections between these aspects such as artifact-storage, artifact-supplier, etc. Each question is further associated with one of seven risk indicators which can be used to summarize the risk. These risk indicators can also be weighted to reflect a user's concerns. We have successfully applied our framework to several use cases in various stages of its development and provided valuable insights to our partners, but it can also be applied to other complex systems outside of the supply chain security problem.
Presentation to be presented during the 2021 ANS Virtual Meeting, Radiation Detection for Homeland Security Technical Session, on June 14, 2021 (https://www.ans.org/meetings/am2021/session/view-582/).
The mission of the Nuclear and Chemical Sciences (NACS) Division within the Physical and Life Sciences (PLS) Directorate is to advance scientific understanding, capabilities, and technologies in nuclear and particle physics, radiochemistry, forensic science, and isotope systems to support LLNL’s national security mission. NACS Division personnel conduct a diverse range of research activities in particle physics, nuclear physics, radiation detection, nuclear measurements, chemical and nuclear forensic science, nuclear and radiochemistry, isotope geochemistry, and environmental science. These areas are leveraged to address evolving national security challenges. Scientific research provides the foundation for addressing these challenges, and it is also the principal means of attracting, training, and retaining staff scientists who can deliver solutions across the Laboratory’s mission space. The overarching strategy is to position the NACS Division at the nexus between fundamental nuclear and chemical science research and nuclear security applications. This approach will support efforts to recruit, train, and retain top-flight scientists and engineers who will play a key role in executing the Laboratory’s core nuclear security missions, while also enhancing LLNL’s reputation as a center for innovative scientific research. This document describes the strategic vision that will be used to guide key investments aimed at enabling NACS scientists to lead new efforts and meet future challenges.