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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 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
NASA NTRS2009

Jet Propulsion Laboratory: Annual Report 2008

Nothing is more exciting than when science mines the far end of our knowledge for the new and the unexpected. In 2008, the world was taken by surprise when JPL astronomers announced the discovery of organic compounds on a planet orbiting another star. We were equally excited to learn from the Spitzer Space Telescope that many, if not most, sun-like stars have rocky planets roughly similar to Earth. Together these are very intriguing clues in our quest to learn if there is life elsewhere in the universe, which certainly has to be one of the most profound mysteries of our age.There are times when, dealing with unknowns, we are reminded to be humble. Very impressive progress is being made by the team developing our next flagship mission, Mars Science Laboratory. Ther conclusion, however, is that it would not be safe to try to fly during the Mars launch window in 2009, and reset for the next opportunity in 2011. We are lucky to have valuable assets that support us as we venture into the unknown. One is the global Deep Space Network, which functions both as our communication gateway to our spacecraft across the solar system as well as a research tool itself in conducting radar astronomy. Our successes depend on our entire team, administrators and business specialists as much as technical people. There are those who help share our missions with the public, finding imaginative venues such as sending out dispatches on the Internet's Twitter.com during the Phoenix mission. We also benefit greatly from the intellectual infusion that comes from our unique identity as a division of the California Institute of Technology and a member of the NASA family.

National Aeronautics and Space Administration (NAS↗
DOE OSTI2024

IoT-Enabled Traveling Wave Microgrid Protection

Traveling Wave Protection based on the Internet of Things (TWP-IoT) is developed to enable ultra-resilient microgrids. TWP-IoT adopts a directional traveling wave approach that utilizes the voltage and current modal components obtained from Discrete Hilbert Transform to identify the fault features via ultra-lightweight IoT hardware. Furthermore, the main contributions of this work include (1) a novel TWP-IoT for microgrid and distribution networks that can achieve the time-of-arrival fault detection and localization with composite wave impedance and conductance using Discrete Hilbert Transform, (2) a cost-effective smart IoT prototype with functionalities outperforming commercial relays, and (3) a real-time hardware-in-the-loop prototype based on RTDS that verifies the robustness and efficacy of TWP-IoT subject to a diverse set of working conditions. TWP-IoT is found to have excellent performance under a wide spectrum of internal and external fault conditions across a myriad of microgrid locations, which is unattainable by today’s TWP products.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2002

Applying Strategic Visualization(Registered Trademark) to Lunar and Planetary Mission Design

NASA teams, such as the NASA Exploration Team (NEXT), utilize advanced computational visualization processes to develop mission designs and architectures for lunar and planetary missions. One such process, Strategic Visualization (trademark), is a tool used extensively to help mission designers visualize various design alternatives and present them to other participants of their team. The participants, which may include NASA, industry, and the academic community, are distributed within a virtual network. Consequently, computer animation and other digital techniques provide an efficient means to communicate top-level technical information among team members. Today,Strategic Visualization(trademark) is used extensively both in the mission design process within the technical community, and to communicate the value of space exploration to the general public. Movies and digital images have been generated and shown on nationally broadcast television and the Internet, as well as in magazines and digital media. In our presentation will show excerpts of a computer-generated animation depicting the reference Earth/Moon L1 Libration Point Gateway architecture. The Gateway serves as a staging corridor for human expeditions to the lunar poles and other surface locations. Also shown are crew transfer systems and current reference lunar excursion vehicles as well as the Human and robotic construction of an inflatable telescope array for deployment to the Sun/Earth Libration Point.

Frassanito, John R.↗
NASA NTRSDate not supplied

Enabling Interoperability in Earth System Digital Twins (ESDT): Integrating Observations, Models, and AI for Actionable Insights Through NASA'S Intelligent Systems Technology Program

NASA’s Intelligent Systems Technology Program (IST) is driving a paradigm shift in Earth science through the development of Earth System Digital Twins (ESDT). These integrated information systems create a dynamic "digital replica" of the Earth by harmonizing continuous, multi-source observations with high-fidelity models and state-of-the-art artificial intelligence (AI) that enable “What now?”, “What next?”, and “What if?” scenario building. These scenarios are reflected in NASA IST’s series of ESDTs, from the Coastal Zone Digital Twin that integrates complex data on the current state of the Chesapeake Bay to the Terrestrial Environmental Rapid-Replication and Assimilation Hydrometeorological (TerraHydro) AI-based ESDT that forecasts water movement across Earth’s surface, to the Agriculture Land Information System (AgLIS) which can be used to assess optimal planting dates and crop yield estimates. By bridging the gap between vast data archives and actionable insights, these projects enable a system-of-systems approach to understanding complex, interacting Earth processes. This poster will highlight recent innovations and future directions from NASA’s ESDT initiatives: Continuous Data Assimilation & Multi-Source Fusion. A core requirement of the ESDT work is the transition from static models to dynamic "living" replicas. This involves creating frameworks for the continual assimilation of near-real-time data from uncoordinated, heterogeneous sources, including satellite observations and airborne assets, and ground-based Internet of Things (IoT) sensors. These systems link design, operational status, and environmental data, ensuring the digital twin accurately reflects the current state of the physical Earth system. High-Fidelity Hybrid Modeling & Computational Acceleration to enable interactive "what-if" explorations, programs are moving beyond traditional, slow physical solvers by developing fast surrogate machine learning models and Deep Generative Models (DGMs). These hybrid approaches use neural networks to emulate complex physics, such as cloud feedback or ocean dynamics, at a fraction of the original computing cost, often leveraging advanced hardware like Graphics Processing Units (GPUs) to achieve the necessary scale. Federated Ecosystems & Interoperable Frameworks rather than building isolated tools, NASA IST is moving toward federated ESDTs and reusable analytic collaborative frameworks. This theme focuses on interoperability standards and common ontologies that allow specialized digital twins to interact and share data. This system-of-systems architecture supports multi-discipline investigations, such as analyzing how upstream watershed changes impact downstream urban flooding or how wildfire emissions affect regional air quality. By leveraging these advancements, ESDTs empower researchers and decision-makers to conduct real-time analysis and run complex hypothetical scenarios, ultimately improving our understanding of Earth’s evolving systems and informing critical real-world applications.

Earth System↗
DOE OSTI2025

Entanglement swapping systems toward a quantum internet

We demonstrate conditional entanglement swapping, i.e. teleportation of entanglement, between time-bin qubits at the telecommunication wavelength of 1536.4 nm with high fidelity of 87%. Our system is deployable, utilizing modular, off-the-shelf, fiber-coupled, and electrically controlled components such as electro-optic modulators. It leverages the precise timing resolution of superconducting nanowire detectors, which are controlled and read out via a custom developed graphical user interface. The swapping process is described, interpreted, and guided using characteristic function-based analytical modeling that accounts for realistic imperfections. Our system supports quantum networking protocols, including source-independent quantum key distribution, with an estimated secret key rate of approximately 0.5 bits per sifted bit.

Davis, Samantha I. [Caltech] (ORCID:00000001999481↗
DOE OSTI2023

Comparison of Machine Learning Algorithms for Natural Gas Identification with Mixed Potential Electrochemical Sensor Arrays

Mixed-potential electrochemical sensor arrays consisting of indium tin oxide (ITO), La 0.87 Sr 0.13 CrO 3 , Au, and Pt electrodes can detect the leaks from natural gas infrastructure. Algorithms are needed to correctly identify natural gas sources from background natural and anthropogenic sources such as wetlands or agriculture. We report for the first time a comparison of several machine learning methods for mixture identification in the context of natural gas emissions monitoring by mixed potential sensor arrays. Random Forest, Artificial Neural Network, and Nearest Neighbor methods successfully classified air mixtures containing only CH 4 , two types of natural gas simulants, and CH 4 +NH 3 with >98% identification accuracy. The model complexity of these methods were optimized and the degree of robustness against overfitting was determined. Finally, these methods are benchmarked on both desktop PC and single-board computer hardware to simulate their application in a portable internet-of-things sensor package. The combined results show that the random forest method is the preferred method for mixture identification with its high accuracy (>98%), robustness against overfitting with increasing model complexity, and had less than 10 ms training time and less than 0.1 ms inference time on single-board computer hardware.

03 NATURAL GAS↗
NASA NTRS2005

New Directions in Space Operations Services in Support of Interplanetary Exploration

To gain access to the necessary operational processes and data in support of NASA's Lunar/Mars Exploration Initiative, new services, adequate levels of computing cycles and access to myriad forms of data must be provided to onboard spacecraft and ground based personnel/systems (earth, lunar and Martian) to enable interplanetary exploration by humans. These systems, cycles and access to vast amounts of development, test and operational data will be required to provide a new level of services not currently available to existing spacecraft, on board crews and other operational personnel. Although current voice, video and data systems in support of current space based operations has been adequate, new highly reliable and autonomous processes and services will be necessary for future space exploration activities. These services will range from the more mundane voice in LEO to voice in interplanetary travel which because of the high latencies will require new voice processes and standards. New services, like component failure predictions based on data mining of significant quantities of data, located at disparate locations, will be required. 3D or holographic representation of onboard components, systems or family members will greatly improve maintenance, operations and service restoration not to mention crew morale. Current operational systems and standards, like the Internet Protocol, will not able to provide the level of service required end to end from an end point on the Martian surface like a scientific instrument to a researcher at a university. Ground operations whether earth, lunar or Martian and in flight operations to the moon and especially to Mars will require significant autonomy that will require access to highly reliable processing capabilities, data storage based on network storage technologies. Significant processing cycles will be needed onboard but could be borrowed from other locations either ground based or onboard other spacecraft. Reliability will be a key factor with onboard and distributed backup processing an absolutely necessary requirement. Current cluster processing/Grid technologies may provide the basis for providing these services. An overview of existing services, future services that will be required and the technologies and standards required to be developed will be presented. The purpose of this paper will be to initiate a technological roadmap, albeit at a high level, of current voice, video, data and network technologies and standards (which show promise for adaptation or evolution) to what technologies and standards need to be redefined, adjusted or areas where new ones require development. The roadmap should begin the differentiation between non manned and manned processes/services where applicable. The paper will be based in part on the activities of the CCSDS Monitor and Control working group which is beginning the process of standardization of the these processes. Another element of the paper will be based on an analysis of current technologies supporting space flight processes and services at JSC, MSFC, GSFC and to a lesser extent at KSC. Work being accomplished in areas such as Grid computing, data mining and network storage at ARC, IBM and the University of Alabama at Huntsville will be researched and analyzed.

Bradford, Robert N.↗
DOE OSTI2020

Communication-efficient certificate revocation management for Advanced Metering Infrastructure and IoT Integration

Advanced Metering Infrastructure forms a communication network for the collection of power data from smart meters in Smart Grid. As the communication between smart meters could be secured utilizing public-key cryptography, however, public-key cryptography still has certain challenges in terms of certificate revocation and management particularly related distribution and storage overhead of revoked certificates. To address this challenge, in this work, we propose a novel revocation management approach by utilizing cryptographic accumulators which reduces the space requirements for revocation information significantly and thus enables efficient distribution of such information to all smart meters. We implemented the proposed approach on both ns-3 network simulator and a testbed. We demonstrated its superior performance with respect to traditional methods for revocation management.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Cognitive IoT and Edge Computing for Intrusion Detection with Federated TinyML

Internet of Things (IoT) and Edge Computing (EC) are rapidly becoming an integral part of the modern society. By 2030, there is estimated to be over 40 billion active and connected IoT devices [1]. This rapid progress also comes with a significant implication on cybersecurity. Back-end infrastructure and systems have a much broader attack than they did previously due to vulnerable IoT/EC devices being connected to wireless networks. This expanding attack surface is a growing concern because IoT/EC are increasingly being used in critical systems such as power grids, health care, and smart homes. To effectively address a problem of this scale, cognitive cyber methods—which can autonomously detect and react to cyber attacks as they develop—are needed. To address this, we bring Artificial Intelligence (AI) and Machine Learning (ML) to IoT/EC devices, using tinyML to monitor voluminous IoT data against cyber threats, and using Federated Learning (FL) to share local detection knowledge across the system while preserving privacy. We propose a novel three-layer architecture: (1) an IoT layer for tinyML-based inference, (2) an edge layer for ML model training, and (3) a cloud layer for FL operations. Using the publicly available 11-class N-BaIoT dataset [2], we demonstrate that this architecture mitigates resource constraints at the IoT layer while improving detection accuracy over standard two-layer designs. An outlier-resistant scaler, feature reduction, and quantization enable the tinyML model to maintain detection accuracy with a reduced model size. Additionally, federated learning that only utilizes the intersection (across heterogenous devices) of the reduced feature set achieves superior detection accuracy compared to locally trained models.

Li, Mingyan [ORNL] (ORCID:0009000569532640)↗
NASA NTRS2004

Space Network Devices Developed

The NASA Glenn Research Center through a contract with Spectrum Astro, Inc., has been developing space network hardware as an enabling technology using open systems interconnect (OSI) standards for space-based communications applications. The OSI standard is a well-recognized layered reference model that specifies how data should be sent node to node in a communications network. Because of this research and technology development, a space-qualifiable Ethernet-based network interface card (similar to the type found in a networked personal computer) and the associated four-port hub were designed and developed to flight specifications. During this research and development, there also have been many lessons learned for determining approaches for migrating existing spacecraft architectures to an OSI-network-based platform. Industry has recognized the benefits of targeting hardware developed around OSI standards such as Transmission Control Protocol/Internet Protocol (TCP/IP) or similar protocols for use in future generations of space communication systems. Some of these tangible benefits include overall reductions in mission schedule and cost and in system complexity. This development also brings us a step closer to the realization of a principal investigator on a terrestrial Internet site being able to interact with space platform assets in near real time. To develop this hardware, Spectrum Astro first conducted a technology analysis of alternatives study. For this analysis, they looked at the features of three protocol specifications: Ethernet (IEEE 802.3), Firewire (IEEE 1394), and Spacewire (IEEE 1355). A thorough analysis was performed on the basis of criteria such as current protocol performance and suitability for future space applications. Spectrum Astro also projected future influences such as cost, hardware and software availability, throughput performance, and integration procedures for current and transitive space architectures. After a thorough analysis, Ethernet was chosen because it was seen as the best longer term fit because of the prevalent commercial market; the current and projected availability of hardware, software, and development tools; and the ease of architecture integration.

Jones, Robert E.↗
DOE OSTI2020

Broadband Communications Using High Voltage Transmission Lines - A Review

The possibilities afforded by using an existing transmission line infrastructure for the transport of broadband communications are many ranging from (conventional) A-to-B point-to-point links, to integration of Wi-Fi access points mounted at defined network (power and communications) locations, to operation as a fault-tolerant, rollover backup communications fabric (in conjunction with other transport media, such as optical fiber or terrestrial microwave). As stated by RCR Wireless reporter Jeff Kagan – regarding an ongoing in-field demonstration - “This is so much more cost effective for the company and so much easier for them to deliver an ultra-fast, gigabit speed, wireless internet connection anywhere there are power lines.” The same situation arises for a utility looking to augment or simply deploy a communications fabric in their region via treating the transmission line infrastructure as a communication fabric thereby reducing the cost and complexity of deployment. A circa 2020 review of broadband over powerlines (BPL) is presented here.

42 ENGINEERING↗
DOE OSTI2023

Testing SOAR tools in use

Investigations within Security Operation Centers (SOCs) are tedious as they rely on manual efforts to query diverse data sources, overlay related logs, correlate the data into information, and then document results in a ticketing system. Security Orchestration, Automation, and Response (SOAR) tools are a relatively new technology that promise, with appropriate configuration, to collect, filter, and display needed diverse information; automate many of the common tasks that unnecessarily require SOC analysts’ time; facilitate SOC collaboration; and, in doing so, improve both efficiency and consistency of SOCs. There has been no prior research to test SOAR tools in practice; hence, understanding and evaluation of their effect is nascent and needed. Here, in this paper, we design and administer the first hands-on user study of SOAR tools, involving 24 participants and six commercial SOAR tools. Our contributions include the experimental design, itemizing six characteristics of SOAR tools, and a methodology for testing them. We describe configuration of a cyber range test environment, including network, user, and threat emulation; a full SOC tool suite; and creation of artifacts allowing multiple representative investigation scenarios to permit testing. We present the first research results on SOAR tools. Concisely, our findings are that: per-SOC SOAR configuration is extremely important; SOAR tools increase efficiency and reduce context switching, although with potentially decreased ticketing accuracy/completeness; user preference is slightly negatively correlated with their performance with the tool; internet dependence varies widely among SOAR tools; and balance of automation with assisting decision making is preferred by senior participants. We deliver a public user- and tool-anonymized and -obfuscated version of the data.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2008

Providing Internet Access to High-Resolution Lunar Images

The OnMoon server is a computer program that provides Internet access to high-resolution Lunar images, maps, and elevation data, all suitable for use in geographical information system (GIS) software for generating images, maps, and computational models of the Moon. The OnMoon server implements the Open Geospatial Consortium (OGC) Web Map Service (WMS) server protocol and supports Moon-specific extensions. Unlike other Internet map servers that provide Lunar data using an Earth coordinate system, the OnMoon server supports encoding of data in Moon-specific coordinate systems. The OnMoon server offers access to most of the available high-resolution Lunar image and elevation data. This server can generate image and map files in the tagged image file format (TIFF) or the Joint Photographic Experts Group (JPEG), 8- or 16-bit Portable Network Graphics (PNG), or Keyhole Markup Language (KML) format. Image control is provided by use of the OGC Style Layer Descriptor (SLD) protocol. Full-precision spectral arithmetic processing is also available, by use of a custom SLD extension. This server can dynamically add shaded relief based on the Lunar elevation to any image layer. This server also implements tiled WMS protocol and super-overlay KML for high-performance client application programs.

Plesea, Lucian↗
DOE OSTI2026

Designing resilient IoT and Edge Computing with federated tinyML

The rapid growth of the Internet of Things (IoT) and Edge Computing (EC) has brought significant conveniences to modern society but has also greatly expanded the cyber attack surfaces, particularly as these technologies are being increasingly integrated into critical systems such as power grids, healthcare, and smart homes. Here, to improve IoT/EC’s cybersecurity posture, we leveraged Artificial Intelligence (AI) and Machine Learning (ML) by employing tinyML to monitor voluminous IoT data for cyber threats while addressing devices’ resource constraints, and utilizing Federated Learning (FL) to share local detection knowledge across the system while preserving privacy. Building on our three-layer architecture combining tinyML and FL to enhance autonomous cyber attack detection, this paper demonstrated that the architecture improves detection accuracy, reduces resource consumption, and enables lightweight, secure IoT device monitoring. These results were validated using the public N-BaIoT dataset as well as real IoT network traffic data collected under multiple attack scenarios from our testbeds. Additionally, we introduced an enhanced FL methodology with a novel preprocessing stage, including federated feature selection and global preprocessor construction, to address IoT/EC data heterogeneity. We developed a physical IoT testbed for attack simulations and data collection, implemented a tinyML-powered detector for realistic model validation, and also built a virtual testbed for scalable evaluations of FL models across diverse network environments.

Cognitive cyber↗
DOE OSTI2025

Improving Cyber Situational Understanding

Effective cybersecurity operations require the ability to analyze large amounts of information to assess security risks and formulate defensive strategies against adversaries. This has become more complex in recent years as the sprawl and interconnectivity of devices grows through implementation of virtualization, cloud computing, and Internet of Things (IoT). The amount of data and analysis required for effective cybersecurity command and control decisions far exceeds humans’ capacity to perform manually. We characterize the analysis problem as cyber situational understanding. The research presented to improve cyber situational understanding focuses on vulnerability analysis and threat intelligence. Regarding vulnerabilities, entities must analyze and plan work for between thousands and tens of thousands of software vulnerabilities annually. Entities heavily use network firewalls to limit vulnerability exposure. As a result, some of these vulnerabilities permit exposure to adversarial exploitation, whereas others are inaccessible and therefore present negligible risk of exploitation. Distinguishing between high and low risk software vulnerabilities requires a deep understanding of the vulnerability, network firewall protection, and characteristics of the targeted device. This problem is solved by extracting network service features from vulnerability data features using both machine-learning and natural language processing. Then, the network firewall topology is parsed to determine which vulnerabilities are reachable by adversaries. Ultimately, a state-based safety analysis ascertains which vulnerabilities are unsafe. A related vulnerability analysis problem occurs in cybersecurity operations when associating an entity’s hardware and software assets to public vulnerability databases. Assets often reveal hardware and software through installation artifacts and network service identification, and entities store these artifacts in inventory databases. However, software and hardware vendors apply a standard Common Platform Enumeration (CPE) naming convention when publicly reporting vulnerabilities. Associating these two datasets often requires many hours to days of manual inspection. The proposed solution automates the mapping approach of human analysts using fuzzy matching techniques, natural language processing, and, ultimately, machine learning to present a small set of recommendations for mapping the two datasets. The result significantly reduces human analysis time and reduces the occurrence of false positives in vulnerability notifications. Finally, cyber threat intelligence (CTI) requires associating cyber observable artifacts, such as IP addresses, URIs, and file hashes, with cyber threat tactics, techniques, and procedures. Unfortunately, most CTI data is compartmentalized across multiple organizations and cannot be shared due to the legal and reputational risk with cyber threat being associated with the entity. The approach to solving this problem inovlves using a distributed ledger with anonymous token spending and authentication. This allows a consortium of semi-trusted entities to share the workload of curating CTI for a threat sharing community’s cooperative benefit.

Huff, Philip↗
DOE OSTI2020

Roundtable Report: Terahertz and 6G Wireless Communications in Science and Extreme Environments

The main objective of the roundtable is to bring together computer scientists and wireless communications experts from industry, academia, and government to explore the electromagnetic spectrum in the Terahertz (THz) bands for ultra-high-speed short-distance wireless communications in extreme environments. This new generation of THz wireless communications is the key to future machine-to-machine communications critical for the mass deployment of an intelligent Internet of Things (IoT). The roundtable discussion explores THz and 6G wireless technologies along with Visible Light Communications (VLC), intelligent reflection surfaces, free-space quantum and optical communications, and nano communications. The roundtable considers the suitability of these technologies for extreme environments from the nanoscale to the mesoscale for the following: scientific facilities and associated instruments, as well as industry, and manufacturing. Such use cases are not traditionally the primary customer of commercial wireless networks which are focused on personal broadband voice and data communications. Finally, the discussion identifies high-level opportunities and challenges for leveraging THz and 6G wireless communications and related Artificial Intelligence (AI) that can catalyze the advancement of the development of hyperconnected smart scientific instruments and facilities.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

A Real-Time ANPC Inverter Digital Twin with Integrated Design-For-Trust

The demand for renewable energy has increased over the last few years, and so has the demand for greater expectations within the energy market. This increasing trend has been accompanied by more significant usage of internet-connected devices (IoT), leading to critical electrical infrastructure being connected to the internet. Implementing internet connectivity with such devices and systems provides benefits such as improving the system's performance, facilitating irregularity and anomaly mitigation, and providing additional situational awareness for enhanced decision-making. However, enhancing the connected system with IoT introduces a drawback – a greater vulnerability to cyber-attacks. Cyber-attacks targeting critical infrastructure in the electrical sector have occurred in the United States and Ukraine. These cyber-attacks highlight and expose vulnerabilities that a system inherits when connecting to the internet. These attacks left thousands of customers without electricity for hours until operators could regain control of the electric utility grid. Therefore, to address the vulnerabilities of an internet-connected power electronic device, this work focused on the hardware layer of the system. Implementing a cyber-control system inside the hardware layer can significantly reduce the possibility of an attacker patching malicious controller firmware into a photovoltaic grid-connected inverter, thus mitigating the likelihood that the inverter becomes inactive a cyber-attack scenario. With this mitigation technique, if a cyberattack is successful and an attacker gains control of the network, a cyber-defense technique is in place to mitigate the impact of the cyber-attack. This additional protection layer was developed based on an innovative concept known as Digital Twin (DT). A DT, in this case, replicates an Active-Neutral Point Clamped (ANPC) inverter and was designed using a hardware language known as VHDL (Very High-Speed Integrated Circuit Hardware Description Language) and applied to Field-Programmable-GateArray (FPGA). The DT is embedded within the FPGA and contained in a controller board, the UCB (Unified Controller Board), developed by the University of Arkansas electrical engineering team. This UCB also contains two Digital Signal Processors (DSPs) responsible for generating associated signals to control an authentic physical inverter. These DSP signals are received and processed by the FPGA that implements the DT of an ANPC; in other words, it simulates in realtime the expected output of an actual ANPC inverter using the signals from the DSP. When a new firmware is ready to be patched, the DT provides output signals simulating behavior that a real ANPC inverter would generate with the new firmware. The new firmware is tested to check if it meets all the operational requirements established using a Design-For-Trust technique (DFTr). If the new firmware fails in at least one of the DFT tests, it is considered malicious and must be rejected. This work is divided into sections, such as Background, which explains the pieces that were used and the strategy behind this work; Process and Procedure, which explains the methodology that was adopted to prove the reliability and effectiveness of this work; Results and Discussion, where the simulations and results are described and explained; followed by Conclusion and Future work section, which concludes this work and adds possible future projects to continue this work further.

do Amaral Custodio, Paulo Vitor↗
DOE OSTI2022

CPES-QSM: A Quantitative Method Towards the Secure Operation of Cyber-Physical Energy Systems

Power systems are evolving into cyber-physical energy systems (CPES) mainly due to the integration of modern communication and Internet-of-Things (IoT) devices. CPES security evaluation is challenging since the physical and cyber layers are often not considered holistically. Existing literature focuses on only optimizing the operation of either the physical or cyber layer while ignoring the interactions between them. This paper proposes a metric, the Cyber-Physical Energy System Quantitative Security Metric (CPES-QSM), that quantifies the interaction between the cyber and physical layers across three domains: electrical, cyber-risk, and network topology. A method for incorporating the proposed cyber-metric into operational decisions is also proposed by formulating a cyber-constrained AC optimal power flow (C-ACOPF) that considers the status of all the CPES layers. The C-ACOPF considers the vulnerabilities of physical and cyber networks by incorporating factors such as voltage stability, contingencies, graph-theory, and IoT cyber risks, while using a multi-criteria decision-making technique. We note that simulation studies are conducted using standard IEEE test systems to evaluate the effectiveness of the proposed metric and the C-ACOPF formulation.

24 POWER TRANSMISSION AND DISTRIBUTION↗