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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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Experimental Testing of a Real-Time Implementation of a PMU-Based Wide-Area Damping Control System
Not Available
Forced Oscillations in the Western Interconnection with the Pacific DC Intertie Wide Area Damping Controller.
Abstract not provided.
Mitigation documentation for the removal of hazardous materials from the engine installation vehicle and manned control car area 25, Nevada national security site, NYE county, Nevada
The purpose of this letter report is to document the mitigation of adverse effects of a proposed undertaking that would remove hazardous materials from the Engine Installation Vehicle (EIV) in Area 25 of the Nevada National Security Site (NNNSS) in compliance with Section 106 of the National Historic Preservation Act (NHPA) and the terms of the 2024 Programmatic Agreement among the U.S. Department of Energy and the Nevada State Historic Preservation Officer and the Advisory Council on Historic Preservation Concerning the Protection of Historic Properties on the Nevada National Security Site, Nye County, Nevada, hereafter referred to as the NNSS PA. The EIV (State Historic Preservation Office [SHPO] Resource No. S3057) has been determined individually eligible for listing in the National Register of Historic Places (NRHP) under Criteria A and C and as a contributing element to the Nuclear Rocket Development Station (NRDS) Historic District, which is eligible for the NRHP under all four Significance Criteria (Reno et al. 2023; Reed 2024).
Poster: Forced Oscillations in the Western Interconnection with the Pacific DC Intertie Wide Area Damping Controller.
Abstract not provided.
Field trials reveal the complexities of deploying and evaluating the impacts of yeast-baited ovitraps on Aedes mosquito densities in Trinidad, West Indies
The use of lure-and-kill, large-volume ovitraps to control Aedes aegypti and Aedes albopictus populations has shown promise across multiple designs that target gravid females (adulticidal) or larvae post-oviposition (larvicidal). Here we report on a pilot trial to deploy 10 L yeast-baited ovitraps at select sites in Curepe, Trinidad, West Indies during July to December, 2019. Oviposition rates among ovitraps placed in three Treatment sites were compared to a limited number of traps placed in three Control areas (no Aedes management performed), and three Vector areas (subjected to standard Ministry of Health, Insect Vector Control efforts). Our goal was to gain baseline information on efforts to saturate the Treatment sites with ovitraps within 20–25 m of each other and compare oviposition rates at these sites with background oviposition rates in Control and Vector Areas. Although yeast-baited ovitraps were highly attractive to gravid Aedes females, a primary limitation encountered within the Treatment sites was the inability to gain access to residential compounds for trap placement, primarily due to residents being absent during the day. This severely limited our intent to saturate these areas with ovitraps, indicating that future studies must include plans to account for these inaccessible zones during trap placement.
Data from the Development Evolution of a Vehicle for Custom Control
In order to develop custom controllers intended to operate vehicles on a live highway, a series of data collection-focused tests were performed at increasing stages of complexity. Modern vehicles with features like Adaptive Cruise Control (ACC) feature a rich set of sensors and drive-by-wire mechanisms. The presented stages of data collection begins with the analysis of raw data provided by various vehicles, and eventually results in spoofing Controller Area Network (CAN) protocols for sending control commands to operate a vehicle. This paper covers the data and technical efforts needed at various stages. The raw data and tools to plot the data are also publicly available.
Cybersecurity of Wide Area Monitoring, Protection and Control Systems for HVDC Applications
The flexibility provided by High Voltage Direct Current (HVDC) systems can be further extended by Wide Area Monitoring, Protection, and Control (WAMAPC) systems. WAMPAC systems enable many HVDC applications and, on the other hand, inevitably introduce cybersecurity concerns that need to be addressed. In this work, a security domain layer and decision framework is reported to detect and mitigate the impact of false data injection (FDI) attacks targeting HVDC stations. Specifically, a rule-based cyber-attack detection method is introduced and implemented on Raspberry Pi and tested on the real-time HVDC simulation facility on the real-time digital simulator (RTDS) platform at ABB U.S. Corporate Research Center.
Literature Review for Sensor Impact Evaluation and Verification Use Cases - Building Controls and Fault Detection and Diagnosis (FDD)
This report summarizes a comprehensive literature review for the selected sensor suites used in building controls and fault detection and diagnostics (FDD), which is a Q2 deliverable of the Sensor Impact Evaluation and Verification project. The project’s overarching goal is to develop a framework for investigating the impact of sensor deployment and configuration for building energy optimization, fault detection and diagnosis (FDD), occupants’ thermal comfort, and potential grid efficiency. While the first phase of the literature review performed in Q1 reviewed the current methods of various sensor selection and placements and their impact, this report focuses on high impactful potential use cases for the selected sensor suites in building control and FDD. The use cases identified in this literature review will be further investigated and be included in the final sensor impact evaluation framework. For the review, the multi-laboratory team reviewed 241 research papers, technical reports, and books to identify existing technologies, the potential impact on energy savings and thermal comfort, and future research opportunities for the selected use cases in building controls and FDD. Along with the literature review, the team conducted a series of interviews with experts in sensors and controls area to identify the state-of-art sensor technologies, and the most impactful use cases in controls and FDD areas. The interview results will also be incorporated with the findings from the literature review in the next quarter, and the final use cases to be evaluated will be selected.
Attack-resilient algorithms and testbed federation for wide-area protection and control in smart grid
Today’s energy infrastructure is undergoing a massive transformation across all generation, transmission, and distribution systems to provide reliability, efficiency, and sustainability to the power system network. During the past 10 years, there has been a remarkable enhancement in developing close-loop wide-area protection and control (WAPAC) applications, such as automatic generation control (AGC), wide-area protection scheme (WAPS), synchrophasor-based wide-area voltage control system (WAVCS), etc., in the energy management system (EMS) to provide an adequate situational awareness to control center operators during physical disturbances and natural events. The rapid digitalization, unencrypted communication, and numerous data-sharing devices have increased digital access points that have exposed the grid network to countless cyberattacks pertinent to the WAPAC cybersecurity. Given the amount of complex grid network coupled with legacy infrastructures, it is untrustworthy to completely rely on information technology (IT)-based conventional security measures to defend against evolving cyberattacks. Hence, there is a compelling need to go beyond the traditional paradigm of ‘security by obscurity’ and ‘bolt-on’ security measures, and develop a suite of innovative security solutions at multiple layers to transform the current “fault-resilient” grid into “fault and attack-resilient” grid of the future. This dissertation specifically focuses on developing application-specific attack-resilient solutions for critical WAPAC applications in the smart grid. The first part of the study, Attack-Resilient Wide-Area Protection Scheme, presents a cyber-physical attack-resilient system (CPARS) for WAPS, where two anomaly detection methods are proposed to detect multi-level cyberattacks followed by the rules-based intrusion mitigation system (RIMS) to initiate effective mitigation strategies, tailored to these attacks, to restore the normal grid operation after disturbances. The first anomaly detection component, Machine learning-based Anomaly Detection for Centralized WAPS, discusses a novel architecture and methodology for developing a machine-learning-based anomaly detection system (ADS) for the centralized wide-area protection system (CWAPS) by applying the variational mode decomposition (VMD) technique and decision tree (DT) algorithms using cyber logs and synchrophasor measurements. The second component, Multi-Agent-based Anomaly Detection for Decentralized WAPS, presents a two-level hierarchical multi-agent-based decentralized WAPS against the system-aware stealthy cyber-attacks. Finally, for the RIMS, the state transition diagram-based mitigation measures are defined based on the grid operation states and experimental testing and evaluation are presented in a cyber-physical testbed environment. The second part of the study, Attack-Resilient Wide-Area Voltage Control System, addresses the existing vulnerabilities in the wide-area voltage control system (WAVCS), presents the methodology for performing an impact analysis during data integrity attacks, and proposes a data-driven attackresilient system (DARS) by incorporating machine learning-based ADS and rules-based anomaly mitigation system (RAMS) to detect these attacks and provide necessary mitigation actions to maintain the transient voltage stability after disturbances. Finally, the third part, Networked Federation Testbed (NEFTSec) for Smart Grid Cybersecurity, focuses on developing an interconnected federated testbed through a common network like the internet, describes its conceptual architectures, and also presents its design components for experimental testing, validation, and evaluation. Further, it presents the co-simulation interface algorithm (CIA) to facilitate the geographically-dispersed real-time distributed simulation (GD-RTDS) during the cyber-physical federation. In general, this dissertation presents innovative attack-resilient solutions for WAPAC applications that are experimentally tested and evaluated using the PowerCyber testbed and NEFTSec platform to accelerate the transition of state-of-the-art research works to the real-field deployments.
A Novel Architecture for Attack-Resilient Wide-Area Protection and Control System in Smart Grid
Wide-area protection and control (WAPAC) systems are widely applied in the energy management system (EMS) that rely on a wide-area communication network to maintain system stability, security, and reliability. As technology and grid infrastructure evolve to develop more advanced WAPAC applications, however, so do the attack surfaces in the grid infrastructure. This paper presents an attack-resilient system (ARS) for the WAPAC cybersecurity by seamlessly integrating the network intrusion detection system (NIDS) with intrusion mitigation and prevention system (IMPS). In particular, the proposed NIDS utilizes signature and behavior-based rules to detect attack reconnaissance, communication failure, and data integrity attacks. Further, the proposed IMPS applies state transition-based mitigation and prevention strategies to quickly restore the normal grid operation after cyberattacks. As a proof of concept, we validate the proposed generic architecture of ARS by performing experimental case study for wide-area protection scheme (WAPS), one of the critical WAPAC applications, and evaluate the proposed NIDS and IMPS components of ARS in a cyber-physical testbed environment. Our experimental results reveal a promising performance in detecting and mitigating different classes of cyberattacks while supporting an alert visualization dashboard to provide an accurate situational awareness in real-time.
Evaluating lightweight unsupervised online IDS for masquerade attacks in CAN
Vehicular controller area networks (CANs) are susceptible to masquerade attacks by malicious adversaries. In masquerade attacks, adversaries silence a targeted ID and then send malicious frames with forged content at the expected timing of benign frames. As masquerade attacks could seriously harm vehicle functionality and are the stealthiest attacks to detect in CAN, recent work has devoted attention to compare frameworks for detecting masquerade attacks in CAN. However, most existing works report offline evaluations using CAN logs already collected using simulations that do not comply with the domain’s real-time constraints. Here we contribute to advance the state of the art by presenting a comparative evaluation of four different non-deep learning (DL)-based unsupervised online intrusion detection systems (IDS) for masquerade attacks in CAN. Our approach differs from existing comparative evaluations in that we analyze the effect of controlling streaming data conditions in a sliding window setting. In doing so, we use realistic masquerade attacks being replayed from the ROAD dataset. We show that although evaluated IDS are not effective at detecting every attack type, the method that relies on detecting changes in the hierarchical structure of clusters of time series produces the best results at the expense of higher computational overhead. We discuss limitations, open challenges, and how the evaluated methods can be used for practical unsupervised online CAN IDS for masquerade attacks.
Automated Vehicle Multi-Object Tracking at Scale with CAN
Millions of vehicles are on the road with RADAR sensors in use for adaptive cruise control (ACC), and RADAR sen- sors are not tracking all of the objects in the field of view. This work shows a work-in-progress tool to improve track- ing from RADAR and controller area network (CAN) which should be vitally useful for safety of transportation systems and automated vehicle development. The CAN data provides object detections, but there is a lingering data association problem. The contribution of this work in progress is the solution to the data association problem by posing the data association as a minimum cost network flow problem, and doing it at low cost with an eye toward scalable CPS research.
Examining the Economic Optimality of Automatic Generation Control
The automatic generation control (AGC) system is temporally situated between economic dispatch and synchronous generator dynamics, and its primary role is to regulate frequency within and tie-line flows between control areas. Given appropriate choice of participation factors (feed-forward controller gains that govern the disaggregation of the area-level power requirement to individual generators), the AGC can be engineered to nudge system dynamics toward a steady-state operating point corresponding to economic optimality. This paper establishes necessary and sufficient conditions under which a widely accepted choice of participation factors guarantees the alignment of steady-state synchronous generator outputs with a global minimum of a prototypical economic dispatch problem. In so doing, it resolves several ambiguities and formalizes technical assumptions governing the role of the standard AGC architecture in the context of economic dispatch and steady-state operation. Numerical case studies tailored to a modified version of the New England 39-bus 10-machine test system validate the theoretical results.
Porosity in Sr 1-x Ca x FeO 3-δ oxygen carriers: The role of surface area and pretreatment on storage activity
Perovskite oxides have generated interest as robust, low-temperature oxygen carrier materials for a variety of clean energy applications, including chemical looping gasification and air separations. Methods to improve O 2 desorption kinetics are vital to allow these carriers to compete economically with traditional metal oxide carriers or cryogenic separations. In this report we investigated the cumulative roles that surface area, pretreatment, and elemental composition have on the oxygen storage properties of a state-of-the-art carrier system, Sr 1-x Ca x FeO 3-δ (x = 0.20, 0.25, 0.30) synthesized using multiple methods. Porous materials synthesized by the Pechini, or citrate, method had their surface area controlled using the synthesis temperature. The high surface area of the Sr 0.7 Ca 0.3 FeO 3-δ materials is most beneficial at low operating temperatures, such as 350 and 400 °C, as their reduction rates are twice as fast as those obtained with their bulk counterparts. These effects are observed at higher operating temperatures and within a single composition, but temperature tunability using variable Ca 2+ substitution in the Sr 1-x Ca x FeO 3-δ overshadows the improvements gained from higher surface areas. Additionally, we establish that pretreatment in N2 at an elevated temperature is necessary to enhance kinetics further. For maximum efficiency, pretreatment at the synthesis temperature is suggested for the Pechini method-synthesized systems, whereas 800 °C is adequate for bulk materials.
Performance Monitoring Program: Developing Comparative Metrics for Fitness-for-Duty Programs
To comply with U.S. Nuclear Regulatory Commission (NRC) regulations, licensees and entities authorized under Title 10 of the Code of Federal Regulations (CFR) Part 26 Section 26.3 (§ 26.3) are required to have fitness-for-duty (FFD) programs. Under § 26.3, the expectation of these FFD programs is to provide reasonable assurance that individuals who are granted unescorted access to nuclear power reactor protected areas and Category I fuel cycle facility material control areas are trustworthy, will perform their tasks in a reliable manner, are not under the influence of any substance, legal or illegal, that may impair their ability to perform their duties, and are not mentally or physically impaired from any cause that can adversely affect their ability to safely and competently perform their duties. Pacific Northwest National Laboratory (PNNL) was tasked with developing a performance monitoring program to risk inform NRC inspection and policy regarding quantitative FFD performance data. To meet this need, PNNL developed methodologies that could be implemented within a performance monitoring program. Throughout this report, these methodologies are referred to as comparative metrics. The NRC provided PNNL with 2016–2019 data from annual reporting forms and single positive test forms provided by licensees and other entities. For most of the comparative metrics, the analyses required customized processing, such as creating filtering fields, adding data fields and summaries, and joining datasets. The comparative metrics developed include: random testing rate, random policy violation rate, pre-access policy violation rate, subversion attempt rate, and number of policy violations by labor category. The comparative metrics can be used for parsing and visualizing FFD program data and monitoring FFD performance at the labor category, facility, licensee, and industry levels to risk inform NRC inspection and policy with regard to the FFD data currently collected from licensees and other entities that implement Part 26 requirements. Furthermore, these developed comparative metrics allow a more in-depth look at the FFD programs for the industry to discern trends and patterns that may warrant changes at an industry level and to inform policy decisions. These analyses should be refreshed as new FFD data become available.
Analytical Models of Frequency and Voltage in Large-Scale All-Inverter Power Systems
Low-order frequency response models for power systems have a decades-long history in optimization and control problems such as unit commitment, economic dispatch, and wide-area control. With a few exceptions, these models are built upon the Newtonian mechanics of synchronous generators, assuming that the frequency dynamics across a system are approximately homogeneous, and assume the dynamics of nodal voltages for most operating conditions are negligible, and thus are not directly computed at all buses. As a result, the use of system frequency models results in the systematic underestimation of frequency minimum nadir and maximum RoCoF, and provides no insight into the reactive power-voltage dynamics. This paper proposes a low-order model of both frequency and voltage response in grid-forming inverter-dominated power systems. The proposed model accounts for spatial-temporal variations in frequency and voltage behavior across a system and as a result, demonstrates the heterogeneity of frequency response in future renewable power systems. Electromagnetic transient (EMT) simulations are used to validate the utility, accuracy, and computational efficiency of these models, setting the basis for them to serve as fast, scalable alternatives to EMT simulation, especially when dealing with very large-scale systems, for both planning and operational studies.
Decentralized Low-Rank State Estimation for Power Distribution Systems
This article considers the low-observability state estimation problem in power distribution networks and develops a decentralized state estimation algorithm leveraging the matrix completion methodology. Matrix completion has been shown to be an effective technique in state estimation that exploits the low dimensionality of the power system measurements to recover missing information. This technique can utilize an approximate (linear) load flow model, or it can be used with no physical models in a network where no information about the topology or line admittance is available. The direct application of matrix completion algorithms requires solving a semi-definite programming (SDP) problem, which becomes computationally challenging for large networks. We therefore develop a decentralized algorithm that capitalizes on the popular proximal alternating direction method of multipliers (proximal ADMM). The method allows us to distribute the computation among different areas of the network, leading to a scalable algorithm. By doing all computations at individual control areas and only communicating with neighboring areas, the algorithm eliminates the need for data to be sent to a central processing unit and thus increases efficiency and contributes to the goal of autonomous control of distribution networks. We illustrate the advantages of the proposed algorithm numerically using standard IEEE test cases.